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Understanding Automated Customer Service in 2026

Posted on Michael Hartsog

Key Takeaways

  • Automated customer service uses AI agents and self-service portals to handle customer interactions without human agents, ranging from simple FAQ responses to complex issue resolution like processing returns and managing account changes.
  • Agentic AI represents the most advanced automation capability, executing multi-step tasks autonomously while maintaining context across channels, unlike traditional chatbots that only provide scripted responses.
  • Successful automation implementation requires integrating with existing CRM systems, designing clear escalation paths to human agents, and maintaining brand voice consistency across all automated interactions.
  • Automation effectiveness is measured through containment rates, customer satisfaction scores, and cost per contact metrics, with the distinction that deflecting customers differs from actually resolving their issues.

Automated customer service is the use of technology—AI, last-gen chatbots, next-gen AI agents, self-service portals, and workflow automation—to handle customer inquiries without requiring a human agent for every interaction. It ranges from simple FAQ bots to sophisticated AI agents that can troubleshoot issues, process returns, and manage account changes autonomously.

This guide covers how automation works, the types of automated customer service tools available, implementation best practices, and how to measure whether your automation is actually helping customers or just deflecting them.

What is automated customer service?

Automated customer service uses technology like AI, chatbots, and self-service portals to handle customer inquiries without a human agent involved in every conversation. At its simplest, automation might answer a frequently asked question. At its most advanced, it can troubleshoot a technical issue, process a return, or update a subscription—all without a person stepping in.

The point here isn’t to replace your support team. It’s to handle the repetitive, high-volume questions so your agents can spend their time on conversations that actually benefit from human judgment and empathy.

How automated customer service works

When a customer reaches out through chat, email, phone, or SMS, the automated system first figures out what they’re trying to accomplish. This happens through natural language processing, or NLP, which analyzes the words and context to determine intent.

From there, the automated customer service system either retrieves the relevant information, takes an action like updating an account, or routes the conversation to a human agent if the issue falls outside its capabilities.

What separates good automation from frustrating automation is whether context carries through this entire process. When it does, customers don’t have to repeat themselves if they get transferred.

Types of automated customer service solutions

The automation landscape spans a wide range of sophistication. Understanding the differences helps clarify what might fit your operation.

Self-service knowledge bases

A knowledge base is essentially a searchable library of articles, FAQs, and how-to guides. Customers can find answers on their own, which works well for straightforward questions. The tradeoff is that customers do the searching themselves, and if the answer isn’t easy to find, they’ll reach out anyway.

Rule-based chatbots

Rule-based chatbots follow pre-programmed decision trees. If a customer says X, the bot responds with Y. They handle predictable, simple customer queries reasonably well, but they struggle when customers phrase questions in unexpected ways or have issues that don’t fit the script.

AI-powered virtual assistants

More flexible than rule-based bots, AI-powered assistants use NLP to understand varied inputs and provide relevant responses. However, many of them can only surface information. They can tell you your order status, for example, but they can’t actually change your shipping address.

Automated ticket routing and email workflows

This type of automation handles ticket routing, sorting, tagging, and directing incoming requests to the appropriate team or agent based on predefined criteria. It reduces the manual triage work that eats up supervisor time and helps ensure inquiries reach someone equipped to handle them.

An automated ticketing system like this also helps care teams manage high volumes without sacrificing service quality.

Agentic AI platforms

Agentic AI sits at the most capable end of the spectrum. Unlike traditional chatbots, agentic AI can reason through multi-step problems, execute actions autonomously, and maintain context across channels and conversations.

Rather than just answering questions, agentic AI actively resolves issues. It can process a return, troubleshoot a device, or manage a subscription change without human intervention.

6 Biggest benefits of automated customer service

The advantages of automation show up across operations, customer experience, and the bottom line. Understanding the full benefits of automated customer service helps make the case for investing in the right platform.

1. Reduced cost per contact

When automation handles high-volume, repetitive inquiries, human agents focus on complex, high-value conversations. This shift typically lowers the average cost of each customer interaction and reduces overall support costs.

2. Around-the-clock availability

Customers expect help at any hour, well beyond standard business hours. Automation delivers 24/7 support without the expense of overnight staffing or teams working across time zones, making it easier to serve customers globally.

3. Faster response and resolution times

Automated systems respond instantly to common questions. That eliminates the wait times that frustrate customers and clog your queue during peak hours.

4. Consistent and accurate answers

Even excellent support agents occasionally provide inconsistent information. Automation pulls from approved knowledge sources every time, so customers receive consistent service with the same correct answer regardless of when they reach out.

5. Improved agent productivity

With fewer repetitive tasks on their plates, agents can dedicate energy to conversations that benefit from human judgment and relationship-building, which strengthens customer relationships over time.

6. Scalability without adding headcount

Seasonal spikes, product launches, or unexpected surges in volume can overwhelm a support team. Automation absorbs fluctuations without requiring temporary hires or overtime, and automation solutions scale to meet demand as your business grows.

Challenges to avoid with customer service automation

Automation can backfire when implemented poorly. Here are the pitfalls that damage customer trust and erode customer loyalty.

Forcing customers to repeat themselves

This happens when conversation context doesn’t carry over between channels or during handoffs from automation to a human agent. Few things frustrate customers more than explaining their issue multiple times, and customer frustration like this is one of the fastest ways to lose trust.

Blocking access to human agents

Making it difficult or impossible to reach a person erodes trust quickly. Even customers who prefer self-service want the option to escalate when their situation calls for it. Both your customers and your support agents benefit when escalation paths are clear and easy to access.

Generic responses that miss context

Canned, irrelevant answers signal that your system doesn’t actually understand the customer’s problem. This often happens when automation lacks access to account data or conversation history. Personalized support requires that your automated system can draw on customer data to tailor its responses.

Black box AI with no decision visibility

For regulated industries especially, using AI that makes decisions without providing an audit trail creates compliance risk. Even outside regulated sectors, teams benefit from understanding how and why the AI responded a certain way.

Poor integration with existing systems

Automation that can’t connect to your CRM, order management, or other business systems can’t deliver personalized or effective resolutions. Integration is foundational to making automation work, including updating customer records accurately and in real time.

How to automate customer service

Implementing automation effectively takes a structured approach. Here’s a practical framework for implementing automated customer service in your organization.

1. Identify your highest volume support tasks

Start by analyzing your ticket data and support analytics. Which inquiries come in most frequently? Which ones are repetitive and straightforward? Those routine tasks are your prime candidates for automation.

2. Select the right customer service automation software

Evaluate vendors based on integration capabilities, AI sophistication, transparency and governance features, and brand customization options.

The right automated customer service software depends on your specific operation and existing tech stack. Look for automated customer service solutions that align with your customer service strategy and can grow with your needs.

3. Integrate automation with your CRM

Connecting automation to your CRM and other data sources enables personalized, context-aware responses. Without this integration, your automation operates blind to customer history and account details.

4. Design clear escalation paths to human agents

Automation works best when it recognizes its own limitations. Build in clear triggers for when a conversation transfers to a human, and ensure the full context transfers along with it. This is especially important for more complex customer needs that require technical expertise or emotional sensitivity.

5. Test automation before full deployment

Use A/B testing and pilot programs with a subset of customer traffic before rolling out broadly. This approach surfaces issues while the stakes are still low.

6. Monitor performance and optimize continuously

Automation isn’t a set-it-and-forget-it solution. Use performance analytics to identify gaps, refine responses, and expand capabilities over time.

Best practices for automated customer support

Beyond implementation, a few practices separate effective automation from frustrating experiences.

Preserve your brand voice in every automated response

Generic, robotic templates feel impersonal. Configure your automation to communicate in a voice consistent with your brand, the same tone customers encounter elsewhere in their journey.

Maintain context across all channels

A customer might start on web chat, switch to SMS, then call in. True omnichannel support maintains one continuous conversation across all of those touchpoints, reducing customer effort and improving the overall customer journey.

Monitor customer feedback to improve automation

Post-interaction surveys and customer feedback analysis reveal where your automation falls short. Use that data to close knowledge gaps and refine conversation flows. When you monitor customer feedback consistently, you can anticipate customer needs before they become recurring issues.

Set guardrails for AI governance

Implement controls, audit trails, and visibility into AI-driven decisions. These protect your brand and ensure compliance with relevant regulations.

Empower automation to resolve issues

Automation that can only answer questions but can’t take action, like processing a return or updating an address, leaves customers with an incomplete experience. Automated customer support systems should be empowered to handle customer requests end to end wherever possible.

Automated customer service examples

Here’s where automation delivers the most value across common use cases, with agentic AI examples pushing the boundaries of what’s possible:

  • Account management and billing inquiries: Balance checks, payment updates, and subscription changes.
  • Order tracking and delivery updates: Proactive support through shipping notifications and self-service status lookups.
  • Technical troubleshooting: Guided diagnostic steps that resolve common issues without agent involvement.
  • Appointment scheduling: Booking, rescheduling, and sending reminders automatically.
  • Returns, exchanges, and refunds: Processing requests and generating shipping labels based on business rules.

These automated customer service examples illustrate how automation tools can address routine service tasks across the full range of communication channels your customers use.

How to measure customer service automation success

Tracking the right key metrics reveals whether your automation is helping or hurting.

Containment rate and resolution rate

Containment rate measures the percentage of inquiries handled entirely by automation. Resolution rate goes a step further, measuring the percentage of issues actually solved by automation. The distinction matters because deflecting a customer isn’t the same as helping them.

Customer satisfaction and NPS

Customer satisfaction scores (CSAT) and Net Promoter Score confirm whether automation is improving or degrading the customer experience. If scores drop after implementation, something’s off. Tracking improved customer satisfaction over time is one of the clearest signals that your automation is working.

Average handle time and first response time

Automation typically improves both metrics by providing instant responses to common questions and reducing the workload on customer service agents.

Cost per contact

Total support cost divided by total interactions. Customer support automation typically lowers this metric over time as it absorbs more volume.

Agent productivity metrics

Track how automation frees up customer service agents to focus on higher-value work. One indicator is whether the complexity of issues agents handle increases as automation takes over simpler inquiries. This shift toward complex issues is a sign that your customer service team is operating at its full potential.

Customer effort score

Customer effort score measures how easy it is for customers to get their issues resolved. Automation tools that reduce friction across self service solutions and digital channels should drive this score down over time.

Customer loyalty

Repeat purchase rates, retention rates, and customer lifetime value reveal whether automation is building or eroding trust over time. If customers return more often and churn less after automating customer service tasks, that’s a strong signal your system is creating positive experiences and meeting customer expectations — not just deflecting support tickets.

How customer experience automation has evolved from chatbots to agentic AI

The progression from early automation to today’s capabilities has been significant. Scripted interactive voice response systems gave way to rule-based chatbots, which evolved into NLP-powered assistants.

Now, agentic AI represents the current state of the art, and machine learning continues to push capabilities further.

What distinguishes agentic AI is its ability to reason through problems, execute multi-step tasks, and maintain continuous context, not just within a single conversation, but across channels and over time.

Agentic AI doesn’t just respond. It resolves. And as automated customer support systems grow more capable, they are increasingly able to handle complex customer scenarios that once required human involvement, including automating routine inquiries at scale.

Start automating customer service with confidence

The right automation platform makes the difference between frustrated customers and efficient, satisfying experiences. What matters most is transparency into how AI makes decisions, continuous context across every channel, and the ability to scale your brand’s authentic voice.

If you’re evaluating automation for your CX operation, we’d welcome the chance to show you how Quiq approaches this. Book a demo to see agentic AI in action.

Frequently Asked Questions (FAQs)

How does natural language processing work with knowledge bases in automated customer service?

Natural language processing (NLP) allows automated systems to understand customer inquiries written in everyday language, interpreting intent rather than relying on specific keywords. When paired with a knowledge base, NLP searches your stored documentation and policies to surface the most relevant answer — meaning response quality scales directly with how well your knowledge base is maintained.

How much does it cost to implement automated customer service?

Costs vary widely based on complexity, platform choice, and integration requirements. Most vendors offer tiered pricing based on conversation volume or feature sets, so the investment scales with your operation.

What is the difference between a chatbot and automated customer service?

A chatbot is one specific tool within the broader category of automated customer service. Automated customer service encompasses customer service automation tools, like chatbots, email routing, voice automation, self-service portals, and AI agents capable of executing complex actions.

Can automated customer service handle complex or emotional customer issues?

Advanced AI can handle many complex issues, though the best implementations recognize when to escalate sensitive or emotional conversations to human agents, preserving full context during the handoff.

Will automated customer service replace human support agents?

Automation handles routine, repetitive tasks, which augments human teams rather than replacing them. This allows agents to focus on complex issues, relationship-building, and situations requiring empathy. Customer support teams remain essential for the conversations that automation can’t fully resolve.

How long does it take to implement customer service automation?

Timelines range from a few weeks for basic chatbots to several months for enterprise-grade agentic AI platforms, depending on integration complexity and customization requirements

11 Live Chat Best Practices for Exemplary Service

Posted on Max Fortis

Key Takeaways

  • Live chat software helps convert visitors into loyal customers. Placing a live chat widget on product pages and specific pages across your website gives potential site visitors instant access to support at the moment they need it most — reducing wait times and boosting customer satisfaction.
  • The perfect balance between AI and human agents is essential. AI can handle simple queries, while humans take over complex issues — ensuring efficiency and quality in every interaction.
  • Preparation is key. Gathering information before a chat begins — such as contact details, order numbers, or topic categories — lets your support team skip repetitive questions and jump straight to resolving the issue. Well-crafted canned responses further help agents respond faster without giving vague answers.
  • Seamless, continuous chat support builds trust. Asynchronous live chat support means customers never lose their conversation history and agents are always well versed in the full context — whether handling routine requests or more complicated queries.
  • Security, sentiment analysis, and feedback loops keep your chat best practices sharp. Protecting customer data, monitoring conversation sentiment, and asking for end-of-chat feedback help teams uphold company standards, improve over time, and deliver consistently exceptional support.

Don’t deliver good customer service. Aim for the exceptional service that sets you apart from your competition. Customers demand convenience, speed, and ease when they need to engage with a company. When it comes to live chat (also known as web chat), it’s critical to provide an experience that welcomes the customer to engage with your brand.

Your live chat window serves as your front line to the customer on your website. This messaging channel allows you to engage with your customers at their point of purchase for higher conversions.

With live chat, customers can reach your brand at their convenience and receive the pre-sales support or post-sales service they need. This blog post gives you the 11 live chat best practices to deliver the ultimate customer experience.

What is live chat support, and how does it work?

Live chat is a messaging tool integrated into a brand’s website, app, or third-party platform that enables instant communication with customers regarding orders, inquiries, or issues. Unlike email or chatbots, live chat provides a more personalized and real-time interaction.

As demand for immediate support increases, live chat software has become a vital solution for brands, allowing them to engage with users instantly. It is commonly used to resolve customer issues, offer after-sales support, and provide quick troubleshooting, all of which contribute to higher customer satisfaction and retention.

Since AI is evolving at such a rapid pace, companies that win with this tech don’t just add chatbots to answer simple queries. Instead, they add layers of agents that can do very specific things, like booking a call, changing an order, or requesting a refund.

The way live chat works will depend on your unique use case, such as your industry, the kinds of live chat agents you use and more. However, this is the most typical workflow:

  1. A visitor opens the chat widget on a website or inside an app and starts a conversation.
  2. An AI agent responds first, greets the visitor, and asks what they need help with.
  3. The AI gathers details by asking simple questions, identifies the intent, and suggests answers based on past support content, order data, or account information.
  4. If the request is simple, the AI resolves it on its own, for example, by sharing order status, return steps, or policy details.
  5. If the issue is more complex, the AI routes the conversation to a human agent with the full context included.
  6. The human agent joins the chat without asking the customer to repeat information and continues the conversation.
  7. The agent can see the full transcript, customer profile, and any actions already taken by the AI.
  8. Once resolved, the conversation is saved and used to improve future AI responses and support workflows.

Live chat is an excellent customer support channel for many reasons. You can resolve customers’ problems quickly and thanks to AI agents, at a low cost too. Whether you’re already using live chat or considering a new tool to manage customer queries, here are some best practices to keep in mind.

11 live chat best practices for handling customer queries

From setting your business hours to having an always-on chat window, there are quite a few things you can do to provide the best live chat support possible. This is where to start.

1. Choose the right live chat platform for your business goals

Choosing the right live chat platform has a direct impact on how fast your team responds, how consistent your support feels, and how easy it is to scale as volume grows.

Instead of picking a tool based on brand recognition alone, start by mapping your actual support workflow. Look at where conversations begin, how they move between agents, and what systems agents already use. The platform you choose should support that flow rather than forcing your team to adapt to rigid processes.

Focus first on real-time performance and reliability.

Test how quickly messages appear for both agents and customers, how stable the connection is during busy periods, and whether conversations are ever delayed. A slow chat experience creates frustration and can make customers abandon the session. Run trials during peak hours and simulate multiple chats at once to see how the system handles load.

Next, look closely at integrations.

Your chat tool should connect directly to the systems your team uses every day, such as your CRM, order management platform, help desk, or knowledge base. This allows agents to see customer history, previous tickets, and account details without switching tabs.

Ask practical questions during evaluation. Can agents view past purchases instantly? Can they update customer records from within the chat? Can conversations be saved automatically? These details matter more than surface-level features.

Ease of use is just as important as functionality.

A complex interface slows down response times and increases training time for new hires. Have several agents test each platform and ask them to complete real tasks, such as finding a past conversation, transferring a chat, or sending saved responses. If they struggle to do basic actions quickly, the tool will create friction over time.

Analytics should help you improve performance, not just collect data.

Look for reporting that shows first response time, resolution time, agent workload, and customer satisfaction trends. Make sure you can break results down by team, time period, or issue type. These insights help you spot gaps in staffing, identify training needs, and understand when customers are most active.

Security and compliance should also be part of the evaluation.

Check whether the platform offers role based access, data encryption, and audit logs. If your team handles payment details, personal data, or account access, you need clear controls over who can view and export conversations. Ask vendors how they store transcripts and how long data is retained.

Finally, test before committing.

Run a pilot with a small group of agents and route a portion of real customer chats through the platform. Pay attention to how agents feel using it, how quickly they can solve problems, and whether customers respond positively.

Collect feedback after a few weeks and compare results against your current setup. The right choice is the one that makes it easier for agents to help customers quickly, consistently, and confidently.

2.  Be transparent with your availability and set your business hours

While larger brands may have a customer support team working 24/7, other businesses may have limited hours. If you’re one of the companies that limits the hours of support, make sure that you simply disable live chat when your team is unavailable or when your company is closed. Quiq’s chat feature allows you to remove the chat bubble on your site during non-supported hours.

If your chat function isn’t available 24/7 and you prefer to receive after-hours messages, tell your customers that you’ve received their message and let them know when you will get back to them.

The most important thing is to be transparent when someone is likely to reply and when a human agent will be able to give the customer their full attention.

If you’re not sure when your busiest hours are, you can use analytics to discover when most live chat conversations happen to assign more agents during those hours.

3. Collect information upfront (it helps agent productivity)

Make it easy for employees to provide a more personalized experience to your customers by collecting a little information upfront. If you don’t have an AI agent integrated with your live web chat yet, use a short web form to collect information. This information can be used to route incoming conversations to the best queue or employee.

Not only that, this extra information will help your employees identify the customer and the nature of their inquiry immediately, instead of having to spend valuable time asking for it. Knowing their full name, account number, topic category, or order number will help your team know who they are talking to and allow them to get a jump on helping the customer faster.

4.  Balance personalization and professionalism

Customers expect live chat interactions to be both personal and professional. Striking the right balance between empathy and professionalism can be challenging, but it is key to a positive customer experience.

To help agents achieve this, implement features like skill-based routing to direct inquiries to the most knowledgeable team members. For example, technical support queries can be automatically sent to agents with expertise in the specific product. Additionally, using a unified inbox in your live chat tool allows agents to view all customer messages in one place, streamlining responses and ensuring consistency.

Providing agents with complete context—such as customer history and preferences—can also improve personalization. This empowers agents to tailor their responses, maintaining a professional yet empathetic tone throughout the conversation.

5. Always be ready to respond

Customers want answers fast and at their own pace. That’s one of the key reasons they’re avoiding the phone and having to be tied to it. With live chat, customers can send messages at their own pace, whether they do so in 3 minutes or 3 hours. Companies can set service level agreements (SLA’s) so that everyone understands what an acceptable response time is for customers when they do reach out.

Quiq helps employees meet those SLAs with our Adaptive Response Timer (ART). This feature not only provides visual cues to notify employees when a conversation needs attention, but it also automatically prioritizes multiple conversations based on how slow or fast the customer is responding to messages.

This is critical because chat agents tend to handle 5 or more conversations at one time. Staying on top of the right ones is easy with Quiq.

6. Never get disconnected from the chat window

Your customers are busy and, at times, may need to step away from a conversation. Sometimes, it’s only for a few minutes while they check another tab on their desktop. At other times, it may be a lot longer.

When customers don’t respond after a certain time limit, most chat systems will “time out” chat sessions, requiring the customer to initiate a new chat session and start their entire process from the beginning.

Unlike many traditional chat tools, Quiq’s chat platform is asynchronous, which means conversations never end and never have to be restarted. This avoids customer frustration of having to restart a conversation and agent uncertainty when a customer goes dark.

Customers can return to the chat whenever it is convenient for them. This conversational continuity gives your agents and your customers peace of mind. For example, they could ask a question in the live chat widget, hop out for lunch, open the same window and the conversation will still be there.

Agents never lose track of conversations and customers feel heard, without having to restart the same conversation over and over again.

7. Present the chat history

Sure, some customers may only need to contact you once, but there are some who need to reach you on a more frequent basis. It’s important that a record is kept of all the past chat interactions you’ve had with a customer.

This conversation history serves as an excellent reference point and helps agents or employees know what kind of issues the customer may have encountered previously and the guidance they were given.

For example, someone may have reached out two months ago about a billing issue and they were pretty upset. They reach out again and if the agent doesn’t know the context, they’ll keep sending canned responses instead of trying to calm the situation down.

Quiq presents the entire conversation history to the agent, along with the most recent inquiry. Let’s say a customer starts a conversation with one agent, walks away during the conversation, and comes back while that first agent is on break. The newly assigned agent will have the same latest interaction, as well as past interaction history, presented.

This makes customer inquiries more efficient as the agent knows the entire account history, whether it happened through live chat bots, phone support or email. You get a boost in agent productivity as they can track the entire customer journey without leaving their dashboard and customers feel heard and understood.

Speaking of which…

8. Provide a seamless customer experience

From time to time, one of your employees may not know how to answer a specific question from the customer. So, they will need to transfer the customer to another team member.

When this happens, you need to guarantee that the customer doesn’t have to explain her question or problem all over again. The new team member should have access to the previous conversation and simply continue the conversation.

Quiq’s transfer and collaboration features allow employees to ask for help behind the scenes from peers or managers. Customers can be easily transferred to other team members and support agents, with or without them even knowing.

Anyone invited to help with the conversation can see the entire history of the conversation and any additional information available on the customer. These features create a seamless experience for your customers while optimizing efficiency.

This becomes increasingly important if you’re training new customer support or sales team members but don’t want to risk them getting stage fright on a call.

9. Ensure authentication & data security

As online data breaches rise, securing live chat interactions is essential to maintaining customer trust. Sensitive data exchanged through live chat is vulnerable to malicious attacks, which can damage your brand’s reputation.

Implementing encryption, two-factor authentication (2FA), and single sign-on (SSO) helps protect this information and assures customers that their data is secure. Most proven live chat tools have these features but it’s worth asking which features you get and in which plan.

Additionally, role-based access controls limit sensitive information to authorized personnel only, preventing unauthorized access. By prioritizing robust data security in your live chat platform, you not only protect your customers but also enhance their confidence in your brand, improving conversion rates and customer loyalty.

10. Use sentiment analysis

Use sentiment analysis to understand how customer conversations are going. This is particularly important for companies that may have a large number of chat conversations to manage. Managers can see at a glance which conversations are going well and which may be at risk.

Quiq uses simple visual cues that identify if customers’ mood shifts during a conversation. Agents and managers can quickly see if a conversation needs extra attention or needs to be prioritized.

Sentiment analysis becomes increasingly important with AI agents. A real person can sense the shift in tone somewhat easily, but agents that simply give pre-written responses without considering sentiment can do massive damage to your sales and customer support.

With AI sentiment analysis, you can get valuable insights such as:

  • Which instant answers sit well with customers, and which ones cause them to lash out or leave the conversation
  • Which types of questions get negative sentiment in responses so you can escalate to human agents
  • Which areas of your support/sales require additional agent training

While not perfect, sentiment analysis helps you take proactive measures to make your customer support operations better, with a more human touch.

11. Ask for feedback at the end

Your customers’ feedback or opinion about how the live chat interaction went is definitely a best practice. You trained your team members to provide the best service they could, but the ultimate test will be what people think about their overall experience.

This is a timely way to know that you’re on the right track, as well as a great way to continuously improve your live chat experience.

There’s another way you can make the most out of this live chat session. If the customer is satisfied with the provided answer, you can use a chat feature to point them to your favorite review site straight from the live chat window and ask them to leave a review.

When the experience is still fresh in their minds, they’re more likely to provide an excellent score and review.

Live chat is your front line for customer issues

It wasn’t so long ago that the only way someone could get in touch with a company was by picking up the phone and calling. Now, with live chat and messaging options, people can simply click-to-chat with a representative who can provide the pre-sales support or post-sales service they need.

Being available to your customers at their “moment of need” is where businesses turn visitors to their website into lifelong buyers who love their product and service and rave about their experience. Live chat may be one of the first interactions your customers have with anyone from your company. Make sure you leave a great first impression by implementing these 11 live chat best practices.

Ready to provide exceptional, personalized and AI-powered customer support? Get a demo of Quiq today.

Frequently Asked Questions (FAQs)

What are the most important live chat best practices for improving customer satisfaction?

The most impactful live chat best practices include reducing wait times with fast response times, using a live chat widget that stays persistent so users never lose their conversation, collecting customer information upfront to avoid repetitive questions, and following up every interaction with a feedback request. Together, these practices create a seamless experience that drives customer satisfaction and loyalty — whether you’re a small e-commerce brand or a large enterprise.

How do canned responses improve chat support without feeling impersonal?

Canned responses save time by giving agents a library of pre-written replies for common questions, helping the support team maintain consistency and uphold company standards. The key is personalization: agents should use them as a starting point and tailor the message to the customer’s specific situation. When done well, canned messages speed up response time without producing the vague answers that frustrate people.

How should live chat handle complex issues?

For more complex queries, live chat software should route conversations from AI agents to human reps who are well versed in the relevant area. The handoff should be seamless — the human rep should have full context, including conversation history and customer information, so the customer never has to repeat themselves. Certain features like skill-based routing and behind-the-scenes collaboration tools play a key role in making this transition smooth.

What role does live chat play in e-commerce and converting potential buyers?

Live chat plays a key role in e-commerce by engaging potential customers directly on product pages and specific pages where purchase decisions are made. A well-placed live chat widget allows new visitors to ask questions in real time, reducing hesitation and cart abandonment. When agents can quickly capture information, provide accurate answers to solve a customer’s problem, and guide shoppers through the buying process, both efficiency and conversion rates improve significantly.

How is live chat different from tools like email or phone support?

Unlike email or phone support, live chat support offers real-time, asynchronous communication that people can engage with at their own pace — without long wait times or being tied to a phone. Live chat software also enables agents to handle multiple conversations simultaneously, integrates with your CRM and other tools for full customer context, and supports both efficiency and a human touch through AI-assisted routing and sentiment analysis. For most businesses today, it’s one of the best tools for delivering fast, personalized support at scale.

8 Customer Retention Strategies That Work

Posted on Lauren Winder

Key Takeaways

  • Retention drives growth: Keeping existing customers is far more cost effective than acquiring new ones, and loyal customers spend nearly 70% more.
  • A loyal customer base builds advocacy: Repeat customers are more likely to recommend your brand and provide valuable feedback through surveys like CSAT and NPS.
  • Track the right metrics: Monitoring Customer Retention Rate (CRR) alongside Cost per Acquisition (CPA) gives you a clearer picture of profitability and long-term success.
  • Effective strategies matter: From building relationships on shared values to empowering customer service teams, offering omnichannel support, personalizing communications, and rewarding loyalty can significantly improve retention.
  • Feedback fuels improvement: Surveys, complaints, and direct customer input are opportunities to make meaningful adjustments that keep customers engaged.
  • Sustainable success: Strong customer retention doesn’t just stabilize revenue, it creates lasting relationships that separate enduring businesses from short-lived ones.

Recruiting new customers costs seven to nine times as much as it does to keep existing customers happy. Besides the obvious foregone revenue, dissatisfied customers are not going to recommend you to the people they know, and they might even go out of their way to tell their friends and family about their negative experiences. This kind of fallout can have long-term consequences for customer retention.

For all these reasons, it’s imperative to retain customers – and one of the best ways of doing that is to implement an effective customer retention strategy.

Even a small increase in your customer retention efforts could substantially improve your bottom line, but customer retention can be extremely challenging. Having said that, enhancing customer retention can be challenging and generally requires an intentional strategy that many companies don’t choose to prioritize.

In this article, we will examine the big picture of why improving customer retention is important and offer customer retention strategies that any customer experience team can implement to keep its customers happy and loyal.

What is customer retention?

Customer retention refers to any effort to keep a customer satisfied enough with you to keep them using your products or services.

Customer retention is an important aspect of business strategy and, done correctly, can help you gain a competitive advantage. Tragically, many businesses don’t invest enough in it – they spend vast amounts of time and money trying to boost their customer acquired while neglecting the ones they’ve already worked so hard to get.

But with the right approach and high-quality service, there’s no reason that excellent customer retention can’t be one of the things setting you apart.

Why is it important to retain customers?

What makes customer retention important is that acquiring more customers costs more than keeping old ones. It’s also worth pointing out that existing customer accounts spend an average of almost 70% more than new customers.

Even better, customer value goes up with loyalty. Think about it: Loyal customers are far more likely to share their experiences with their social media circles, build a strong customer community, and drive repeat business. The more loyal the customer, the higher the customer lifetime value (CLV).

These customers are not only your best cheerleaders, they also help you better understand your brand in various other ways, like via CSAT and NPS (Net Promoter Score®) surveys. If you ask them, they will provide honest feedback about your products or services, allowing you to make the course corrections required to succeed. We’ll have more to say about all this in the section on improving customer retention strategies that drive long-term customer retention.

Calculating your customer retention rate

To measure customer retention, start with determining your current customer retention rate (CRR).

The CRR measures how many customers are retained over a particular period (usually one year) and allows you to gauge the long-term profitability of your marketing and sales efforts. It’s also a key metric for evaluating the success of your overall customer retention strategies. The math is pretty straightforward: we just need to divide your number of customers who made repeat purchases by the total number of active customers over the same time period.

So, if we have 50 return customers and 200 active customers for the year 2026, our CRR would be 25%.

A related metric worth tracking is the cost per acquisition (CPA). The CPA measures the cost a company incurs to acquire one new customer (ideally, a new customer who becomes loyal to the company’s brand).

If you have both the CRR and the CPA, you should have a good chunk of the context needed to make smart, data-driven decisions. If you want to increase your retention rate, read the next section.

Now that we’ve made a strong case for trying to enhance customer retention, let’s discuss specific strategies that’ll help you actually do it.

8 Effective customer retention strategies

Use these robust customer retention strategies to meet customer expectations and keep more current customers.

1. Strong values strengthen customer relationships

Many companies have “mission” or “vision” statements that explicitly state the values they live by. Though these statements are sometimes viewed as hot air that only serves to give the marketing team something to put on the company website, the truth is that your processes, the quality of your products, and the way you treat your customers are all a reflection of them.

This is a long way to say that values are important, but you don’t have to take our word for it. When asked, many customers who stated they had a relationship with a brand indicated that it was due to shared values. This isn’t surprising – customers will naturally be attracted to brands that mirror their beliefs while enhancing their lifestyles, especially when they’re younger.

Building a brand that your customers can easily relate to will foster trust and drive customer acquisition. This is key to creating strong relationships and, by extension, a successful business. Let your customers know what you stand for, and be sure to act on these convictions (by donating to worthy causes, for example). Having common values with your customers makes it easier to attract and retain them.

2. Empower your customer experience team

As a CX leader tasked with building, operationalizing, and scaling your contact center, you undoubtedly think about human agents’ interactions with customers. An important element in that equation is how you empower your team of customer service representatives to grow and build trust with your customers.

To achieve this, focus on comprehensive training programs that emphasize empathy, active listening, and effective problem-solving. For instance, role-playing scenarios can prepare agents to handle customer feedback with confidence and care. Implementing regular workshops and continuous learning can help your team stay up to date on the latest trends and best practices.

Many organizations are now leveraging AI-powered roleplay platforms such as Kendo AI to simulate realistic customer conversations, helping teams sharpen their communication skills and deliver more consistent, high-quality experiences that directly impact customer retention.

Implementing a customer feedback loop can help your team understand and respond to customer needs more effectively. Encourage your agents to ask for feedback after interactions and use this information to improve service delivery. Monitoring key performance indicators (KPIs) such as customer satisfaction scores (CSAT), Net Promoter Scores® (NPS), and first-call resolution rates can provide valuable insights into how well your team is building trust.

3. Make yourself easy to work with

A great way to stand out is by making it as easy as possible for customers to find what they need. If your documentation or website is complex or confusing, this is certain to become a problem at one point or another. Clear, concise information, on the other hand, can help enhance customer retention.

Take the issue of refunds. If a customer is looking for a refund, they’re obviously dissatisfied. How much worse will they feel if they must then struggle to find a way to contact you, only to be faced with a maze of robotic voices endlessly repeating a menu of options?

If your agents are sympathetic and your information is easy to navigate, a refund needn’t be the end of a professional relationship. More broadly, it pays to invest the time required to make your content easy to follow and your agents easy to contact. Frustration at this level can erode trust and severely impact your customer retention programs.

One often overlooked factor in customer retention is experience consistency across touchpoints. When interfaces, flows, or messaging feel disjointed, even strong products can become frustrating to use. Superside’s research into customer experience design shows that consistent UI patterns, predictable interactions, and clear visual hierarchy reduce friction and build trust over time, especially as products scale and teams grow.

4. Offer omnichannel customer support

Customers love great offers and discounts, but they also love it when they can get help solving problems with as little friction as possible.

A good way to do this (and improve customer retention simultaneously) is to provide support through the channels that make the most sense for your customers, from social media to texting. There are a few other advantages to this omnichannel approach:

  • It enables you to respond very quickly to incoming queries, which can be a huge advantage for reasons already discussed above.
  • By integrating with technology like large language models, you can personalize your replies at scale and even offer services like real-time translation.
  • Faster resolution means you’ll increase customer retention and enhance customer loyalty.

5. Reply ASAP in customer interactions

Few things will result in customers lost than taking too long to respond to an issue. As a general rule, people have never enjoyed waiting around. It tends to dampen customer experience.

For this reason, you want to reply to issues as quickly as possible so they remain loyal.

This doesn’t necessarily mean you have to resolve an issue right off the bat. Many customers will feel less anxious and frustrated simply by knowing they’ve been heard and someone is working on a solution. Respond immediately, even if it’s just to say, “We’re sorry you’re running into issues, and we’re committed to getting you up and running again as soon as possible.”

You can also take this initial message as an opportunity to manage expectations about how long it will take to find a solution. Obviously, some problems are relatively straightforward, while others are more substantial, and you can communicate that to the customer (assuming it’s appropriate to do so). It’s never fun to hear that you’ll have to wait a week to get some issue sorted out, but it’s far worse to find that out after you’ve already made a bunch of plans that are difficult to change.

6. Personalize your communications

Artificial intelligence has a long history of delivering personalized content that builds customer loyalty. You’re probably familiar with Spotify, which can discover patterns in the music and podcasts you enjoy and use algorithms to recommend songs and artists that align with your tastes.

With the power of agentic AI, platforms like Quiq are elevating personalized experiences to unprecedented levels. Agentic AI enables AI agents to customize customer interactions and improve their customer journey based on past preferences and interactions.

Once upon a time, only human agents could analyze a customer’s profile and tailor their responses with relevant information. Now, a well-optimized generative language model can achieve this almost instantaneously – and on a much larger scale – translating into greater customer success. You can even re-engage customers on a 1:1 scale with smart AI use.

7. Implement customer feedback into your products or services

Customer data can help determine your customers’ needs, and surveys are an effective way to gather that data, including NPS (Net Promoter Score®) surveys. Some of the benefits of conducting customer surveys include:

  • They’re a great way to understand customer behavior and your customer lifecycle.
  • Encouraging customers to give honest and open feedback makes your brand appear open to customer concerns and are willing to do whatever it takes to make them happy.
  • These customers will be more likely to give both positive and negative feedback in the future if they see changes implemented based on their pain points.
  • Survey feedback can result in positive adjustments to your processes, products or services.
  • It can help ensure you’re pursuing the right targeting strategy
  • They can help you identify dissatisfied customers before they leave, and create campaigns or offers to win them back.
  • By the same token, surveys help you better understand why satisfied customers are happy.

Of course, surveys aren’t the only way to do this. You can also treat customer complaints that come through other feedback channels in a similar manner.

Regardless of how you choose to proceed, interacting with your customers in this productive, proactive way is a great opportunity. Seventy percent of customers who complain will purchase your product again if their complaints are favorably resolved.

8. Reward customer engagement and loyalty

Though nothing beats exceptional customer service, thoughtful gestures go a long way in fostering a community and real customer loyalty. In addition to standard discounts and other offers, think of things that will make your customers feel good about using your product.

A thank-you note or any positive acknowledgment can keep your customers coming back, thus enhancing your customer retention rate.

Loyalty programs can also be a super effective tactic in your customer retention plan. Just look at how Starbucks has built brand loyalty and reduced customer churn with its star program. There’s a cost savings aspect to it, gamification of a customer education program, and a whole customer experience within the app. Consider how you might drive similar business growth while boosting customer retention metrics with a loyalty program of your own.

Building customer relationships

Customers are the foundation of any business. But it’s not enough to just get customers; you must also ensure that you invest in improving customer retention if you want to improve your overall customer lifetime value. Today, customer retention is what separates sustainable growth from short-lived success. You can do this by using the strategies presented in this post to build world-class relationships with your customers.

Want more effective customer retention strategies? Check out our free guide to uncover the 4 major silos hurting your customers, agents, and business. Get actionable tips on how to shatter them and boost your customer retention rates with agentic AI.tionable tips on how to shatter them and boost your customer retention rates with agentic AI.

Frequently Asked Questions (FAQs)

How do I know if my customer retention strategy is working?

Start by tracking your Customer Retention Rate (CRR), Customer Satisfaction Score (CSAT), and Net Promoter Score (NPS). If these metrics are trending upward and repeat purchase or renewal rates are increasing, your strategy is on the right track for business growth. You can also measure reductions in churn and improved lifetime value (CLV).

Which customer retention strategy delivers the fastest results?

While results vary by industry, prioritizing quick response times and omnichannel support often yields immediate impact. Customers notice when you’re easy to reach and proactive in resolving issues – on the channels they prefer using to contact you. Acknowledging their pain points promptly can quickly build trust and prevent customer churn.

How can AI improve customer retention?

AI helps build personalizes experiences at scale. With agentic AI, CX leaders can deliver hyper-relevant communications, anticipate customer needs, and provide faster resolutions through automation across messaging channels (including social media). This frees up human agents to focus on high-value, relationship-building conversations.

Should small businesses focus on retention as much as large enterprises?

Yes. In fact, small businesses often rely more heavily on repeat business and word-of-mouth referrals. Retention strategies across the customer journey, such as personalized communication, loyalty rewards, and attentive customer service, keeps customers engaged.

How to Improve Customer Experience with Contact Center Automation

Posted on Michael Hartsog

Key Takeaways

  • Automation augments, it doesn’t replace: The best strategies use AI to handle routine tasks, freeing up human agents for complex, high-value problem solving.
  • Efficiency drives satisfaction: Reducing average handle time and eliminating backlogs directly correlates to higher customer satisfaction scores (CSAT).
  • Scalability is key: Automation allows contact center operations to handle volume spikes without the need for frantic hiring sprees.
  • Data is the fuel: Successful automation relies on integrating with your existing systems to provide personalized, context-aware service.
  • Agentic AI is the future: Moving beyond simple scripts to AI that can reason and take action is the next frontier of CX.

In 2026, customer experience leaders no longer just ask how to answer calls faster. They are asking how to reinvent the entire interaction model to drive loyalty, increase revenue, and reduce churn.

For years, the answer to increasing volume was simply increasing headcount. But that math no longer works. To truly scale and deliver the personalized, instant experiences customers demand, forward-thinking brands are turning to contact center automation.

This isn’t about replacing your team with robots. It is about equipping your organization with the intelligence to handle the mundane, so your people can handle the meaningful.

What is Contact Center Automation?

At its core, contact center automation is the strategic use of artificial intelligence (AI), intelligent workflows, and system integrations to streamline customer interactions.

It goes far beyond the clunky interactive voice response (IVR) systems of the past. Today, automation involves sophisticated technology that can handle repetitive tasks, assist agents in real time, and resolve customer inquiries automatically across both voice and digital channels. 

Crucially, it does all this without sacrificing the quality of the experience.

Think of it as an “always-on” layer of your support stack. It identifies intent, pulls data from your CRM, and executes tasks — like resetting a password or tracking an order — without a human ever needing to click a button.

Why is Automation Beneficial for a Contact Center?

The pressure on customer experience leaders to reduce costs while simultaneously improving satisfaction has never been higher. Contact center automation is the lever that makes this possible. It transforms the contact center from a cost center into a strategic asset.

Improved Efficiency

The most immediate impact of contact center automation is the removal of friction. High-volume, repetitive tasks — like answering “Where is my order?” or “What are your hours?” — bog down human agents. Automation handles these inquiries instantly and accurately.

By automating these routine interactions, you significantly reduce the backlog of tickets. This creates a smoother operational flow where customers get answers immediately, and agents aren’t drowning in a sea of simple tickets.

Enhanced Agent Productivity

Automation can be a powerful tool for your internal teams, too. AI copilots and agent assist tools work in the background during live conversations. They listen to the interaction, understand the context, and surface relevant answers or knowledge base articles in real time.

This means agents spend less time searching through disparate systems and more time connecting with the customer. It also reduces the cognitive load on your team, making it easier for new agents to get up to speed and perform like seasoned pros.

Scalability

Every customer experience leader dreads the holiday spike or the unexpected service outage that floods the lines. Hiring and training temporary staff is expensive and time-consuming. Contact center automation provides elasticity to your operations.

Because AI doesn’t need to sleep or take breaks, your automated systems can scale up instantly to handle massive increases in volume. This ensures consistent performance during peak seasons, keeping wait times low even when demand is at an all-time high.

Customer Support

Speed is the currency of modern customer support. Customers expect answers now, not in twenty minutes. Automation delivers faster response times across every channel, from web chat to SMS.

Beyond speed, automation enforces accuracy. A well-trained AI doesn’t have “off days” or forget policy details. It provides consistent, accurate answers every single time, reducing the need for customers to call back because they received incorrect information.

Happier Agents

Burnout is a real crisis in the industry. When agents spend eight hours a day answering the same three questions, morale plummets and turnover skyrockets. Contact center automation takes the robotic work out of the human’s hands.

By handling the repetitive, draining tasks, automation allows your human agents to focus on what they do best: solving meaningful, complex problems that require empathy and judgment. This shift leads to higher job satisfaction, lower burnout, and better retention rates.

Personalized Service

One of the biggest myths about automation is that it feels impersonal. In reality, the opposite is true. Because contact center automation integrates with your CRM and customer data platforms, it uses customer history and intent in real time.

Instead of a generic script, the AI can greet a customer by name, reference their last order, and predict why they are reaching out. This delivers a tailored response that drives higher satisfaction, loyalty, and long-term retention.

Contact Center Automation Use Cases

To visualize how this works in practice, let’s look at three specific areas where contact center automation is making a massive difference.

Agent Assist

Imagine an agent helps a customer with a complex billing dispute. Instead of putting the customer on hold to read through policy documents, an AI assistant pops up on the agent’s screen with the exact clause they need, based on the conversation’s real-time transcript.

Agent assist tools also handle the “after-call work.” They can automatically generate summaries of the conversation, tag the disposition, and schedule follow-up tasks. This saves agents valuable minutes after every interaction, which adds up to thousands of hours saved across the organization.

Self Service & Virtual Agents

This is the most visible form of contact center automation. Virtual or AI agents live on your website or messaging channels, ready to resolve common questions 24/7.

Unlike old-school chatbots that get stuck in loops, modern AI agents use natural language processing (NLP) to understand what the customer actually wants. They can handle end-to-end transactions, like processing a return or upgrading a subscription, and escalate seamlessly to a human when the issue becomes too complex.

Post-Interaction Automation

The work doesn’t stop when the conversation ends. Automation streamlines the entire post-interaction process. It can auto-generate conversation summaries and update the CRM, ensuring your data is always clean and current.

It can also trigger automated workflows, such as sending a satisfaction survey immediately after a resolution or scheduling a check-in email for two weeks later. This improves reporting and quality assurance without adding manual administrative work to your team’s plate.

How to Automate Your Contact Center

Implementing contact center automation is a journey, not a switch you flip. To ensure success and drive real ROI, follow these strategic steps.

1. Identify high-volume, repetitive interactions.

Start by analyzing your data. What are the top ten reasons customers contact you? You will likely find that a huge percentage of your volume comes from a handful of simple questions. These are your prime candidates for automation.

2. Map customer journeys and friction points.

Don’t just automate for the sake of it. Look at your customer journey. Where are people getting stuck? Where are the long wait times? Deploy automation specifically to smooth out these friction points.

3. Start with automation that augments agents, not replaces them.

Your first goal should be to help your team, not replace them. Implement tools that make your agents faster and smarter. This builds trust in the technology and ensures that your internal culture adapts positively to the change.

4. Integrate automation with existing systems.

Automation operating in a silo is useless. Ensure your platform integrates deeply with your CRM, ticketing system, and knowledge base. The AI needs access to this data to provide accurate, personalized service.

5. Train AI using real conversation data.

Your automation is only as good as the data it learns from. Use historical transcripts and real customer interactions to train your AI models. This ensures the system understands the specific nuances, slang, and terminology of your business.

6. Measure outcomes tied to customer experience — not just cost savings.

While cost reduction is a benefit, it shouldn’t be the only metric. Measure the success of your contact center automation by looking at CX metrics like customer satisfaction (CSAT), Net Promoter Score (NPS), and customer effort score (CES).

Best Practices for Automating Your Contact Center

As you roll out your strategy, keep these best practices in mind to ensure you are building a system that serves both your business and your customers.

  • Design automation around outcomes, not deflection alone. The goal isn’t just to stop people from calling. It is to solve their problem. If you deflect a call but frustrate the customer, you haven’t won.
  • Maintain a clear path to human agents. There is nothing more infuriating than being trapped in a bot loop. Always provide an easy “escape hatch” for customers to reach a human if they need one.
  • Use AI that understands context, intent, and conversation history. Customers hate repeating themselves. Your automation should know who they are and what they talked about last time.
  • Continuously train and refine using real interactions. AI isn’t “set it and forget it.” Regularly review interactions to see where the automation failed or misunderstood, and use that data to retrain the model.
  • Track CX metrics like CSAT, FCR, average handle time, and customer effort score. Keep a close eye on your average handle time and First Contact Resolution (FCR). These metrics will tell you if your automation is actually making life easier for your customers and agents.
  • Choose platforms built for enterprise scale and security. When dealing with sensitive customer data, you cannot compromise on security. Ensure your vendor meets enterprise standards for data protection and compliance.

Elevate Your Customer Experience with Quiq

The future of contact center automation is about taking action.

Quiq goes beyond basic automation with agentic AI — AI agents that can reason, take action, and collaborate with human teams to resolve customer needs end-to-end. We help enterprise brands move from simple deflection to true resolution, driving revenue and loyalty in the process.

Frequently Asked Questions (FAQs)

What is contact center automation?

Contact center automation uses AI, workflows, and system integrations to handle routine customer interactions, assist agents in real time, and automate post-interaction tasks — reducing manual effort while improving speed, accuracy, and consistency.

How is contact center automation different from chatbots?

Traditional chatbots typically handle scripted FAQs and break down when conversations become complex. Modern contact center automation, especially agentic AI, can understand intent, use context, take action across systems, and collaborate with human agents to resolve issues end-to-end.

Does contact center automation replace human agents?

No. The most effective automation is designed to augment agents, not replace them. Automation handles repetitive tasks and surfaces insights so agents can focus on complex, high-value conversations that require empathy, judgment, and problem-solving.

Which customer interactions should be automated?

Automation works best for high-volume, repetitive interactions such as:

  • Account questions and FAQs
  • Appointment scheduling or order status
  • Intelligent routing and triage
  • Agent assists during live conversations
  • Post-interaction summaries and follow-ups

More complex or emotional interactions should remain human-led, with AI support.

What is agentic AI in a contact center?

Agentic AI refers to AI agents that can reason, make decisions, and take actions — not just respond to prompts. In a contact center, agentic AI can resolve issues, trigger workflows, update systems, and collaborate with humans to achieve outcomes, not just answer questions.

9 Customer Service Challenges and How to Overcome Them

Posted on Michael Hartsog

Key Takeaways

  • Set clear expectations: Define response times and support channels upfront to prevent frustration.
  • Train for empathy: Equip agents to personalize interactions and turn issues into loyalty moments.
  • Use automation wisely: Leverage agentic AI with a solution like Quiq to speed up resolutions without losing the human touch.
  • Manage difficult requests: Stay transparent and solution-oriented when needs can’t be met.
  • Reduce turnover: Invest in onboarding, feedback, and recognition to keep service teams engaged.

When someone comes to you with a problem, they can be angry, stubborn, mercurial, and—let’s be honest—extremely frustrating. Some of this is simply unavoidable, but some stems from the fact that many customer service professionals lack a detailed, high-level understanding of customer service problems and how to overcome them. In this article, we will cover some of the most common customer service problems and how you can remedy them

What are The Top Customer Service Challenges?

After years of running a generative AI platform for contact centers and interacting with leaders in this space, we have discovered that the top customer service problems are:

  1. Understanding customer expectations
  2. Exceeding customer expectations
  3. Dealing with unreasonable customer demands
  4. Improving your internal operations
  5. Not offering a preferred communication channel
  6. Not offering real-time options
  7. Handling angry customers
  8. Dealing with a service outage crisis
  9. Retaining, hiring, and training service professionals
  10. Ignoring customer feedback
  11. Inconsistent customer experiences

In the sections below, we’ll break each of these down and offer strategies for addressing them.

1. Understanding Customer Expectations

Deciding which communication channels to offer customers depends a great deal on the kinds of customers you’re serving. That said, in our experience, text messaging is a universally successful method of communication because it mimics how people communicate in their personal lives. The same goes for web chat and WhatsApp.

Beyond this, setting the right expectations upfront is another good way to address common customer service challenges. For example, if you are not available 24/7, only provide support via email, or don’t have dedicated account managers , you should  make that clear right at the beginning.

2. Exceeding Customer Expectations

Once you understand what your customers want and need, the next step is to go above and beyond to make them happy. Everyone wants to stand out in a fiercely competitive market, and going the extra mile is a great way to do that. One of the major customer service challenges is knowing how to do this proactively, but there are many ways you can succeed without a huge amount of effort.

Consider a few examples, such as:

  • Treating the customer as you would a friend in your personal life, i.e., by apologizing for any negative experiences and empathizing with how they feel;
  • Offering a credit or discount for a future purchase;
  • Sending them a card referencing their experience and thanking them for being a loyal customer.

The key is making sure they feel seen and heard. If you do this consistently, you’ll exceed your customers’ expectations, and the chances of them becoming active promoters of your company will increase dramatically.

3. Dealing with Unreasonable Demands

Of course, sometimes a customer has expectations that simply can’t be met, and this, too, counts as one of the serious customer service challenges. Customer service professionals often find themselves in situations where someone wants a discount that can’t be given, a feature that can’t be built, or a bespoke customization that can’t be done, and they wonder what they should do.

The only thing to do in this situation is to gently let the customer down, using respectful and diplomatic language. Something like, “We’re really sorry we’re not able to fulfill your request, but we’d be happy to help you choose an option that we currently have available” should do the trick.

4. Improving Your Internal Operations

Customer service teams face the constant pressure to improve efficiency, maintain high CSAT scores, drive revenue, and keep costs to service customers low. This matters a lot; slow response times and being kicked from one department to another are two of the more common complaints contact centers get from irate customers, and both are fixable with appropriate changes to your procedures.

You are probably already tracking metrics like first contact resolution (FCR) and (AHT), but this is easier when you have a unified, comprehensive dashboard that gives you quick insight into what’s happening across your organization.

You might also consider leveraging the power of generative AI, which has led to AI assistants that can boost agent performance in a variety of different tasks. You have to tread lightly here because too much bad automation will also drive customers away. But when you use technology like large language models according to best practices, you can get more done and make your customers happier while still reducing the burden on your agents.

5. Not Offering a Preferred Communication Channel

In general, contact centers often deal with customer service challenges stemming from new technologies. One way this can manifest is the need to cultivate new channels in line with changing patterns in the way we all communicate.

You can probably see where this is going – something like 96% of Americans have some kind of cell phone, and if you’ve looked up from your own phone recently, you’ve probably noticed everyone else glued to theirs.

It isn’t just that customers now want to be able to text you instead of calling or emailing; the ubiquity of cell phones has changed their basic expectations. They now take it for granted that your agents will be available round the clock, that they can chat with an agent asynchronously as they go about other tasks, etc.

We can’t tell you whether it’s worth investing in multiple communication channels for your industry. But based on our research, we can tell you that having multiple channels—and text messaging in particular—is something most people want and expect.

6. Not Offering Real-Time Options

When customers reach out asking for help, their customer service problems likely feel unique to them. But since you have so much more context, you’re aware that a very high percentage of inquiries fall into a few common buckets, like “Where is my order?”, “How do I handle a return?”, “My item arrived damaged, how can I exchange it for a new one?”, etc.

These and similar inquiries can easily be resolved instantly using AI, leaving customers and agents happier and more productive.

7. Handling Angry Customers

A common story in the customer service world involves an interaction going south and a customer getting angry.

Gracefully handling angry customers is one of those perennial customer service challenges; the very first merchants had to deal with angry customers, and our robot descendants will be dealing with angry customers long after the sun has burned out.

Whenever you find yourself dealing with a customer who has become irate, there are two main things you have to do:

  1. Empathize with them
  2. Do not lose your cool

It can be hard to remember, but the customer isn’t frustrated with you, they’re frustrated with the company and products. If you always keep your responses calm and rooted in the facts of the situation, you’ll always be moving toward providing a solution.

8. Dealing With a Service Outage Crisis

Sometimes, our technology fails us. The wifi isn’t working on the airplane, a cell phone tower is down following a lightning storm, or that printer from Office Space jams so often it starts to drive people insane.

As a customer service professional, you might find yourself facing the wrath of your customers if your service is down. Unfortunately, in a situation like this, there’s not much you can do except honestly convey to your customers that your team is putting all their effort into getting things back on track. You should go into these conversations expecting frustrated customers, but make sure you avoid the temptation to overpromise.

Talk with your tech team and give customers a realistic timeline; don’t assure them it’ll be back in three hours if you have no way to back that up. Though Elon Musk seems to get away with it, the worst thing the rest of us can do is repeatedly promise unrealistic timelines and miss the mark.

9. Retaining, Hiring, and Training Service Professionals

You may have seen this famous Maya Angelou quote, which succinctly captures what the customer service business is all about:

“I’ve learned that people will forget what you said, people will forget what you did, but people will never forget how you made them feel.”

Learning how to comfort a person or reassure them is high on the list of customer service challenges, and it’s something that is certainly covered in your training for new agents.

But training is also important because it eases the strain on agents and reduces turnover. For customer service professionals, the median time to stick with one company is less than a year, and every time someone leaves, that means finding a replacement, training them, and hoping they don’t head for the exits before your investment has paid off.

For many growing companies, expanding the talent pool beyond a single geographic area can help ease that pressure. Hiring support professionals in different regions not only improves time zone coverage but can also increase retention when workloads are better distributed. Some organizations use an Employer of Record (EOR) to hire internationally without needing to establish a legal entity in each country, which simplifies compliance while allowing teams to scale thoughtfully.

Keeping your agents happy will save you more money than you imagine, so invest in a proper training program. Ensure they know what’s expected of them, how to ask for help when needed, and how to handle challenging customers.

10. Ignoring Customer Feedback

Few customer service problems are as self-inflicted as ignoring customer feedback. When customers take the time to share their experiences, whether through surveys, reviews, social media, or direct conversations, they’re offering you free insight into what’s working and what isn’t.

The problem isn’t usually a lack of feedback; it’s a lack of follow-through. Too often, feedback is collected, stored in a dashboard, and never meaningfully acted on. This creates a dangerous gap between what customers are saying and how the organization evolves.

To avoid this, feedback should be treated as an operational input, not a vanity metric. Look for recurring themes, prioritize issues that impact multiple customers, and close the loop whenever possible by letting customers know their input led to change. When customers feel heard and see evidence of you addressing their feedback, they’re far more likely to stay loyal, even when something goes wrong.

11. Inconsistent Customer Experiences

Inconsistent customer experiences are especially damaging because they erode trust. A customer might have a great interaction one day and a frustrating one the next, even though they’re dealing with the same company. From the customer’s perspective, this unpredictability feels careless or disorganized.The solution is alignment. Centralizing customer data, standardizing processes, and equipping agents with shared tools and guidance all help create a more seamless experience. Technology, when implemented thoughtfully, can play a key role here by ensuring context carries over between interactions and channels. When customers know what to expect every time they reach out, confidence and satisfaction naturally follow.

Final Thoughts on the Top Customer Service Problems

Customer service problems aren’t going away, but the way leading contact centers address them is changing. Today’s most effective teams aren’t just reacting to issues as they arise; they’re using agentic AI to proactively resolve problems, streamline operations, and deliver consistent, high-quality experiences across every channel.

With agentic AI platforms like Quiq, contact centers can automate outcomes by assigning specialized AI agents to handle common inquiries, manage real-time issues, and seamlessly hand off complex cases to human agents with full context. The result is faster resolution, happier customers, and less strain on your service teams.

To go deeper, download the Agentic AI for CX Buyer’s Kit to explore real-world use cases, implementation considerations, and strategies for solving today’s most pressing customer service challenges with agentic AI.

Frequently Asked Questions (FAQs)

What is the most common customer service complaint?

Many teams struggle to keep up with rising customer expectations across multiple channels. Customers now expect fast, personalized responses wherever they reach out – email, SMS, social, or chat. Tools like Quiq’s agentic AI help unify these channels, help CX leaders maintain an effective omnichannel strategy,  and maintain consistent quality at scale.

What is agentic AI?

Agentic AI refers to AI systems that can take autonomous actions on behalf of users, not just respond to prompts. In customer service, this means AI that can interpret intent, make decisions, and complete tasks – like resolving issues, escalating complex cases, or updating orders without manual intervention.

How can automation improve customer experience without feeling impersonal?

Automation should simplify, not replace, the human touch. Using Quiq’s agentic AI for repetitive tasks like order tracking or FAQs frees up agents to focus on more complex, emotional conversations that require empathy and problem-solving.

How does unified messaging impact overall CX performance?

Unified messaging ensures every interaction, no matter the channel, feels seamless and informed. Quiq centralizes customer conversations so agents have full context, resulting in faster responses, fewer escalations, and stronger relationships.

What KPIs should CX leaders track to measure improvement?

Key metrics include CSAT, NPS, first response time, and resolution rate. For teams using Quiq’s agentic AI solution, analytics dashboards provide real-time visibility into these metrics, helping leaders identify bottlenecks and continuously improve customer experience.

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How to Build a Comprehensive AI Business Case for Customer Experience

Posted on Michael Hartsog

Key Takeaways

  • Move Beyond Basic AI ROI: While return on investment (ROI) is essential for tactical decisions, a robust AI business case must focus on strategic transformation. Relying solely on cost savings underestimates the value of agentic AI and fails to account for the significant cost of inaction in a competitive market.
  • The Six Pillars of AI Strategy: A comprehensive proposal should address six specific dimensions: Strategic Alignment, Operational Value, Human Impact (reskilling), Risk & Compliance, Financial Impact (including TCO), and Future-Proofing. This holistic view ensures alignment with C-Suite goals.
  • Prioritize Workforce Reskilling: Successful AI implementation isn’t just about automation; it requires a strong change management plan. Shifting agents from repetitive tasks to high-value interactions improves employee morale and elevates the customer experience.
  • Structure Your Case as a Roadmap: Present the AI strategy as a journey rather than a one-time purchase. This includes defining a clear 3–5 year vision, scenario modeling (incremental vs. all-in), and setting distinct adoption milestones to measure success.
  • Mitigate Risk and Ensure Compliance: A strong business case must address AI risk management. By establishing governance early, enterprises can reduce bias and errors, making AI a trustworthy layer in their customer engagement strategy, rather than a liability.

Since 2010, I’ve been selling in the CX space. Like most sellers, ROI has always been one of the most reliable tools in my kit to help drive deals to close. Efficiency gains, cost savings, and incremental revenue have consistently been the levers that tip decisions in our favor. But lately, as I talk to enterprise CX leaders about agentic AI, I’m hearing something different: “I’m struggling to put the AI business case together.”

Customer Experience executives and practitioners are facing something more than just another incremental technology upgrade. If they are looking at AI strategically, they’re faced with a decision resulting in a fundamental transformation of how they do business. As such, many are struggling to figure out where to even begin—what the starting point looks like, how to structure the AI business case, and how to make sure the story is comprehensive enough to gather alignment across the enterprise and gain buy-in from the C-Suite and Board.

At Quiq, I’ve seen firsthand that the companies making progress aren’t just presenting ROI. They’re reframing the conversation around strategic transformation.

Don’t get me wrong—ROI still matters. But it’s tactical. It captures some of the efficiency, cost savings, and revenue wins, but it doesn’t tell the whole story. And when ROI is the only narrative, the business case undersells the opportunity and the risk of inaction.

Why a Modern AI Business Case Goes Beyond Cutting Costs

Agentic AI represents a shift far larger than simple automation. A robust case for investment must highlight three key pillars:

  • Transformation, not transactions: It’s about reshaping how enterprises utilize their data to deliver valuable and personalized experiences.
  • Human impact: It’s not necessarily about replacing people; it’s about empowering and reskilling them, utilizing their human resources further up into the value chain.
  • Strategic resilience: It’s about competing in a rapidly changing, digital-first, AI-driven marketplace that everyone knows is coming. And coming quickly!

The 6 Dimensions of a Strong AI Business Case

From my perspective—and from what we see with Quiq customers—the strongest AI business cases cover six specific dimensions:

1. Strategic Alignment

Agentic AI must link directly to the enterprise’s biggest priorities. In CX, that means driving revenue in new and existing streams, scaling service without ballooning headcount, differentiating the brand with personalized 24/7 support, and enabling customer-preferred digital-first models. 

For example, Quiq has helped companies like Bob’s Discount Furniture scale revenue and drive effective, efficient service by creating a seamless and differentiated customer experience while keeping costs stable through digital messaging and agentic AI.

2. Operational Value

Yes, this is where ROI lives—faster handle times, improved self-service, higher CSAT, and NPS (loyalty). But it’s more than that. 

Spirit Airlines, another Quiq customer, improved both the customer’s self-service experience and agent productivity, proving AI can drive operational wins without sacrificing quality.

3. Human Impact

This is where change management comes in. With AI, human agents can shift their focus from repetitive tasks to higher-value, emotionally complex interactions. That requires proactive training and reskilling, not just deploying new tools. 

Enterprises that invest here get both better customer experiences and more engaged employees. There is also ample proof within Quiq’s customer base that meaningful digital engagement in the contact center reduces churn and improves agent morale by moving human support staff higher in the value chain.

4. Risk & Compliance

AI creates new risks if it’s unmanaged, but done right, it can reduce errors and bias. At Quiq, we’ve developed a best-in-the-world AI Engineering practice, along with best practices that have helped our enterprise customers maintain compliance in highly regulated industries by making AI a trustworthy layer in their customer engagement strategy. 

The right toolkit with the right resources—whether on staff or outsourced to your supplier—matters.

5. Financial Impact

Beyond ROI, enterprises must weigh the total cost of ownership (TCO) and resilience economics. Your AI business case must ask: 

  • What’s the cost of not adopting AI—lost competitiveness, rising labor costs, or increased churn? 
  • Do we build it ourselves or hire the build-out? 

Quiq’s answer is that you can do both, taking advantage of the economies of scale in an enterprise-scale agentic platform, yet maintaining ownership to whatever extent you wish.

6. Future-Proofing

Agentic AI isn’t a one-off project. It’s a capability that grows with the enterprise. It scales with demand, adapts as customer expectations evolve, and keeps organizations ahead of AI-native competitors.

Structuring Your Business Case as a Roadmap

The AI business case should look like a roadmap for transformation, not just a financial spreadsheet. That means helping CX leaders frame the story around:

  • Vision Statement: What does AI-powered CX look like in 3–5 years?
  • Use Case Prioritization: Which applications bring near-term wins and long-term value?
  • Value Story: How do financial, human, and risk impacts connect?
  • Scenario Modeling: What happens if they do nothing? What if we take an incremental approach? What if we go all in?
  • Change Management: How will the workforce be prepared for the shift?
  • Roadmap: What are the adoption milestones and KPIs?

The Conversation Enterprises Need to Have

For years, ROI has been the centerpiece of every technology proposal. It’s familiar, it’s measurable, and it often unlocks executive attention. But with agentic AI, ROI alone isn’t enough to justify the journey ahead.

This isn’t about marginal efficiency gains—it’s about preparing the enterprise for resilience and transformation in a world where customer expectations are rising faster than ever.

The most successful CX leaders are reframing their AI business case around a more complete story:

  • Financial outcomes matter, but so do workforce enablement and reskilling.
  • Operational improvements are critical, but so is compliance, governance, and risk mitigation.
  • Efficiency metrics are important, but so is future-proofing against AI-native competitors.
  • Growth in a new world is vital, using agentic AI to use what was once focused on service to now drive incremental revenue.
  • Loyalty is driven off of satisfaction, so getting AI right is an imperative.

At Quiq, we’ve seen enterprises that take this holistic approach move faster, gain stronger alignment, and deliver not just AI adoption—but lasting CX transformation. The AI business case must evolve. 

Enterprises that treat AI as a strategic imperative—not just a cost-saving project—will be the ones that define the next era of customer experience.

Frequently Asked Questions (FAQs)

Why is ROI alone insufficient for an AI business case?

While AI ROI captures efficiency gains and cost savings, it is often too tactical to justify a major enterprise transformation. A modern business case must also account for strategic resilience, revenue growth, and the competitive advantage gained by adopting agentic AI early. Focusing only on ROI ignores the long-term risk of falling behind AI-native competitors.

What are the risks associated with deploying AI in Customer Experience (CX)?

AI risk management is a critical component of any business case. Potential risks include data privacy concerns, algorithmic bias, and compliance errors. However, a comprehensive strategy that includes proper governance, “human-in-the-loop” protocols, and a reputable AI engineering partner can mitigate these risks and ensure the system is trustworthy.

How does agentic AI impact the human workforce?

Agentic AI changes the role of human agents, rather than simply replacing them. It handles repetitive, low-value inquiries, allowing human staff to focus on emotionally complex, high-value interactions. A strong business case includes workforce reskilling plans to move employees up the value chain, resulting in higher engagement and lower churn.

What should be included in an AI transformation roadmap?

An effective AI transformation roadmap should include a vision statement for the next 3–5 years, prioritization of high-value use cases, and scenario modeling (comparing the cost of inaction vs. investment). It must also outline change management protocols and specific KPIs to track progress beyond simple financial metrics.

How does AI future-proof a business?

Future-proofing with AI involves building a capability that scales with enterprise demand and adapts to evolving customer expectations. By integrating flexible AI infrastructure now, companies ensure they remain agile and competitive against new market entrants who use digital-first, AI-driven models from day one.

7 Ways to Strengthen Customer Connections Through Every Conversation

Posted on Ejieme Eromosele

Key Takeaways

  • Connection Happens in Every Conversation: Loyalty is built through consistent, empathetic, meaningful communication across all touchpoints.
  • Messaging Is the Heartbeat of CX: Fast, familiar channels create opportunities for personalization, context-rich replies, and human-sounding interactions.
  • Automation Should Strengthen, Not Replace, Humanity: Agentic AI handles repetitive tasks so humans can focus on emotional, complex moments that build trust.
  • Authenticity Can Scale With the Right Systems: Clear voice guidelines, centralized data, and smart automation help brands stay personal as they grow.
  • Teams Are Essential to Connection: Empowered, well-trained agents supported by the right tools create the relationships customers remember and return for.

Messaging, automation, and AI have made it easier than ever to talk to customers. Yet, paradoxically, it feels harder than ever to make those conversations meaningful.

We live in an era where efficiency often masquerades as experience. Brands are automating interactions at record speeds, but if those interactions lack empathy or context, they aren’t building relationships—they’re just processing tickets.

The reality is that customer connection isn’t built through great service alone; it’s built through great conversations. Today’s most successful brands compete on connection just as fiercely as they do on product or price. Why? Because when a customer feels genuinely understood, they stay loyal longer, spend more, and forgive mistakes more easily.

So, how do you bridge the gap between digital efficiency and human authenticity?

In this guide, I’ll explore what customer connection truly means now, why it drives long-term loyalty, and the foundational elements behind authentic relationships. We will also dive into practical strategies for using messaging and agentic AI to amplify—not replace—the human touch.

1. Understand What “Customer Connection” Really Means

At its core, customer connection is the trust, understanding, and emotional resonance a customer feels every time they interact with your brand.

It is easy to mistake “communication” for “connection.” Communication is the exchange of information; connection is the exchange of emotion and value. Connection isn’t about a single transaction or a resolved support ticket. It is the cumulative effect of every conversation adding up to a relationship.

True connection requires a blend of three critical elements:

  1. Empathy: Customers feel heard, valued, and understood, rather than processed.
  2. Consistency: Every message, whether from a bot or a human, sounds like it came from the same brand personality.
  3. Ease: It is simple to get help, find answers, or get things done without friction.

Brands don’t create connection by talking more. They create it by communicating better. When you shift your focus from “handling volume” to “building relationships,” you change the fundamental nature of your customer experience.

2. Recognize That Connection Is the New Competitive Advantage

Products can be copied and prices can be undercut. The one thing your competitors cannot replicate is the relationship you have with your customers. Connection is the new competitive advantage because it directly influences trust, loyalty, and lifetime value.

Data consistently shows connected customers behave differently:

  • They stay loyal longer: Emotional alignment creates a barrier to exit that price drops from competitors can’t easily break.
  • They buy more often: Customers who feel a connection are more open to upsells and cross-sells because they trust your recommendations. In fact, 64% are more likely to buy more frequently.
  • They advocate for you: Emotional connection turns satisfied buyers into vocal brand ambassadors.
  • They are more forgiving: When communication is transparent and a relationship exists, customers are far more likely to forgive a service hiccup or shipping delay.

Every conversation is a chance to either reinforce or erode that connection. This is why messaging consistency is key. If a customer has a fantastic chat with a sales rep, but a disjointed, robotic experience with support, the connection fractures.

3. Build on the Six Foundations of a Connected Brand

Authentic connection doesn’t happen by accident. It is the result of intentional design and culture. To create lasting customer bonds, CX leaders must build upon these six pillars:

  1. Trust: This is the bedrock. Trust is built through transparency (being honest about what you can do), reliability (doing what you say you will), and follow-through (resolving issues completely).
  2. Empathy: This goes beyond “I’m sorry for the inconvenience.” It’s about understanding the customer’s emotional state—are they frustrated, confused, or excited?—and responding with humanity.
  3. Personalization: Using data to make every interaction feel relevant, not robotic. It means knowing who the customer is, so they don’t have to explain themselves.
  4. Consistency: Creating a unified experience across channels. A conversation that starts on SMS should be able to continue on web chat without the customer feeling like they’ve started over.
  5. Responsiveness: Meeting customers where they are and replying when they need you most. Speed matters, but only when paired with accuracy.
  6. Shared purpose: Aligning your brand with values your customers care about. When customers see their values reflected in your brand, the connection deepens.

When these elements work together, customers feel connected—not just served.

4. Use Messaging to Make Every Interaction Personal

Messaging is now the heartbeat of customer communication. It is fast, familiar, and inherently personal. It’s how we talk to our friends and family, so when brands use it correctly, they step into that trusted circle.

Here is how to use messaging to build stronger relationships:

  • Keep the tone conversational: Ditch the corporate jargon. Use language that is approachable, clear, and friendly.
  • Maintain context across channels: One of the biggest connection killers is asking a customer to repeat their order number or issue. Your systems should provide a unified view so the conversation flows seamlessly.
  • Personalize based on history: “Welcome back, Sarah. How is that new espresso machine working out?” is infinitely better than “How can I help you?”
  • Be proactive: Don’t wait for the customer to ask where their order is. Send updates, confirmations, and support tips before they feel the need to reach out.
  • Balance speed with thoughtfulness: Quick replies are great, but they still need to sound human. A generic auto-response that arrives in 0.5 seconds is less valuable than a thoughtful, personalized reply that takes 30 seconds.

Remember, connection comes from making every message feel like a genuine conversation, not a transactional exchange of data.

5. Balance Automation With Human Empathy

Some CX leaders fear automation kills connection. The truth is, when done right, automation acts as a connection amplifier.

Think about it: if your human agents are bogged down answering “What are your hours?” or “What is my tracking number?” 500 times a day, they have zero emotional energy left for the complex, sensitive issues that actually require empathy.

The secret is to seamlessly blend agentic AI and people:

  • Use automation for the repetitive: Let AI handle FAQs, order status checks, and scheduling. It does these tasks faster and more accurately than a human can.
  • Bring humans in for the emotional: When a customer is upset, has a complex problem, or needs advice, get a human involved immediately.
  • Design smart handoffs: The transition from AI to agent should be invisible. The agent should know exactly what the AI and the customer discussed, so they can pick up the baton without missing a beat.

Best practices for using agentic AI:

  • Keep automated messages friendly: Even an AI agent should have manners. Ensure your agentic guardrails (we call them Process Guides) reflect your brand voice—brief, helpful, and polite.
  • Make the “escape hatch” visible: Never trap a customer in a loop. Make it incredibly easy to switch to a human if the AI isn’t solving the problem.
  • Train your AI like a new hire: Continuously feed your AI real interactions to improve its tone, relevance, and accuracy.

At the end of the day, automation should make communication easier, not emptier.

6. Scale Connection Without Losing Authenticity

Scaling a startup culture of “high-touch” service to an enterprise level is one of the hardest challenges in CX. As you grow, the risk of losing that human touch increases. But scalability and authenticity are not mutually exclusive.

Here is how to stay personal as you grow:

  • Create a clear voice and tone guide: Document exactly how your brand sounds. Is it witty? Serious? Nurturing? Give your team (and your AI) a north star for personality.
  • Centralize customer data: You cannot personalize at scale if your data is siloed. Ensure every agent and AI assistant has the full story—past purchases, previous interactions, and preferences.
  • Train teams on empathy AND tech: Don’t just train agents on how to use the software. Train them on active listening, reading emotional cues in text, and de-escalation.
  • Personalize at scale with segmentation: Use smart automation to treat different customer segments differently. A VIP customer might get a different routing priority or tone than a first-time browser.
  • Regularly review message quality: Don’t just track metrics like Average Handle Time. Audit transcripts for warmth, clarity, and accuracy. 💡Pro tip: Agentic conversation analytics can help with this on a new level now.

True scalability happens when technology enhances authenticity, not just efficiency.

7. Empower Teams to Create Connection From the Inside Out

Customer connection starts inside your organization. You cannot expect burnt-out, frustrated agents to build warm, trusting relationships with customers.

To build a team that champions connection:

  • Arm them with context: Give agents access to complete customer histories. When an agent knows the customer has been with you for 10 years, they can frame the conversation with the respect that loyalty deserves.
  • Ditch the rigid scripts: Empower agents to solve problems. Guidelines are good; robotic scripts are bad. Let your team use their judgment to make things right.
  • Celebrate communication moments: Did an agent turn an angry customer into a happy one? Celebrate that win publicly! 🎉
  • Invest in ongoing training: Build emotional intelligence and digital fluency. The ability to convey empathy through a chat window is a skill that must be honed.
  • Align your teams: Marketing, product, and service teams should all share a philosophy on communication. If marketing promises “we’re family” and support says “ticket closed,” the connection breaks.

When your teams feel trusted, supported, and empowered, your customers feel it too. This matters every day, but it can also help teams respond better in times of crisis.

Measuring the Health of Your Customer Connections

You can’t manage what you don’t measure. While “connection” feels like a soft metric, it can be tracked and improved through insight-driven data.

Look beyond the basic operational metrics and track these key indicators:

  • Sentiment trends: Use AI to analyze sentiment across messaging and chat. Are conversations trending positive or negative over time?
  • Retention and repeat purchase rates: These are the ultimate lagging indicators of connection.
  • Response time vs. Resolution time: Are you fast, or are you effective? You need a balance of both.
  • Net Promoter Score (NPS) and Customer Effort Score (CES): NPS measures loyalty; CES measures friction. Both are critical.
  • Conversation quality: Use QA tools to score the tone and consistency of interactions.

Treat these numbers as signals, not just scores on a report card. If sentiment drops, dig into the why. The goal isn’t perfection; it’s continuous progress toward deeper relationships.

How Quiq Helps Brands Build Lasting Customer Connections

Building connection at an enterprise scale requires the right infrastructure. This is where Quiq shines.

Quiq is the platform designed for conversation-first connection, helping brands turn everyday interactions into long-term relationships through:

  • Unified messaging: Keep customers and teams connected across SMS, chat, social, and more channels in one seamless view.
  • Agentic AI + human collaboration: Let automation handle the simple tasks, so your agents have the time and energy to handle the meaningful moments.
  • Contextual awareness: Every conversation comes equipped with history and sentiment insights, so you never fly blind.
  • Personalization at scale: Tailor each response dynamically, without slowing down your operation.
  • Analytics that matter: Measure engagement quality and emotional tone to truly understand the health of your customer base.

Recap and Next Steps

Connection is the true measure of CX success—not volume, not speed, and certainly not how well you stick to a script. To start strengthening your connections today:

  1. Audit your interactions: Look at your last 50 customer chats. Were they warm? Were they clear? Did they feel human?
  2. Evaluate your automation: Identify where AI can enhance the experience, rather than just deflecting it.
  3. Empower your team: Give them the tools, data, and permission they need to create real relationships.

Ultimately, meaningful customer connections are built one authentic conversation at a time. What helps you build deeper relationships with your customers? I’d love to know! Feel free to reach out on LinkedIn and share your thoughts.

Frequently Asked Questions (FAQs)

What’s the biggest difference between communication and connection?

Communication exchanges information, connection builds trust. Connection means customers feel seen, understood, and valued beyond the transaction.

How can brands create genuine connection in digital channels?

By combining messaging, personalization, and context across all channels. When every reply feels thoughtful and familiar, digital conversations start to feel human again.

What’s one simple way to strengthen customer connection today?

Start by listening. Review real customer messages to spot emotional cues, then tailor responses that show empathy and understanding.

How do AI tools like Quiq improve connection without losing the human touch?

AI streamlines the simple stuff, routing, FAQs, notifications, so your agents can focus on meaningful interactions that deepen trust.

What’s the long-term payoff of investing in customer connection?

Lower churn, higher lifetime value, and stronger brand loyalty. Customers stay longer with brands that make them feel genuinely understood.

Transforming CX: Four Lessons from Chamberlain’s Agentic AI Success

Posted on Michael Hartsog

Key Takeaways

  • Legacy Chatbots Have Limitations: Traditional intent-based chatbots often hit performance ceilings, as seen in Chamberlain Group’s stagnant 30% resolution rate. Agentic AI offers a scalable alternative to meet rising customer expectations.
  • Knowledge-Driven AI is the Future: Chamberlain’s AI agent, Amber, leverages a comprehensive knowledge base and cognitive reasoning to deliver dynamic, unscripted support. This adaptability sets agentic AI apart from traditional bots.
  • Integration is Key to Scalable CX: Seamless integration with platforms like Salesforce and Genesys allowed Chamberlain to create a unified, intelligent CX ecosystem, enabling Amber to handle diverse queries efficiently.
  • Results That Redefine Success: Chamberlain’s AI-driven transformation doubled resolution rates to 60+%, reduced repeat calls, and delivered customer experiences so effective that users preferred the AI over human agents.
  • A Blueprint for the Future of CX: Chamberlain’s journey highlights the importance of moving beyond scripted interactions to knowledge-driven, integrated AI solutions that deliver measurable business outcomes.

Last week at the C3 Tech Summit, our partner, Customer Experience Shared Services Manager, Tommy Mayfield of Chamberlain Group, shared their transformational journey into agentic AI. His presentation offered a powerful look at how a global leader in intelligent access moved beyond the limitations of legacy systems to redefine customer support and drive revenue.

For any executive navigating the complexities of CX, Chamberlain’s story is more than just a case study—it’s a blueprint for the future. It highlights a strategic shift from rigid, scripted interactions to dynamic, intelligent conversations that deliver measurable business results.

Here are my takeaways from the event and Chamberlain’s powerful story.

1. Recognize the Limitations of Legacy Chatbots

Chamberlain’s story began with a common challenge. Their existing intent-based chatbot technology had hit a performance ceiling. Despite significant investment, resolution rates were stagnant in the low 30% range, failing to meet their goal of reducing call volume. The customer experience was suffering, leading to increased churn risk and high operational costs for manual updates.

This situation is one many CX leaders can relate to. Traditional bots, which operate on traditional NLP and predefined flows, simply can’t scale to meet rising customer expectations for nuanced, effective support. Chamberlain recognized that incremental improvements wouldn’t be enough; they needed to transform their CX strategy.

2. Embrace a Knowledge-Driven Strategy

The solution was a strategic shift to agentic AI, leading to the creation of “Amber,” their new AI agent powered by Quiq. The core difference? Amber is knowledge-driven, not scripted. Instead of following a rigid path, it leverages a deep understanding of Chamberlain’s vast knowledge base, along with reasoning based on cognitive architecture, to solve problems dynamically.

By ingesting everything from PDF manuals and training decks to video transcripts, Chamberlain created a single source of truth. This allows Amber to reason through issues and mimic the problem-solving process of a top-tier support agent. The AI can ask clarifying questions, adapt to the user’s responses, and provide precise solutions without being confined to a predetermined script. Adaptability like this is the hallmark of true agentic AI.

3. Build Scalable CX Through Integration 

A key takeaway from Tommy’s presentation was the critical role of data and seamless integration. Chamberlain’s success wasn’t just about launching a smarter bot; it was about connecting it to their core systems. By integrating with platforms like Salesforce, Genesys, and their own myQ ecosystem, they created a unified flow of information.

This architecture enables Amber to handle both residential and commercial support queries, routing users to the right experience with ease. For example, the system uses existing tags in Salesforce to deliver the correct information without extra effort. This level of integration ensures the AI assistant isn’t just an isolated tool but a central, intelligent hub within their entire CX operation.

4. Results Should Speak for Themselves

The results Chamberlain shared speak for themselves. The company’s legacy chatbot could only reach a 30% resolution rate. With Quiq, their resolution rate is more than double that at 60+%. Repeat calls from customers who first tried chat have also decreased significantly. 

Perhaps most powerfully, Tommy shared a direct quote from a customer named Adam, who said:

This is the ultimate validation: when the AI provides an experience so effective and satisfying that customers prefer it.

Looking ahead, Chamberlain is focused on expanding its AI capabilities. Their forward strategy includes deeper data integrations for account-level insights, implementing proactive troubleshooting to solve issues before they arise, and exploring new use cases and markets. This forward-thinking vision demonstrates that their journey with agentic AI is just beginning.

Final Thoughts

Chamberlain Group’s story is a compelling example of how agentic AI is transforming customer support. It proves that by moving away from outdated, scripted bots and embracing a knowledge-driven, integrated approach, enterprises can not only improve efficiency but also deliver a truly superior customer experience. Their success reinforces our belief at Quiq that the future of CX lies in creating fast, easy, and personalized interactions powered by intelligent AI.

You can watch the full presentation with Chamberlain at C3 below:

Frequently Asked Questions (FAQs)

What is agentic AI, and how does it differ from traditional chatbots?

Agentic AI is a knowledge-driven system that uses cognitive reasoning to solve problems dynamically, unlike traditional chatbots that rely on predefined scripts and flows. This allows for more nuanced, adaptable, and effective customer interactions.

How did Chamberlain Group improve its resolution rate with agentic AI?

By implementing Amber, an AI agent powered by Quiq, Chamberlain leveraged a unified knowledge base and seamless system integrations to double their resolution rate from 30% to 60+%.

Why is integration important for AI-driven CX?

Integration ensures that AI systems like Amber can access and utilize data from platforms like Salesforce and Genesys, creating a unified flow of information. This enables the AI to provide accurate, context-aware solutions and streamline customer support.

What are the key benefits of agentic AI for customer experience?

Agentic AI improves resolution rates, reduces operational costs, enhances customer satisfaction, and scales to meet complex support needs. It also enables proactive troubleshooting and personalized interactions. Learn more >

Your Guide to Live Chat: Benefits & Best Practices

Posted on Michael Hartsog

Key Takeaways

  • Visibility matters:  If users can’t see or know about your live chat, they won’t use it. Promote the chat option via your website, email campaigns, phone hold messages, and other touchpoints.
  • Remove friction in access: Make initiating chat as painless as possible. Minimize form fields, allow conversational data collection before routing to agents, and reduce extra steps that discourage use.
  • Personalize interactions: Use branding, agent names/pictures, or context from prior interactions to tailor the chat experience. The more it feels human and relevant, the more comfortable customers will be using it.
  • Leverage AI & automation smartly: Use AI to automate answers to routine queries, freeing human agents for more complex tasks. At the same time, ensure smooth escalation from AI to humans and maintain continuity

When customer experience directors float the idea of investing more heavily in live chat for customer service, it’s not uncommon for them to get pushback. One of the biggest motivations for such reticence is uncertainty over whether anyone will actually want to use such support channels—and whether investing in them will ultimately prove worth it.

An additional headwind comes from the fact that many CX directors are laboring under the misapprehension that they need an elaborate plan to push customers into a new channel. However, one thing we consistently hear from our enterprise customers is that it’s surprising how customers naturally start using a new channel when they realize it exists. To borrow a famous phrase from Field of Dreams, “If you build it, they will come.” Or, to paraphrase a bit, “If you build it (and make it easy for them to engage with you), they will come.” You don’t have to create a process that diverts them to the new channel.

What is Live Chat?

Live chat is a real-time messaging tool on a website or app that lets customers quickly communicate with a business. It typically appears as a small chat window and allows users to ask questions, get support, or receive guidance instantly while browsing. Live chat improves customer experience by reducing wait times and offering immediate, personalized help.

Why is Live Chat Important for Contact Centers?

Live chat has a clear impact on customer engagement. When businesses offer real-time messaging, customers are more likely to return, explore confidently, and move toward a purchase because they can get quick answers without waiting on hold.

It’s also a channel customers genuinely prefer. Live chat feels easier and more convenient than phone or email, lets users multitask, and gives them a written record of the conversation—all of which contribute to consistently strong satisfaction. Support teams benefit, too. Handling conversations through chat reduces the emotional strain of frequent phone calls and allows agents to manage more interactions efficiently, which can improve morale and retention.

Overall, live chat stands out as an effective communication channel that supports better customer satisfaction and stronger outcomes for support teams—making it a smart choice for contact centers and customer service today and in the future.

Benefits of Live Chat Support Services

Real-Time Support

When customers need help, they don’t want to wait. Live chat support services provide instant solutions, cutting down resolution times and getting customers the answers they need—fast. And when customers get quick answers, they stick around. Faster replies lead to higher satisfaction, increased trust, and more repeat business. The quicker the response, the better the experience,— and that’s a win for both customers and businesses.

Increased Customer Satisfaction

Today’s customers expect immediate support, and live chat support services deliver exactly that. When customers know they can rely on your support team for quick, clear, and helpful answers, they feel confident in your brand. That confidence translates into loyalty, repeat purchases, and positive word-of-mouth—turning a one-time buyer into a long-term customer.

Efficiency

Live chat isn’t just better for customers,— it’s a game-changer for support teams too. Unlike phone calls, where agents can only help one person at a time, live chat lets them handle multiple conversations at once. That means fewer bottlenecks, faster resolutions, and better overall efficiency. Plus, fewer phone calls = lower costs. With live chat, businesses can reduce phone expenses, optimize staffing, and minimize hold times—all without sacrificing customer experience.

Omnichannel Integration

Customers don’t just stick to one channel—they bounce between email, social media, SMS, and your website. Live chat support services integrate seamlessly into this mix, creating a unified experience. Whether a customer starts a conversation on social media and follows up via chat or asks a question through SMS, they get the same consistent service. Even better, integrating chat across channels keeps all customer interactions in one place, so your team has a complete history of past conversations. That means no more repeating issues, fewer dropped interactions, and a smoother customer journey from start to finish.

Live Chat Support Best Practices

Prompt Response Times

Speed matters when it comes to live chat support services. The faster you respond, the more valued customers feel—and that leads to higher satisfaction and loyalty. Nobody likes waiting, especially when they have a quick question standing between them and a purchase. Whether a customer is asking about shipping costs, return policies, or product details, meeting them in the moment with real-time support keeps them engaged.

Professional Communication

Live chat is fast, but that doesn’t mean it should feel rushed. A professional and friendly tone makes all the difference in building trust and keeping conversations productive. Customers want clear, concise, and helpful responses—not robotic scripts or vague answers. Miscommunication can create frustration, so keep things simple, polite, and to the point. Use proper grammar, avoid jargon, and personalize interactions with the customer’s name. A great chat experience feels like talking to a knowledgeable friend—someone who understands the problem and knows exactly how to help. The smoother the conversation, the more confident customers feel about your brand.

24/7 Availability

Customers shop on their own time, whether that’s during a lunch break, late at night, or halfway across the world. Offering live chat support services 24/7 means you’re always there when they need help. This is especially valuable for global businesses, ensuring customers in different time zones get real-time answers instead of waiting for office hours. Plus, round-the-clock availability isn’t just about support—it’s a sales booster too. A shopper with a question at 2 AM might just leave if they can’t get an answer. But if live chat is available? That hesitation disappears, and the sale happens.

6 Tips for Encouraging Customers to Use Live Chat

1. Make Sure People Know You have Live Chat Services

One of the simplest ways to increase live chat adoption is to make it highly visible. Promote it across your usual channels—your support page, social media, order confirmation emails, and other customer touchpoints so people know it’s available.

You can also shift customers from phone to messaging by mentioning live chat in your IVR or hold messages. Since customers dislike waiting on hold, offering a quick alternative like web chat, SMS, WhatsApp, or Apple Messages can encourage them to switch. A prompt as straightforward as “Press 2 to chat with an agent online or by text” can significantly reduce call volume.

Highlighting live chat benefits everyone. Agents can manage multiple conversations at once, leading to quicker resolutions and higher overall satisfaction. And the more places you link to live chat on post-purchase emails, product pages, hero pages, and other high-intent parts of your website, the easier it is for customers to get help in the moment, which can also boost conversions.

2. Minimize the Hassle of Using Live Chat

One of the better ways of boosting engagement with any feature, including live chat, is to make it as pain-free as possible.

Take contact forms, for example, which can speed up time to resolution by organizing all the basic information a service agent needs. This is great when a customer has a complex issue, but if they only have a quick question, filling out even a simple contact form may be onerous enough to prevent them from asking it. Every additional second of searching or fiddling means another lost opportunity.

 There’s a bit of a balancing act here, but, in general, the fewer fields a contact form has, the more likely someone is to fill it out.

The emergence of large language models (LLMs) has made it possible to use an AI agent to collect information about customers’ specific orders or requests. When such an agent detects that a request is complex and needs human attention, it can ask for the necessary information to pass along to an agent. This turns the traditional contact form into a conversation, placing it further along in the customer service journey, so only those customers who need to fill it out will have to use it.

3. Personalize Your Chat

Another way to make live chat for customer service more attractive is to personalize your interactions. Personalization can be anything from including an agent’s name and picture in the chat interface displayed on your webpage to leveraging an LLM to craft a whole bespoke context for each conversation.

For our purposes, the two big categories of personalization are brand-specific personalization and customer-specific personalization. Let’s discuss each.

Brand-specific personalization

Marketing and contact teams should collaborate to craft notifications, greetings, etc., to fit their brand’s personality. Chat icons often feature an introductory message such as “How can I help you?” to let browsers know their questions are welcome. This is a place for you to set the tone for the rest of the conversation, and such friendly wording can encourage people to take the next step and type out a message.

More broadly, these departments should also develop a general tone of voice for their service agents. While there may be some scripted language in customer service interactions, most customers expect human support specialists to act like humans. And, since every request or concern is a little different, agents often need to change what they say or how they say it.

Customer-specific personalization

Customer-specific personalization, which might involve something as simple as using their name, or extend to drawing from their purchase history to include the specifics of the order they’re asking about.

Among the many things that today’s LLMs excel at is personalization. Machine learning has long been used to personalize recommendations, but when LLMs are turbo-charged with a technique like retrieval-augmented generation (which allows them to use validated data sources to inform their replies to questions), the results can be astonishing.

Machine-based personalization and retrieval-augmented generation are both big subjects, and you can read through the links for more context. But the high-level takeaway is that, together, they facilitate the creation of a seamless and highly personalized experience across your communication channels using the latest advances in AI. Customers will feel more comfortable using your live chat feature, and will grow to feel a connection with your brand over time.

4. Include Privacy and Data Usage Messages

By taking privacy seriously, you can distinguish yourself and thereby build trust. Customers visiting your website want an assurance that you will take every precaution with their private information, and this can be provided through easy-to-understand data privacy policies and customizable cookie preferences.

Live messaging tools can cause concerns because they are often powered by third-party software. Customer service messaging can also require a lot of personal information, making some users hesitant to use these tools.

You can quell these concerns by elucidating how you handle private customer data. When a message like this appears at the start of a new chat, it is always accessible via the header, or persists in your chat menu, customers can see how their data is safeguarded and feel secure while entering personal details.

5. Use Rich Messages

Smartphones have become a central hub for browsing the internet, shopping, socializing, and managing daily activities. As text messaging gradually supplemented most of our other ways of communicating, it became obvious that an upgrade was needed.

This led to the development of rich messaging applications and protocols such as Apple Messages for Business and WhatsApp, which use Rich Communication Services (RCS). RCS features enhancements like buttons, quick replies, and carousel cards—all designed to make interactions easier and faster for the customer.

Using rich messaging in live chat with customers will likely help boost engagement. Customers are accustomed to seeing emojis now, and you can include them as a way of humanizing and personalizing your interactions. There might be contexts in which they need to see or even send graphics or images, which is very difficult with the old Short Messaging Service (SMS).

6. Separating Chat and Agent Availability

Once upon a time, ‘chat availability’ simply meant the same thing as ‘agent availability,’ but today’s language models are rapidly becoming capable enough to resolve a wide variety of issues on their own. In fact, one of the major selling points of AI agents is that they provide round-the-clock service because they don’t need to eat, sleep, or take bathroom breaks.

This doesn’t mean that they can be left totally alone, of course. Humans still need to monitor their interactions to make sure they’re not being rude or hallucinating false information. But this is also something that becomes much easier when you pair with an industry-leading conversational AI for CX platform that has robust safeguards, monitoring tools, and the ability to switch between different underlying models (in case one starts to act up).

Having said that, there are still a wide variety of tasks for which a living agent is still the best choice. For this reason, many companies have specific time windows when live chat for customer service is available. When it’s not, some choose to let customers know when live chat is an option by communicating the next availability window.

Employing these two strategies means that your ability to service customers is decoupled from operational constraints of agent availability, and you are always ready to seize the opportunity to serve customers when they are eager to engage with your brand

Creating Greater CX Outcomes with Live Web Chat is Just the Start.

Live web chat remains one of the strongest ways to resolve issues quickly while building trust and elevating the customer experience. The key to driving higher engagement is making chat visible, easy to use, and personalized while using AI to handle routine questions and fill in gaps when agents aren’t available.

With Quiq, these strategies become even more effective. Quiq helps teams blend AI, automation, and human agents across chat, messaging, and web channels so customers always get fast, reliable support.

If you’re interested in taking additional steps and learning how to use live chat more effectively within your customer-service strategy, be sure to explore our Agentic AI for CX Buyers Kit. It breaks down practical, actionable ways to elevate your support experience—covering automation, AI-driven workflows, and the evolving role of messaging. Inside, you’ll find clear guidance on how to use live chat alongside modern AI capabilities to boost satisfaction, streamline operations, and drive more meaningful customer outcomes.

Frequently Asked Questions (FAQs)

Why should businesses offer live chat support?

Live chat provides instant, convenient communication – reducing wait times and improving customer satisfaction while lowering operational costs.

How can I encourage customers to use live chat?

Make the chat widget visible, promote it across touchpoints (like emails or social), and ensure it’s easy to access without long forms or redirects.

How does live chat benefit support teams?

AI agents can handle multiple chats simultaneously, improving efficiency, reducing call volume, and boosting job satisfaction.

Can live chat integrate with other channels?

Absolutely. Live chat can be part of an omnichannel strategy that connects web, SMS, and social interactions for a seamless customer experience.

What metrics should I track to measure chat success?

Monitor chat volume, first-response time, resolution time, CSAT scores, and conversion rates to understand performance and customer satisfaction.

Call Center Cost Reduction: 12 Proven Strategies

Posted on Michael Hartsog

Key Takeaways

  • AI is the key to smarter cost reduction. Technology like agentic AI and tools like AI agents and assistants automate routine tasks, boost efficiency, and actually improve service quality.
  • You can cut costs and keep customers happy. Introducing robust analytics, asynchronous channels, and personalized AI reduces costs while improving CX.
  • A phased roadmap drives lasting results. Start with assessment and planning, implement quick wins, then optimize and scale with ongoing performance tracking.
  • Human agent engagement is essential. Clear communication, strong training, and incentives help teams embrace new tools and work more efficiently.
  • Agentic AI delivers the biggest impact. Agentic AI automates complex workflows, reduces operational costs, and empowers human agents to do higher-value work.

Call centers represent a significant portion of overall customer service spending for many organizations. While they were once viewed as cost centers, they are now evolving into strategic drivers of customer satisfaction, brand loyalty, and revenue. Even with this shift, organizations still face mounting pressure to manage and reduce operational costs without compromising the quality of the customer experience.

The challenge is finding sustainable, employee- and customer-friendly ways to improve efficiency and lower operational costs. It’s a delicate balance, but with the right strategies, it’s entirely achievable.

This guide will walk you through 12 proven strategies to reduce call center operational costs. You’ll learn how to implement these changes while maintaining high service quality and keeping your agents satisfied and engaged.

Top 12 Call Center Cost Reduction Strategies

Reducing costs doesn’t have to mean cutting corners. By focusing on smart investments in technology and process optimization, you can achieve significant savings while simultaneously improving your customer and agent experience. Here are 12 strategies to get you started.

Infographic showing 12 call center cost reduction strategies for enterprise brands

1. Implement Human Agent-Facing AI Assistants

To achieve meaningful call center cost reduction, organizations must move toward AI assistants that can plan, reason, and act autonomously within your CX ecosystem. Agentic AI represents a leap forward, enabling AI assistants to assist human agents in real time by suggesting responses and taking action on common requests, like submitting orders and processing follow-ups.

  • Cost Benefit: Quiq’s AI Assistants for human agents dramatically improve efficiency by suggesting next-best actions, on-brand responses, and even taking action on behalf of agents.
  • Case study highlight: Panasonic EU worked with Quiq to implement agent-facing AI that provides real-time response suggestions. Learn more >

2. Implement agentic AI agents for Customers

Routine inquiries like order status updates, password resets, or basic product questions can consume a significant amount of your human agents’ time. Implementing AI agents to handle these common, Tier 1, low-complexity tasks is a powerful cost-reduction strategy.

  • Cost benefit: This approach reduces handle time for your human agents and can lower headcount requirements, especially during peak volume periods. Quiq’s agentic AI can seamlessly integrate with your existing systems and maintain a consistent brand voice while driving down per-interaction costs. This frees up your team to focus on interactions that require a human touch, driving down operational costs.
  • Case study highlight: Brinks Home™ lowered cost per contact by 67% using this strategy. Learn more >

3. Implement Voice AI for Workforce Optimization

Voice AI can manage a wide range of routine customer interactions, such as appointment scheduling, order updates, or account inquiries. This allows your live agents to dedicate their time and expertise to more complex or higher-value calls that genuinely require human empathy and problem-solving skills.

  • Cost benefit: Leveraging Voice AI reduces average handle time, minimizes the need for overstaffing during peak hours, and can even lower training costs by providing real-time guidance to agents. Quiq’s Voice AI analyzes tone, intent, and emotion in real time, enabling smarter routing, live coaching, and more efficient staffing—helping call centers cut costs without sacrificing quality.
  • Case study highlight: Spirit Airlines implemented an omnichannel strategy in its contact center, including Voice AI, leading to an automated resolution rate of over 40%, with conversation times that are 16% faster. Learn more >

4. Utilize Cloud-Based Call Center Software

On-premise hardware is expensive to purchase, maintain, and upgrade. Cloud-based call center software eliminates this capital expenditure and provides the flexibility to scale your operations up or down as needed, without being tied to physical infrastructure. Not to mention, using cloud technology means that all your agents need is a laptop and Internet access, and they can work from anywhere. No more massive call centers—and the massive cost that goes with them.

  • Cost benefit: Migrating to the cloud significantly reduces IT maintenance costs and often improves uptime and reliability. A cloud-native architecture like Quiq’s Digital Engagement Center allows for rapid deployment, effortless updates, and seamless integration with CRMs and other business systems—no hardware required.

5. Integrate Omnichannel Communication Platforms

Modern customers expect to move fluidly between voice, web chat, SMS, and a number of asynchronous messaging channels without having to repeat themselves. Supporting these journeys with a collection of disconnected tools is inefficient and creates a frustrating experience for both customers and agents.

  • Cost benefit: Consolidating your channels onto a single, unified platform reduces tool redundancy and lowers software licensing costs. With an AI-ready omnichannel platform, agents can manage all interactions from one unified view, driving efficiency and leading to better customer outcomes.
  • Case study highlight: Brinks Home shifted digital transactions from 12% to 60% in under three years. Learn more >

6. Optimize Agent Scheduling and Workforce Planning

Idle time is a major-yet-hidden cost driver in any call center. Inefficient scheduling can lead to agents waiting for calls during lulls and being overwhelmed during peaks. Using data-driven workforce management (WFM) tools helps you forecast demand and align staffing levels accordingly.

  • Cost benefit: Optimized scheduling minimizes agent downtime and reduces the need for costly overtime, all while ensuring you have optimal coverage to meet service levels. You can integrate scheduling tools with your contact center platform to track real-time agent utilization and other productivity metrics.

7. Focus On First Call Resolution

First Call Resolution (FCR) is a critical metric. When customers have to call back multiple times to resolve a single issue, it drives up call volume and tanks customer satisfaction. Focusing on resolving issues in a single interaction is a powerful lever for call center cost reduction.

  • Cost benefit: Improving FCR means fewer repeat contacts, escalations, and follow-ups, which translates directly to measurable cost savings. AI-provided responses and recommendations from an AI assistant built by Quiq can surface the right information or suggest the next best action during a conversation, empowering agents to solve problems faster and boosting FCR rates.
  • Case study highlight: A large, Southern-themed American chain of restaurant and gift stores worked with Quiq to deploy AI that reduced customer follow-up times by over 90% and resolved most issues in the first interaction. 

8. Streamline Call Routing and IVR Systems

“Please listen carefully as our menu options have recently changed.” This familiar phrase often signals a frustrating customer journey ahead. Outdated Interactive Voice Response (IVR) trees and inefficient routing strategies increase call times and annoy customers, forcing many to “zero out” to reach a human.

  • Cost benefit: Intelligent routing ensures customers are connected to the right agent or self-service option faster, which reduces average handle time (AHT). Quiq’s AI-enhanced routing can identify customer intent early in the interaction and direct the inquiry to the optimal channel—be it a human or an AI agent.
  • Case study highlight: A financial services company uses Quiq’s intelligent tagging and routing capabilities to match inquiries to specialized agents, reducing resolution times and ensuring a more personalized experience. Improving workflows in this way, along with providing a unified console experience, has led to 95% agent QA scores, as they’ve become more confident and efficient in delivering quality support.

9. Develop Self-Service Customer Portals

Empowering customers to find answers and solve issues on their own is one of the most effective ways to reduce call volume. Robust self-service options, such as comprehensive FAQ hubs, knowledge bases, and AI-powered chat, can deflect a large number of repetitive inquiries.

  • Cost Benefit: Every inquiry resolved through self-service is one less call your agents have to handle, directly reducing your cost per contact. Pairing self-service portals with agentic AI like Quiq’s allows for intelligent escalation only when human intervention truly adds value.
  • Case study highlight: Chamberlain Group worked with Quiq to create an agentic AI Agent named Amber who can do everything from answer common questions to help customers troubleshoot complex account and product-specific issues. And customers prefer the experience!  

10. Reduce Agent Turnover Through Better Training and Opening Digital Messaging

High agent turnover is one of the biggest hidden costs in the call center industry, with some estimates putting the annual rate around 40%. The expenses associated with recruiting, hiring, and training new agents add up quickly. Investing in comprehensive onboarding and ongoing training improves agent performance, satisfaction, and retention. 

Additionally, many modern call centers rely on remote, part-time, or contract agents to maintain flexibility and control labor costs. Streamlining payroll documentation for distributed teams helps reduce administrative overhead and ensures agents receive accurate income records. Tools like PayStub Master can simplify pay stub generation, making payroll processes more efficient for growing support teams.

Not only that, but opening up digital messaging channels means that when agents chat with customers, they can do so at a clip of 3-5 conversations at a time vs. just one. And agents prefer it to answering the phone.

  • Cost benefit: Lowering turnover reduces recruitment and training expenses. Better-trained agents are also more efficient and provide higher-quality service. You can equip agents with AI-powered coaching and conversation insights to accelerate their skill development and boost their confidence. Plus, moving interactions to digital channels is a cost reduction strategy. Not to mention, agents are less likely to burn out managing chat vs. angry customers calling in.
  • Case study highlight: A global hospitality brand introduced digital messaging to their agent team via Quiq, leading to zero agent turnover and 40% improvement in response times. Learn more > 

11. Implement Performance-Based Incentives

Motivating agents to align with key business goals can drive significant efficiency gains. Implementing incentive programs tied to measurable Key Performance Indicators (KPIs) like First Call Resolution, Customer Satisfaction (CSAT), and Average Handle Time encourages agents to work more effectively.

  • Cost benefit: Performance-based rewards can increase agent productivity without increasing headcount. Using analytics dashboards to transparently track performance metrics and celebrate top performers fosters a culture of achievement and continuous improvement.
  • Pro tip! Save time and money by using unbiased AI Analysts to review every conversation to determine if KPIs are being met. 

12. Consider Specialized vs. Cross-Trained Agents

Some organizations perform best with fewer, specially-skilled agents, while others do better with more agents who are cross-trained. It depends on your business and product type. For many companies, specialization can lead to bottlenecks. Cross-training agents to handle multiple types of interactions (e.g., sales, support, billing) across different channels creates a more agile and flexible workforce. Either way, two things remain true:

  1. If your support agents are idle while the sales queue is backed up, you’re not using your resources efficiently. 
  2. Gathering data at the outset of a conversation is always most efficient.

Cost benefit: A multi-skilled team reduces idle time and improves coverage flexibility, allowing you to deploy agents where demand is highest. Quiq’s omnichannel system supports seamless transitions between tasks, making it easy for agents to switch roles as needed. If you go with fewer, more specialized agents, ensure you have a comprehensive AI automation and routing system in place, so your agents only need to take on high-complexity tasks.

How to Measure and Track Cost Reduction Success

To ensure your call center cost reduction initiatives are effective, you must track the right KPIs. These metrics will help you quantify your savings, measure the impact on customer experience, and identify areas for further optimization.

Cost Per Call 

  • Definition: This metric calculates the total expense of operating your call center divided by the total number of calls handled. It gives you a clear picture of the expense associated with each customer interaction.
  • Benefit: Tracking cost per call helps you directly measure the financial impact of your efficiency initiatives. A lower number indicates your strategies are working.
  • Calculation: Total Call Center Operating Costs / Total Number of Calls Handled

Customer Satisfaction (CSAT)

  • Definition: CSAT measures how happy customers are with a specific interaction or experience. It’s typically measured with a survey asking customers to rate their satisfaction on a scale.
  • Benefit: This metric ensures your cost-cutting efforts aren’t negatively impacting the customer experience. A stable or increasing CSAT score alongside reduced costs is the ideal outcome.
  • Calculation: (Number of “Satisfied” + “Very Satisfied” Responses / Total Number of Responses) × 100

Average Handle Time (AHT)

  • Definition: AHT measures the average duration of a single customer interaction, from the moment an agent starts until all after-call work is complete.
  • Benefit: Reducing handle time is a direct way to improve agent efficiency and lower cost per call. However, it should be monitored alongside CSAT to ensure quality isn’t being sacrificed for speed.
  • Calculation: (Total Talk Time + Total Hold Time + Total After-Call Work) / Total Number of Interactions

Agent Utilization Rate

  • Definition: This metric measures the percentage of time agents are actively engaged in call-related activities versus their total paid time.
  • Benefit: A higher utilization rate indicates that your workforce is being used efficiently, with minimal idle time. It’s a key indicator for assessing the effectiveness of your scheduling and WFM strategies.
  • Calculation: (Total Time Spent on Call-Related Activities / Total Paid Agent Hours) x 100

Customer Satisfaction vs. Cost Balance

  • Definition: This isn’t a single formula but rather a strategic analysis of the relationship between your cost metrics (like cost per call) and your satisfaction metrics (like CSAT or NPS).
  • Benefit: It provides a holistic view, helping you ensure that you’re achieving a sustainable balance. The goal is to find the sweet spot where costs are optimized and customer satisfaction remains high. This balance is crucial for long-term success.

Learn how agentic AI is changing CX metrics. Get the guide >

Implementation Roadmap for Call Center Cost Reduction

A successful cost reduction program requires a structured approach. A phased roadmap helps ensure you build a strong foundation, secure early wins, and create lasting change.

Phase 1: Assessment and Planning (Month 1-2)

Before diving into technology upgrades or process changes, organizations should start by building a strong foundation rooted in data and strategic clarity.

Current State Analysis and Cost Audit

Begin by auditing your current operational expenses, analyzing call volumes, and measuring agent productivity. Dig deep to identify redundant tools, inefficient manual workflows, and the highest-cost areas of your operation. This data will be the baseline against which you measure success.

Goal Setting and Budget Allocation

With a clear understanding of your current state, set specific, measurable, and achievable goals. These might include targets like “reduce cost per contact by 15% in 6 months” or “improve FCR by 10%.” Prioritize initiatives with the strongest potential ROI, paying special attention to how advanced technologies like Agentic AI can accelerate your progress.

Phase 2: Quick Wins Implementation (Month 3-4)

Once you have a plan, focus on changes that can deliver a high impact with relatively low cost and effort.

Low-Cost, High-Impact Changes

Look for immediate opportunities. This could involve consolidating communication tools into a unified omnichannel platform to reduce licensing fees or automating simple, repetitive tasks like ticket routing and post-interaction follow-ups.

Process Optimization Initiatives

Standardize and improve your knowledge bases to make it easier for agents to find information. Streamline agent workflows to remove unnecessary steps. Optimize agent schedules to better match staffing levels with forecasted call volumes, reducing both idle time and overtime. This is also the perfect stage to introduce pilot programs for agentic AI to demonstrate its value.

Phase 3: Optimization and Scaling (Month 5-6)

With a foundation in place and quick wins achieved, the final phase is about refining your approach, measuring results, and scaling what works.

Performance Monitoring and Adjustments

Continuously track your key performance indicators, including AHT, CSAT, FCR, and cost per contact. Use this data to see what’s working and what isn’t. Be prepared to fine-tune your strategies based on these insights. As you prove the value of your initiatives, you can scale AI and automation across more processes and departments.

Common Challenges and Solutions

Implementing change is never without its obstacles. Here’s how to navigate two of the most common challenges in a call center transformation.

1. Overcoming Resistance to Change

Agents and managers may be resistant to new technologies and processes, especially if they fear job replacement or disruption to their established routines.

Change Management Best Practices

Effective change management starts with a clear vision. Communicate the “why” behind the changes and the expected benefits for the company, employees, and customers. Involve frontline agents early in pilot programs to gather their feedback and foster a sense of ownership.

Agent Buy-In and Training Strategies

Offer hands-on training, workshops, and quick-reference guides to ease the learning curve for new tools. Crucially, frame new technologies like AI as tools that enhance—not replace—human expertise. Highlight how they can eliminate mundane tasks and free up agents to focus on more engaging, higher-value work.

Get more tips for managing the human element of change. Download guide >

2. Maintaining Service Quality During Cost Reduction

An aggressive focus on cost-cutting can inadvertently lead to a decline in service quality, which can damage customer loyalty and your brand’s reputation.

Customer Satisfaction Monitoring

Keep a close eye on your customer-facing metrics throughout the process. Track CSAT, Net Promoter Score (NPS), and resolution rates to catch any negative trends early. Use customer feedback surveys and sentiment analysis to understand the “why” behind the numbers and fine-tune your workflows and automation triggers accordingly.

Agentic AI: The Ultimate Tool for Cost Savings

While all 12 strategies can contribute to a more efficient call center, the single most impactful change you can make is the implementation of agentic AI. This technology doesn’t just automate simple tasks; it handles complex, multi-step workflows, intelligently escalates when needed, and empowers human agents to perform at their best.

By taking on the repetitive and routine work, agentic AI frees up your team to focus on building customer relationships and solving the most challenging issues. Quiq’s agentic AI is the #1 recommendation for any organization serious about call center cost reduction because it delivers substantial savings while simultaneously enhancing both the customer and agent experience.

Frequently Asked Questions (FAQs)

What is the average cost savings potential from these strategies?

The savings potential varies widely depending on your call center’s size, current efficiency, and the specific strategies you implement. However, organizations often see cost reductions of 15-30% or more by combining technology adoption, process optimization, and workforce management improvements.

How long does it take to see results from call center cost reduction efforts?

You can see results from “quick win” initiatives like process optimization or scheduling adjustments within a few months. More significant technology implementations, like deploying agentic AI, may take 3-6 months to show their full financial impact, though improvements in efficiency metrics are often visible much sooner.

What are the risks of aggressive cost-cutting in a call center?

The biggest risk is a decline in service quality, which can lead to customer frustration, churn, and damage to your brand’s reputation. It can also lead to agent burnout and high turnover if employees feel overworked and under-supported. This is why it’s crucial to balance cost reduction with a focus on CX and agent satisfaction metrics.

How do you maintain quality while reducing costs?

The key is to focus on efficiency, not just cuts. Invest in technology like AI that handles repetitive tasks flawlessly, freeing up humans for high-value interactions. Continuously monitor CSAT and FCR to ensure quality remains high. Empower agents with better tools and training so they can work smarter, not just harder.

What’s the highest-value strategy for call center cost reduction?

Implementing agentic AI is typically the highest-value strategy. It offers the greatest potential for automating complex workflows, significantly reducing operational costs, and freeing up human agents to focus on strategic, revenue-generating, and complex customer issues. Its impact is systemic, improving everything from handle time to agent satisfaction.

How often should cost reduction strategies be reviewed?

Cost reduction is not a one-time project; it’s an ongoing process of optimization. You should review your strategies and KPIs on a quarterly basis to adapt to changing business needs, customer expectations, and new technological capabilities.

How to Anticipate Customer Needs: Benefits & Tips

Posted on Lauren Winder

Key Takeaways

  • Anticipating what customers need before they ask strengthens trust and encourages long-term loyalty. Customers are more likely to stay with brands that simplify their experience.
  • Modern customers expect fast, frictionless interactions. Reducing steps and minimizing wait times helps deliver the convenience they’re looking for.
  • Sending updates, reminders, or support resources can prevent issues from becoming customer frustrations.
  • When service reps have the authority to resolve issues (e.g., offering discounts, replacing items), they can provide faster and more satisfying resolutions.
  • Tools like asynchronous messaging and pre-built responses help agents manage multiple conversations efficiently and reduce repetitive tasks.

When was the last time you heard a story about exceptional customer service? Or an innovative way a company figured out how to anticipate customer needs?

You know the kind: An observant hotel employee rescues a beloved stuffed animal. The considerate customer service agent sends a gift card to apologize for a shipping error. A software company sees you’re having trouble with their platform and sends you a private video walkthrough. These are all great examples, but what really makes a difference day after day is simply anticipating customer needs before they become problems.

Some companies seem to have an uncanny ability to predict and get ahead of their customers’ problems. But it doesn’t just happen. Exceptional customer service is designed with dedication built into company cultures.

We get it. Sometimes, merely meeting customer needs is a struggle. Anticipating them? Now that seems daunting. After all, you can’t read minds. The good news is that your customers don’t expect you to. But they do want you to anticipate their problems and help them reach a resolution as quickly as possible.

For all of the work it requires to make anticipating customer needs happen, the payoff is well worth it. Let’s take a look at how to anticipate customer needs and what it means to your customer service.

What Will You Gain by Anticipating Customer Needs?

In a word: loyalty.

We’ve touched on customer loyalty before, but we can’t stress its importance enough. In a digital-first age, customers have endless choices—and you need to make them choose you. Winning their loyalty has become more important than ever.

Customer service has become a major competitive advantage. According to Microsoft, 90% of customers say customer service is important to their brand choice and loyalty to that brand. And should those customer service expectations fall short, 58% of customers show little hesitation in severing the relationship. The days of implicit loyalty are long gone.

While customer loyalty should be enough of a draw, here are some more benefits to anticipating customer needs:

  • Increased revenue. When your customers feel taken care of, they’re more likely to come back. They’re looking for easy, frictionless experiences and will frequent businesses that provide them.
  • Less strain on your customer service team. Making things simple for customers will have a direct impact on your customer service team. Even when you provide more customer service, it’ll still be better for your agents. Customers will have fewer questions, there will be less urgency in their questions, and they’ll be less frustrated overall.

How to Predict Customer Problems

Every customer interaction tells a story; you just have to know what to listen for. Maybe it’s the same question popping up in chat, or a spike in response times when new updates roll out. These little signals often point to bigger issues waiting to surface. By pairing human intuition with data from your customer engagement tools, you can spot patterns early and take action before customers even realize there’s a problem. Encourage your team to share what they’re seeing, too. The more connected your people and data are, the easier it is to stay one step ahead and predict customer problems.

1. Set and Exceed Customer Expectations

Today’s customers don’t just want good service—they expect it. In fact, 55% of customers expect better service every year, according to Microsoft’s Global State of Customer Service Report. And HubSpot’s State of Service Report shows that 88% of businesses agree customer expectations have never been higher, with 79% noting that customers are more informed than ever.


So what does that mean for brands? It’s not about surprising and delighting customers once in a while; it’s about consistently setting clear expectations and then exceeding them. When customers know what to expect, they’re more likely to trust your brand. And when your team goes a step further by resolving issues faster, communicating proactively, or simplifying a complex process, you create moments that build loyalty.


The key is simplicity. Customers want frictionless experiences, easy navigation, and quick solutions. To deliver that, don’t just rely on intuition. Instead, ask your customers directly. Post-purchase surveys and satisfaction metrics like CSAT can reveal whether you’re meeting expectations. Take it one step further by talking to people who didn’t convert. Understanding why they walked away can highlight the gaps between what you think you’re delivering and what customers actually need.


In short, great service isn’t about random acts of delight—it’s about predictable excellence that customers can rely on every time.

2. Give Customers Convenient Service.

Regardless of whether they’re shopping for a vacation getaway, office supplies, or looking for subscription-based fashion, your customers expect convenience and fast service.

Just how fast? According to Hubspot’s Annual State of Service report, 90% of customers rate an “immediate” response as important or very important when they have a customer service question, which customers define as under 10 minutes.

Here are a few ways to give customers fast, convenient service:

  • Make customer service digital. Customers don’t want to interrupt their day to call customer service, wait on hold to speak to a representative, or spend days waiting for an email response. These slower communication methods are helpful in a pinch, but customers now want something more. They want digital customer service.

You don’t need a crystal ball to see that consumers are using mobile devices to communicate. Implementing business messaging to reduce wait times, deflect calls, and provide faster assistance disrupts and resets the consumer expectation that contacting a company for help is slow and inconvenient.

  • Be easily accessible. It sounds easy, right? If they found your website, surely they can find your customer service contact info hidden on your help page, which is hidden in your footer, or beneath a menu in your header. Yes, customers can probably find you, but make the process easier by being available to them wherever they are.

Have a web chat (also known as live chat) box on your website so customers can instantly chat with a customer service agent—no matter how far down your website rabbit hole they’ve gone.

Don’t stop there. Are your customers on Instagram? What about Twitter? The more places you’re available to answer questions, the happier your customers will be. With an omnichannel approach, they won’t have to go searching for help, and you’ll always have someone there when they need you.

At Quiq, we help our clients provide convenient ways for customers to engage with a brand and allow consumers to reach out to companies on their terms. Communicating with companies via messaging is still pretty new, and we’ve seen so many consumers respond with surprise and delight at the ability to text a company for help.

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3. Stop Communication Inefficiencies Before They Start

Many customer needs examples revolve around their time. As we mentioned above, inefficient communication just adds to your customers’ frustrations. You’ve likely experienced the struggle of having to navigate IVR systems (those interactive voice response systems that use automation to collect customer information and point them in the right direction). Whether you’re waiting on hold or waiting for an email response, that’s time you can’t get back.

During those moments of need, the last thing your customers want is to interrupt their day. Customer loyalty is won (or lost) in these critical moments.

Anticipate customers’ needs by working within their schedules and workflows. Here are a few ways to get started.

  • Make communication asynchronous. The biggest frustration when calling help centers is that you must put your day on hold to do so. Don’t force your customers to conform to your service center’s schedule. Instead, offer asynchronous messaging.

Communication methods like web chat and voice are helpful for getting answers to more complex questions, but they also require customers to block out their time and respond immediately. Asynchronous messaging, however, lets customers respond whenever they’re available. As a bonus, your customer service agents can handle multiple interactions at the same.

  • Take advantage of chatbots. Chatbots are the key to giving customers the immediate responses they crave without overwhelming your customer service team. They’re always available to provide simple answers to questions or, at the very least, acknowledge the customer’s question and let them know when an agent will be available to chat.

You can also use chatbots to help you anticipate customers’ needs by having them prompt customers with messages as they navigate through your website. Start with a welcome message, offer product suggestions based on browsing history, or provide answers to FAQs during checkout.

  • Eliminate repetitive tasks. Speed up redundant tasks by creating pre-build responses for common questions. Not only will you be able to speed up response times, but you’ll also ensure customers get the same accurate and helpful information no matter which customer service agent they talk to.

Imagine how your customers would perceive your brand if they were able to text a question to your contact center and get immediate help and resolution. No interruptions to their day, no inconvenience or waiting involved.

Aligning your people, processes, and technology to reduce effort and streamline communications will do wonders for your customer service. With each positive interaction, customers will anticipate great service well into the future.

When your customer expects to be taken care of, they can engage with your company without feeling that they have to play offense, which leads to more pleasant interactions for both sides.

4. Empower Agents to Make the Right Decisions for Customers.

Sometimes, anticipating customers’ needs means understanding that you can’t predict them all. Problems come up, mistakes get made, and website bugs happen. The trick is coming up with a plan to handle things that have no plan.

How do you do that? Empower customer service agents to take action to solve customer issues. Unfortunately, right now, not everyone has that power. Around 20% of service agents say their biggest challenge is not having the ability to make the right decisions for customers, according to Hubspot. But it’s likely that many more face this issue regularly.

Ensure your customer agents have the authority to do things like:

  • Offer discounts when customers encounter problems.
  • Expedite orders when shipments are lost or damaged.
  • Take as much time as they need to solve customer issues.

Without the authority to make these decisions on their own, agents have to wait for approvals or miss out on opportunities to surpass customer expectations.

5. Be Proactive, Not Reactive

The best customer experiences don’t just solve problems—they prevent them. Being proactive means spotting friction before it frustrates your customers. And customers agree— more than two-thirds want an organization to reach out and engage with proactive customer notifications, according to Microsoft. Maybe your data shows a spike in chat volume after product updates, or your agents notice the same questions popping up in support. Use those signals to reach out early, update FAQs, or automate helpful prompts before customers even have to ask.

Proactive service builds confidence. It shows customers you’re paying attention, that their time matters, and that you’re committed to constant improvement. Over time, this mindset turns reactive support teams into trusted partners—reducing inbound volume while boosting loyalty and satisfaction.

Being proactive can be as simple as sending tracking links to limit “where’s my order?” inquiries. Consider collecting top customer questions and sharing them during the purchasing process, or feed answers to an AI Agent for quick customer service response times.

6. Harness Agentic AI to Anticipate Customer Needs

Anticipating customer needs used to rely on intuition and experience—but Agentic AI takes it a step further. By combining real-time data with autonomous decision-making, Agentic AI can detect patterns, predict intent, and act before a human agent even steps in. For example, it can recognize when a customer is likely to churn, surface the right solution instantly, or trigger proactive outreach before an issue becomes a ticket.

Unlike traditional AI that waits for input, Agentic AI takes initiative because it’s learning from every interaction to continuously improve how it serves customers. This shift from reactive to anticipatory service helps brands deliver faster resolutions, smoother experiences, and a level of personalization that feels effortless. The result? Customers who feel seen, supported, and understood—long before they ever need to ask.

Equip Your Team with the Tools to Meet Future Needs.

You may not be able to predict every customer need, but you can make sure your team is always ready for whatever comes next. By setting clear expectations, spotting early signals, and leveraging AI to anticipate challenges, you can transform customer service from reactive to remarkably proactive.

At the heart of it all, customers want the same thing: quick, effortless resolutions and brands that truly understand them. Quiq’s Agentic AI platform helps leading companies deliver just that—empowering teams to anticipate needs, automate intelligently, and personalize every interaction at scale.Want to see how it all comes together? Download the Agentic AI for CX Buyer’s Kit to explore how Agentic AI can help your organization stay one step ahead of every customer need.

Frequently Asked Questions (FAQs)

What does it mean to anticipate customer needs?

Anticipating customer needs means predicting questions, problems, or preferences before customers voice them and then taking proactive steps to deliver solutions or information ahead of time.

Why is anticipating customer needs important for customer service?

It helps reduce frustration, prevent repetitive inquiries, and make customers feel understood. This level of foresight builds trust, loyalty, and long-term retention.

How can businesses start anticipating customer needs?

Start by analyzing customer data and feedback to identify recurring issues or requests. Then, use automation tools like AI agents or AI-powered prompts to offer solutions in advance.

What tools help teams anticipate and respond faster?

Messaging platforms that support asynchronous conversations, proactive chat triggers, and real-time data insights – like Quiq – enable teams to respond efficiently and personalize interactions at scale.

How does proactive communication improve the customer experience?

Proactive communication keeps customers informed and reassured. Sending shipping updates, appointment reminders, or self-service resources reduces uncertainty and enhances satisfaction.

What’s the difference between reactive and proactive customer service?

Reactive service responds only when a customer reaches out. Proactive service identifies needs and resolves potential issues beforehand – resulting in smoother, faster, and more positive interactions.

How can I best use customer feedback to improve products and service?

Customer feedback is one of the most valuable sources of insight your business has, as it tells you exactly where expectations are being met or missed. Start by categorizing feedback into themes like product usability, service experience, and communication. Then, use AI-driven sentiment analysis to identify trends at scale and spot emerging issues early. Share these insights cross-functionally between support, product, and marketing so improvements happen holistically, not in silos. Finally, close the loop by letting customers know when their feedback inspired change. It builds trust and shows you’re listening.

What metrics track proactive customer service effectiveness?

Measuring proactive service is about tracking prevention and perception. Core metrics include:

  • First Contact Resolution (FCR): Are customers getting answers before they need to reach out again?
  • Ticket Deflection Rate: How often are knowledge base articles, AI agents, or proactive alerts resolving issues before they become tickets?
  • Customer Satisfaction (CSAT) & Net Promoter Score (NPS): Gauge how proactive interactions impact sentiment.
  • Average Handle Time (AHT): When you anticipate needs effectively, resolutions should become faster and smoother.
  • Customer Effort Score (CES): A lower effort score means your proactive efforts are paying off.

Together, these metrics reveal how well your team is turning foresight into seamless customer experiences.

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Evaluating AI Models: Everything You Need To Know

Posted on J.R. Rettenmeyer

Key Takeaways

  • AI performance starts with evaluation. Metrics and human insight work together to keep models accurate, reliable, and bias-free.
  • Use the right tools for the job. Regression relies on MSE or RMSE; classification leans on accuracy, precision, and recall.
  • Generative AI needs extra care. Scores like BLEU and BERT help, but human review ensures outputs sound natural and on-brand.
  • Trust is built through testing. Continuous evaluation keeps AI aligned with real-world performance and customer expectations.

Machine learning is an incredibly powerful technology. That’s why it’s being used in everything from autonomous vehicles to medical diagnoses to the sophisticated, dynamic AI Assistants that are handling customer interactions in modern contact centers.

But for all this, it isn’t magic. The engineers who build these systems must know a great deal about how to evaluate them. How do you know when a model is performing as expected, or when it has begun to overfit the data? How can you tell when one model is better than another?

That’s where AI model evaluation comes in. At its core, AI model evaluation is the process of systematically measuring and assessing an AI system’s performance, accuracy, reliability, and fairness. This includes using quantitative metrics (like accuracy or BLEU), testing with unseen data, and incorporating human review to check for issues such as bias or coherence. It’s a critical step for determining a model’s readiness for real-world deployment, ensuring trustworthiness, and guiding continuous improvement.

This subject will be our focus today. We’ll cover the basics of evaluating a machine learning model with metrics like mean squared error and accuracy, then turn our attention to the more specialized task of evaluating the generated text of a large language model like ChatGPT.

How to Measure the Performance of a Machine Learning Model?

A machine learning model is always aimed at some task. It might be predicting sales, grouping topics, or generating text.

How does the model know when it’s gotten the optimal line or discovered the best way to cluster documents?

In the next few sections, we’ll talk about a few common ways of evaluating the performance of a machine-learning model. If you’re an engineer this will help you create better models yourself, and if you’re a layperson, it’ll help you better understand how the machine-learning pipeline works.

To answer that, evaluation must assess multiple dimensions: performance (does it predict accurately?), weaknesses (does it generalize to unseen data or overfit?), trustworthiness (can it be explained and trusted?), and fairness (is it biased toward certain groups?). Together, these components give a complete picture of model quality.

Evaluation Metrics for Regression Models

Regression is one of the two big types of basic machine learning, with the other being classification.

In tech-speak, we say that the purpose of a regression model is to learn a function that maps a set of input features to a real value (where “real” just means “real numbers”). This is not as scary as it sounds; you might try to create a regression model that predicts the number of sales you can expect given that you’ve spent a certain amount on advertising, or you might try to predict how long a person will live on the basis of their daily exercise, water intake, and diet.

In each case, you’ve got a set of input features (advertising spend or daily habits), and you’re trying to predict a target variable (sales, life expectancy).

The relationship between the two is captured by a model, and a model’s quality is evaluated with a metric. Popular metrics for regression models include the mean squared error, the root mean squared error, and the mean absolute error (though there are plenty of others if you feel like going down a nerdy rabbit hole).

Common regression metrics include Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). MSE measures average squared error, RMSE converts it to the original units, and MAE reduces the effect of outliers.

Evaluation Metrics for Classification Models

People tend to struggle less with understanding classification models because it’s more intuitive: you’re building something that can take a data point (the price of an item) and sort it into one of a number of different categories (i.e., “cheap”, “somewhat expensive”, “expensive”, “very expensive”).

Regardless, it’s just as essential to evaluate the performance of a classification model as it is to evaluate the performance of a regression model. Some common evaluation metrics for classification models are accuracy, precision, and recall.

Accuracy is simple, and it’s exactly what it sounds like. You find the accuracy of a classification model by dividing the number of correct predictions it made by the total number of predictions it made altogether. If your classification model made 1,000 predictions and got 941 of them right, that’s an accuracy rate of 94.1% (not bad!)

Both precision and recall are subtler variants of this same idea. The precision is the number of true positives (correct classifications) divided by the sum of true positives and false positives (incorrect positive classifications). It says, in effect, “When your model thought it had identified a needle in a haystack, this is how often it was correct.”

The recall is the number of true positives divided by the sum of true positives and false negatives (incorrect negative classifications). It says, in effect, “There were 200 needles in this haystack, and your model found 72% of them.”

Accuracy tells you how well your model performed overall, precision tells you how confident you can be in its positive classifications, and recall tells you how often it found the positive classifications.

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How Can I Assess the Performance of a Generative AI Model?

Now, we arrive at the center of this article. Everything up to now has been background context that hopefully has given you a feel for how models are evaluated, because from here on out it’s a bit more abstract.

Using Reference Text for Evaluating Generative Models

When we wanted to evaluate a regression model, we started by looking at how far its predictions were from actual data points.

Well, we do essentially the same thing with generative language models. To assess the quality of text generated by a model, we’ll compare it against high-quality text that’s been selected by domain experts.

The Bilingual Evaluation Understudy (BLEU) Score

The BLEU score can be used to actually quantify the distance between the generated and reference text. It does this by comparing the amount of overlap in the n-grams [1] between the two using a series of weighted precision scores.

The BLEU score varies from 0 to 1. A score of “0” indicates that there is no n-gram overlap between the generated and reference text, and the model’s output is considered to be of low quality. A score of “1”, conversely, indicates that there is total overlap between the generated and reference text, and the model’s output is considered to be of high quality.

Comparing BLEU scores across different sets of reference texts or different natural languages is so tricky that it’s considered best to avoid it altogether.

Also, be aware that the BLEU score contains a “brevity penalty” which discourages the model from being too concise. If the model’s output is too much shorter than the reference text, this counts as a strike against it.

The Recall-Oriented Understudy for Gisting Evaluation (ROGUE) Score

Like the BLEU score, the ROGUE score is examines the n-gram overlap between an output text and a reference text. Unlike the BLEU score, however, it uses recall instead of precision.

There are three types of ROGUE scores:

  • rogue-n: Rogue-n is the most common type of ROGUE score, and it simply looks at n-gram overlap, as described above.
  • rogue-l: Rogue-l looks at the “Longest Common Subsequence” (LCS), or the longest chain of tokens that the reference and output text share. The longer the LCS, of course, the more the two have in common.
  • rogue-s: This is the least commonly-used variant of the ROGUE score, but it’s worth hearing about. Rogue-s concentrates on the “skip-grams” [2] that the two texts have in common. Rogue-s would count “He bought the house” and “He bought the blue house” as overlapping because they have the same words in the same order, despite the fact that the second sentence does have an additional adjective.

The Metric for Evaluation of Translation with Explicit Ordering (METEOR) Score

The METEOR Score takes the harmonic mean of the precision and recall scores for 1-gram overlap between the output and reference text. It puts more weight on recall than on precision, and it’s intended to address some of the deficiencies of the BLEU and ROGUE scores while maintaining a pretty close match to how expert humans assess the quality of model-generated output.

BERT Score

At this point, it may have occurred to you to wonder whether the BLEU and ROGUE scores are actually doing a good job of evaluating the performance of a generative language model. They look at exact n-gram overlaps, and most of the time, we don’t really care that the model’s output is exactly the same as the reference text – it needs to be at least as good, without having to be the same.

The BERT score is meant to address this concern through contextual embeddings. By looking at the embeddings behind the sentences and comparing those, the BERT score is able to see that “He quickly ate the treats” and “He rapidly consumed the goodies” are expressing basically the same idea, while both the BLEU and ROGUE scores would completely miss this.

Why AI Model Evaluation is Critical

Agentic AI is redefining how businesses operate – automating reasoning, decision-making, and task execution across fields like engineering and CX. But with that autonomy comes risk. Every AI agent must be carefully evaluated, monitored, and fine-tuned to ensure it performs reliably and aligns with your brand’s goals. Otherwise, even a small model error can compound into major consequences for your brand.

If you’re enchanted by the potential of using agentic AI in your contact center but are daunted by the challenge of putting together an engineering team, reach out to us for a demo of the Quiq agentic AI platform. We can help you put this cutting-edge technology to work without having to worry about all the finer details and resourcing issues.

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Footnotes

[1] An n-gram is just a sequence of characters, words, or entire sentences. A 1-gram is usually single words, a 2-gram is usually two words, etc.
[2] Skip-grams are a rather involved subdomain of natural language processing. You can read more about them in this article, but frankly, most of it is irrelevant to this article. All you need to know is that the rogue-s score is set up to be less concerned with exact n-gram overlaps than the alternatives.

Frequently Asked Questions (FAQs)

What does AI model evaluation mean?

It’s how teams measure whether an AI system is performing as intended, accurate, fair, and ready for real-world use.

Why does AI model evaluation matter?

Evaluation exposes blind spots early and helps build confidence that the model can be trusted with customer-facing tasks.

How are generative models evaluated?

Metrics like BLEU, ROUGE, and BERT gauge quality, while human reviewers check tone, clarity, and usefulness.

Can metrics replace human judgment?

Not yet. Automated scores quantify performance, but humans still define what “good” sounds like.

How do I know if my model is ready?

When it performs consistently across test data, aligns with business goals, and earns trust through transparent evaluation.

AI in Customer Service: Interactions and Strategies

Posted on Max Fortis

AI is one of the most exciting new developments in customer service. But how does customer service AI work, and what does it make possible? In this piece, we’ll offer the context you need to make good decisions about this groundbreaking technology. Let’s dive in!

What is AI in Customer Service?

AI in customer service means deploying innovative technology–generative AI, custom predictive models, etc.–to foster support interactions that are quick, effective, and tailored to the individual needs of your customers. When organizations utilize AI-based tools, they can automate processes, optimize self-service options, and support their agents, all of which lead to significant time and cost savings.

What are the Benefits of Using AI in Customer Service?

There are myriad advantages to using customer support AI, including (but not limited to):

  • Quicker Response Times: AI swiftly manages both simple and complex questions, minimizing wait times and enhancing the overall customer experience.
  • Round-the-Clock Support: With AI in place, customers receive continuous support, no matter the time or day, ensuring help is always available when needed.
  • Reduced Costs: Automating repetitive tasks with AI reduces the need for large teams, which helps lower operational costs while maintaining service quality.
  • Increased Agent Productivity: AI takes care of mundane tasks, freeing up agents to focus on more strategic efforts, like cross-selling and delivering personalized solutions.
  • Tailored Interactions: Using customer data, AI personalizes responses and suggestions, making every interaction feel unique and relevant to the customer’s needs.
  • Effortless Scalability: As your business grows, AI can seamlessly manage a growing number of customer requests without adding additional resources.
  • Emotion Recognition: AI can assess customer sentiment in real-time, adapting its responses to ensure more positive and satisfying interactions.
  • Reliable Accuracy: AI ensures that all customer interactions are consistent and precise, based on your company’s guidelines and information, minimizing errors.
  • Agent Empowerment: By automating routine tasks, AI empowers agents to focus on more meaningful, high-impact work, making their roles more rewarding.
  • Optimized Processes: AI streamlines operations by identifying which tasks can be automated, allowing your support team to work more efficiently.

9 Applications for AI in Customer Service

Is AI right for your customer service operations? Here are some common ways companies are adopting it.

  1. AI Agents: AI-powered bots manage both routine and complex tasks, automating customer interactions and allowing agents to focus on higher-value work.
  2. Agent Assistance: AI provides real-time guidance and response suggestions, helping agents work more efficiently and confidently.
  3. Automated Workflows: AI streamlines workflows by intelligently routing tickets, suggesting responses, and summarizing conversations, improving efficiency.
  4. Workforce Management: AI predicts staffing needs, optimizes schedules, and personalizes shifts, helping reduce overtime and improve team management.
  5. Service Quality Assurance: AI speeds up quality assurance by reviewing customer interactions and providing actionable insights to improve agent performance.
  6. Call Management: AI helps manage calls by transcribing interactions, summarizing calls, and offering real-time support, reducing wait times and enhancing training.
  7. Help Center Optimization: AI improves knowledge base performance by identifying content gaps and automating the creation or updating of articles.
  8. Revenue Generation: AI drives upselling and cross-selling by integrating with backend systems, offering personalized product recommendations during customer interactions.
  9. Insights for Improvement: AI analyzes customer conversations to uncover patterns, trends, and areas for improvement, helping businesses refine their support strategies.

Things to Consider When Using AI in Customer Service

Now that we’ve covered some necessary ground about what customer support AI is and why it’s awesome, let’s talk about a few things you should be aware of when weighing different solutions and deciding on how to proceed.

Augmenting Human Agents

Against the backdrop of concerns over technological unemployment, it’s worth stressing that generative AI, AI agents, and everything else we’ve discussed are ways to supplement your human workforce.

So far, the evidence from studies done on the adoption of generative AI in contact centers have demonstrated unalloyed benefits for everyone involved, including both senior and junior agents. We believe that for a long time yet, the human touch will be a requirement for running a good contact center operation.

CX Expertise

Though a major benefit of customer service AI service is its proficiency in accurately grasping customer inquiries and requirements, obviously, not all AI systems are equally adept at this. It’s crucial to choose AI specifically trained on customer experience (CX) dialogues. It’s possible to do this yourself or fine-tune an existing model, but this will prove as expensive as it is time-intensive.

When selecting a partner for AI implementation, ensure they are not just experts in AI technology, but also have deep knowledge of and experience in the customer service and CX domains.

Time to Value

When integrating AI into your customer experience (CX) strategy, adopt a “crawl, walk, run” approach. This method not only clarifies your direction but also allows you to quickly realize value by first applying AI to high-leverage, low-risk repetitive tasks, before tackling more complex challenges that require deeper integration and more resources. Choosing the right partner is an important part of finding a strategy that is effective and will enable you to move swiftly.

The best way to ensure the time to value is there is by using automatic time tracking to find out how your real agents stack up to AI ones.

Channel Enablement

These days, there’s a big focus on cultivating ‘omnichannel’ support, and it’s not hard to see why. There are tons of different channels, many boasting billions of users each. From email automation for customer service and Voice AI to digital business messaging channels, you need to think through which customer communication channels you’ll apply AI to first. You might eventually want to have AI integrated into all of them, but it’s best to start with a few that are especially important to your business, master them, and branch out from there.

Security and Privacy

Data security and customer privacy have always been important, but as breaches and ransomware attacks have grown in scope and power, people have become much more concerned with these issues.

That’s why LLM security and privacy are so important. You should look for a platform that prioritizes transparency in their AI systems—meaning there is clear documentation of these systems’ purpose, capabilities, and limitations. Ideally, you’d also want the ability to view and customize AI behaviors, so you can tweak it to work well in your particular context.

Then, you want to work with a vendor that is as committed to high ethical standards and the protection of user privacy as you are; this means, at minimum, only collecting the data necessary to facilitate conversations.

Finally, there are the ‘nuts and bolts’ to look out for. Your preferred platform should have strong encryption to protect all data (both in transit and at rest), regular vulnerability scans, and penetration testing safeguard against cyber threats.

Observability

Related to the transparency point discussed above, there’s also the issue of LLM observability. When deploying Large Language Models (LLMs) into applications, it’s crucial not to regard them as opaque “black boxes.” As your LLM deployment grows in complexity, it becomes all the more important to monitor, troubleshoot, and comprehend the LLM’s influence on your application.

There’s a lot to be said about this, but here are some basic insights you should bear in mind:

  • Do what you can to incentivize users to participate in testing and refining the application.
  • Try to simplify the process of exploring the application across a variety of contexts and scenarios.
  • Be sure you transparently display how the model functions within your application, by elucidating decision-making pathways, system integrations, and validation of outputs. This makes it easier to model how it functions and catch any errors.
  • Speaking of errors, put systems in place to actively detect and address deviations or mistakes.
  • Display key performance metrics such as response times, token consumption, and error rates.

Brands that do this correctly will have the advantage of being established as genuine leaders, with everyone else relegated to status as followers. Large language models are going to become a clear differentiator for CX enterprises, but they can’t fulfill that promise if they’re seen as mysterious and inscrutable. Observability is the solution.

Risk Mitigation

You should look for a platform that adopts a thorough risk management strategy. A great way to do this is by setting up guardrails that operate both before and after an answer has been generated, ensuring that the AI sticks to delivering answers from verified sources.

Another thing to check is whether the platform is filtering both inbound and outbound messages, so as to block harmful content that might otherwise taint a reply. These precautions enable brands to implement AI solutions confidently, while also effectively managing concomitant risks.

AI Model Flexibility

Finally, in the interest of maintaining your ability to adapt, we suggest looking at a vendor that is model-agnostic, facilitating integration with a range of different AI offerings. Quiq’s AI Studio, for example, is compatible with leading-edge models like OpenAI’s GPT3.5 and GPT4, as well as Anthropic’s Claude models, in addition to supporting bespoke AI models. This is the kind of versatility you should be on the look out for.

What is the Future of AI in Customer Service?

The future of customer service lies in AI and humans working together to provide personalized and empathetic experiences. AI agents, powered by natural language processing and sentiment analysis, will handle complex inquiries and offer proactive, tailored solutions. Automation will streamline workflows, reducing response times and allowing agents to focus on higher-value tasks like upselling. AI-driven insights will continuously refine customer service strategies, improving efficiency and satisfaction, all while prioritizing data privacy and ethical AI use.

Where to Get Started with AI in Customer Service

To successfully integrate AI in customer service, begin by identifying key pain points like long response times or repetitive inquiries. Start small by automating areas such as self-service or support ticketing, and gradually expand as you refine its effectiveness.

It’s important to consider challenges like data privacy and AI bias. Ensure robust data protection measures are in place and train AI on diverse datasets to avoid unfair outcomes. Early-stage AI implementation may face issues with data quality and accuracy, but these can be addressed through data cleaning and continuous refinement.

When selecting AI tools, prioritize systems that balance functionality with ease of use. Ensure smooth integration with existing CRM systems and maintain clear escalation paths for more complex issues.

By starting small, monitoring AI performance, and continuously optimizing, businesses can successfully integrate AI in customer service with human agents to enhance efficiency. Ultimately, with thoughtful planning and continuous improvements, AI can help businesses create a more responsive, personalized, and efficient customer service experience that complements human capabilities and meets evolving customer expectations.

For more context, check out our in-depth Guide to Evaluating AI for Customer Service Leaders.

Customer Service Strategies: 5 Effective Ways to Improve eCommerce Support

Posted on Michael Hartsog

More than ever before, eCommerce businesses’ overall revenue is directly tied with the quality of their customer service. Today’s customers value shopping experiences more than price or product selection and can easily transition to one of many competitors. 86% of consumers say they would spend more for a better experience, and 76% of consumers said it’s far easier now to take their business elsewhere than ever before.

According to the 2020 ROI of Customer Experience Report, 94% of consumers outstanding experience with a brand say they would recommend it to family and friends. In contrast, only 13% of consumers who had an abysmal customer experience with a brand would recommend it.

From these statistics, it’s possible to conclude that marketing and sales alone aren’t enough for eCommerce businesses to remain competitive, maintain a substantial market share, and grow their brand reputation. They need to go above and beyond to implement outstanding customer service strategies, before and after closing the sale.

Here are 5 successful customer service strategies that eCommerce brands can quickly implement to improve their overall customer experience.

1. Build a Strong Customer Service Team

Start by hiring an excellent customer service team and creating an environment that promotes staff retention.

Conversational Engagement Platforms, like Quiq, are meant to augment human agents, not replace them. When offering top-notch customer support, software can’t replace the need for well-trained and skilled customer representatives.

Here are six strategies to attract talented, customer service-minded professionals.

  • Hire the right people: Hire for attitude. Look for employee representatives with empathy, patience, and excellent communication skills.
  • Train employee representatives: eCommerce hiring managers must train their employee representatives to understand their products and services and connect with their customers on an emotional level.
  • Equip customer service agents: Brand leaders should provide a platform to offer the best consumer experience without stress, overwork, or burnout. For example, Quiq’s Conversational Customer Engagement Platform enables companies to engage with customers across different channels in one centralized place, providing easy, simultaneous responses.
  • Track agents’ performance: Using surveys, management teams should collect feedback from customers on their experiences with employees and use the insights from these ratings to evaluate each representative’s performance.
  • Reward excellent performance: Incentivize top-performing employee representatives to motivate others to do more.
  • Listen to employee representatives: Ask for and listen to worker feedback to understand their needs.

Customer service is often the first area considered for budget cuts. However, this strategy is counterproductive. According to customer experience research, 50% of consumers would switch to a competitor after a bad experience, and 80% would switch after more than one bad experience. To keep consumers from switching to competitors, managers must prioritize customer service.

When it comes to the finesse and care it takes to navigate complicated customer inquiries or assist distressed customers, nothing beats a knowledgeable, well-trained, and accessible human agent. That’s why many channels, like Apple Messages for Business and Google Business Messages require brands to have live agents to escalate conversations to.

2. Personalize Every Conversation With Consumers

customer service improvement strategies

Personalizing customer conversations means tailoring support and service to their exact needs and expectations.

Customizing services to meet consumer demand gives eCommerce businesses a competitive advantage in their industries, helps deliver faster support from team members, makes customers feel more connected, and reinforces a consistent sense of satisfaction.

Here are a few ways to offer personalized service:

  • Engage with consumers where they already are
  • Transfer consumers smoothly across employee representatives
  • Mention people by their name in every conversation
  • Make recommendations when the requested product or service is unavailable
  • Offer free demonstrations and training to educate customers

Shoppers look toward eCommerce providers to know their needs and provide what they want. Research shows that 80% of consumers are more likely to make a purchase when brands offer personalized experiences, while 72% of consumers say they only engage with personalized messaging. To win and keep business, eCommerce employees must treat consumers as people — not numbers in a sales report — with unique needs and expectations.

A conversational engagement platform can help employees provide highly personalized experiences. For example, Quiq clients, like Stio, can send outbound messages to segmented customers and offer them targeted promotions. They can use Quiq’s intelligent routing feature to provide VIPs, who may spend at a certain level or who are part of their Pro Purchase Program with priority support.

3. Collect and Use Customer Feedback

Continually gathering feedback from shoppers on their experience can help eCommerce business leaders:

  • Understand their consumers’ needs, challenges, and pain points
  • Identify the positive and negative experiences shoppers have with their brand
  • Locate the cracks in customer service
  • Provide a more personalized experience for shoppers
  • Build trust and make shoppers feel valued

To obtain comprehensive and useful customer feedback, company decision-makers need to implement intuitive ways for consumers to communicate with them and ensure the information provides actionable insight for improving customer service.

Here are seven ways to collect customer feedback:

  • Send customer satisfaction surveys online
  • Organize feedback focus groups
  • Read reviews from third-party review sites
  • Build an online community for customers

Gathering feedback is only the first step. Next, it’s important for managers to create an action plan on cumulative insights and train employees to leverage this information when responding to customer complaints.

Continuously requesting consumer feedback will help identify any gaps in customer service and reduce the likelihood of a shopper feeling unsatisfied with their transaction.

4. Use KPIs to Gauge Customer Service Performance

It is not enough for eCommerce managers to train and equip their customer service teams. Measuring and tracking customer experience with the right KPIs can help the entire team understand how their consumer experience ties to overall business success, and how shoppers’ interactions with them change over time.

KPIs help eCommerce leaders appreciate their shoppers’ satisfaction level and readiness to continue doing business with them.

Here are four customer experience KPIs to track as an eCommerce strategy:

  • Net promoter score
  • Customer effort score
  • Rate of returning visitors
  • Revenue per customer

See the breakdown of each KPI below.

Net Promoter Score

Net promoter score (NPS) is a reflection of an eCommerce business’s customer experience. An eCommerce business’s net promoter score shows the likelihood of shoppers referring their family and friends to do business with that brand.

To calculate NPS, send a survey including the question, “How likely are you to recommend our product?” Customers provide their answers on a scale of 1 to 10.

After collecting this information, calculate NPS by subtracting the total number of entries below 5 from the total number of entries above 5.

An NPS below zero indicates a low customer satisfaction level. An NPS between zero and 30 shows more satisfied customers than unsatisfied customers. Above 30 implies that there are far more satisfied customers than unsatisfied customers. Above 70 means that customers are loyal and will be the source of a lot of word-of-mouth referrals.

Customer Effort Score

Customer Effort Score (CES) reveals how much work consumers must put into researching products and services or completing a particular task. For example, how long does it take the average shopper to get a refund, sign up, or get a request ticket answered?

Customer effort score reflects how accessible a business is to its consumers.

As with NPS, calculate CES using a survey with the question, “How much effort did you have to put into completing this task?” Ask customers to respond on a scale of 1 to 7 or 1 to 5.

Here’s the breakdown for each scale.

On a scale of 1 to 5:

  • 1 = Very high effort
  • 2 = High effort
  • 3 = Neutral
  • 4 = Low effort
  • 5 = Very low effort

On a scale of 1 to 7:

  • 1 = Extremely difficult
  • 2 = Very difficult
  • 3 = Fairly difficult
  • 4 = Neither
  • 5 = Fairly easy
  • 6 = Very easy
  • 7 = Extremely easy

To calculate CES, divide the total effort scores by the number of responses. Measure it right after a purchase or service interaction. On a 1–7 scale, a score of 5+ means customers find your product or service easy to use; below 5 suggests they’re facing challenges.

Rate of Returning Visitors

The rate of returning visitors (RVR) reflects the effectiveness of customer success strategies and user experience for an online service. If shoppers enjoy their experience on the site, they’ll be more likely to return.

For an online service, calculate RVR by dividing the number of returning visitors by the number of unique visitors. The higher the value, the better the customer experience on the site.

While RVR can vary for different industries, a good RVR is 30% or more.

Revenue Per Customer

Revenue per customer (RPC) ties the overall consumer experience to a company’s bottom line.

To calculate RPC, divide the total revenue by the total customer count.

A high RPC means consumers have a consistently positive experience with a business. They are loyal, repeat shoppers who recommend the brand to friends and family.

Combined, these four KPIs provide insight into the quality of customer service, the satisfaction consumers derive from a product or service, and areas for improvement.

For example, a CES below 5 for contacting support could mean one or more of the following:

  • Customers don’t receive a timely response
  • Consumers must try multiple channels to access the customer service team
  • Customers must repeat themselves to every new call center agent they interact with
  • It takes a long time for representatives to resolve their issues

Company executives should dig deep to uncover the factors producing the low KPIs and benchmark their KPIs with their competitors to know where they stand.

5. Provide a Consistent Cross-Channel Experience

A cross-channel customer service strategy allows eCommerce employees to provide seamless and consistent customer support across different channels. Shoppers can switch between SMS, webchat, and social media without any service interruptions or inconsistencies in quality.

Cross-channel customer service helps shoppers get quick responses to their needs, improves the brand’s reputation and trust, and boosts consumers’ positive experiences.

Here are seven strategies to implement a cross-channel experience:

  • Ensure customers can reach employee representatives offline and online on the platform of their choice
  • Implement seamless transition when moving customers from one call center agent to another
  • Maintain comprehensive documentation on each customer to help call center agents continue conversations based on the last engagement
  • Build mobile-friendly customer support pages to provide mobile consumers a smooth experience
  • Respond on time to customer queries on all channels and present practical solutions to their needs
  • Create a comprehensive self-service solution to help customers solve their problems by themselves
  • Present a unified front and ensure every team and department collaborate and share information

Today, 95% of customers use three or more channels to connect with a company in a single service interaction, and 65% of customers expressed frustration over inconsistent experiences across channels. Establishing a presence on all available platforms might spread a company’s resources too thin and lead to inconsistent, negative experiences. Instead, focusing on meeting consumers where they are and establishing unified, consistent experiences on their most used channels will create a better overall customer experience.

With Quiq’s cross-channel digital messaging platform, employees can provide a consistent experience for consumers across different digital platforms.

Also, to implement the best customer service strategy, nothing beats working with the right conversational customer engagement platform. Ideally, interacting with consumers will be easy and fun for employees and provide frictionless support for shoppers, while increasing the brand’s competitive advantage, market share, and overall revenue.

Key Takeaways

Improving eCommerce customer service strategies doesn’t have to be complicated—it just requires consistency, the right tools, and a customer-first mindset. Here’s a quick recap of the five strategies covered:

  • Hire and retain the right people. A strong customer service team is your foundation. Invest in hiring, training, and supporting representatives who can deliver real value to your customers.
  • Personalize every interaction. Today’s shoppers expect tailored experiences. Meeting them where they are, remembering their preferences, and offering relevant recommendations all go a long way.
  • Collect and act on feedback. Listening to your customers helps identify areas for improvement and ensures your support is aligned with their expectations.
  • Measure what matters. Tracking KPIs like NPS, CES, and revenue per customer gives you the insight you need to improve and scale your support strategy effectively.
  • Provide a consistent experience across channels. Whether it’s SMS, web chat, or social media, customers expect seamless, responsive support—no matter where they reach out.

When done right, these strategies don’t just improve customer service—they help build loyalty, encourage repeat purchases, and turn satisfied shoppers into brand advocates.

Invest in a Quality Customer Engagement Platform

More than ever, consumers want to do business with brands that make it easy to browse, shop, complete transactions, and get support on the consumers’ terms. eCommerce businesses can gain a significant competitive advantage by providing these experiences through seamless engagement via digital channels.

Improving customer success and satisfaction is a long-term plan that requires buy-in and commitment from management, investment in training employee representatives, collecting feedback consistently, measuring the right things, and investing in a platform to manage everything.

Quiq is a conversational customer engagement platform that enables enterprises to unify SMS, email, chat, and social media interactions with their consumers all in one place. Request a demo to see how Quiq can help employee representatives provide a seamless customer service experience.

6 Tips to Improve Retail Customer Experience

Posted on Max Fortis

If you’re like the rest of the retail industry, you either have to build an online shopping experience from scratch or seriously ramp up your web-store capabilities.

This meant your retail customer experience took a hit.

As customer satisfaction declined in 2021 and expectations rose, online retailers faced pressure to adapt or risk losing customers.

So what’s an e-tailer to do to improve online retail customer satisfaction?

Embrace messaging.

Even if you’ve adopted various forms of business messaging, there are many ways to elevate your strategy and improve your customer satisfaction in retail.

Read on to see why messaging has become a vital part of improving retail customer experience, along with 6 ways to use it to improve customer satisfaction.

Why messaging is essential in online retail.

Messaging is changing the way online retailers do business, but it’s more than a box that needs checking. You shouldn’t just roll out an SMS/text messaging or WhatsApp program and staff it with customer service reps from your contact center. To make the most of it, you need a well-developed strategy.

Text messaging especially has the potential to improve the retail customer experience. Four out of 5 customers send a text message on a daily basis, and nearly half of consumers prefer messaging as a means to connect with businesses. Your customers are telling you that they want to interact via messaging, why not listen?

Here at Quiq, we’ve seen rapid adoption of messaging by online retailers. Brands like Overstock, Pier 1, and Tailor Brands have experienced tangible benefits, including more natural customer engagement, lower service costs, and a reduced workload.

6 ways to improve online retail customer satisfaction with messaging.

E-tailers struggle with customer satisfaction. There are some aspects out of your control (ahem: shipping and manufacturing anytime after March 2020), but there are things you can do to alleviate your customers’ struggles.

Messaging is a big part of that. Having reliable communications and using them strategically helps promote customer satisfaction. Here are 6 ways you can use messaging to improve your online shopping experience.

1. Help shoppers find the perfect product.

The biggest argument against online shopping for years has been the lack of personalized customer service. Shoppers can’t ask for recommendations (and algorithms hardly make up for it), sizing help, or general advice.

Messaging helps your team close that gap (along with the support of AI agents). Yes, it’s great for post-purchase interactions. But customers also want help before they checkout. In fact, nearly two-thirds (64%) of customers use messaging when they want to make a purchase or a booking/reservation, according to our Customer Preference for Messaging report.

Quiq lets you help customers when they need it most. You can provide the on-demand service they need while shopping your site, viewing your products on social media, or browsing your app. You’re giving them that in-store, personalized experience while they’re going about their day. This kind of proactive assistance plays a key role in improving retail customer experience.

2. Provide transparent interactions.

When customers call your support line, are they greeted with a “This call may be recorded” message? That’s a great tool for your business, but what about the customer? Once they end the conversation, they have no record of the interaction. They can’t refer back to it later, check to make sure they heard everything correctly, or prove that the conversation even existed. Yes, some companies offer a confirmation number, but that does little to help your customer access the information.

Even popular web chat solutions can be session-based, meaning when the session is over, the conversation disappears. Customers can’t refer back or naturally start the conversation back up when a related question pops up.

We know the importance of asynchronous communication. Customers aren’t always available to respond instantly, and sometimes new questions appear once their first ones have been answered. That’s why Quiq’s web chat conversations are persistent; they start right where they left off. Plus, customers can request to have their web chat transcripts emailed to them.

You get an even longer messaging history on channels like SMS/text and Facebook Messenger.

Persistent communication threads help build trust and enhance the retail customer experience. Mobile messaging adds an additional layer of transparency. Message history can stretch back even further than the last conversation on SMS and Facebook Messenger, giving the customer access to older messages and more conversation details.

3. Staff for multiple messaging channels.

An omnichannel messaging strategy can greatly enhance your retail customer experience when it’s done right. Customers frequently ping-pong across platforms. Zendesk’s 2022 CX Trends report found that 73% of customers want the ability to start a conversation on one channel and pick it back up on another.

Yet, it’s all too easy to add messaging channels and hand them over to your call center agents. While it’s feasible to cross-train your customer support team on both phones and messaging, there’s a little more to it than that.

First, you need to ensure you have available staff to cover multiple messaging channels. Asynchronous messaging does save time over traditional phone calls. But if your team is already stretched thin, adding additional channels will just feel like a burden. Plus, we all know that customers hate to wait.

Try assigning staff members to your messaging channels. While Quiq clients can serve customers on the platform the customers prefer, it takes a trained and available support team for a great omnichannel experience.

4. Reduce wait times.

Speaking of waiting, customers hate it. While you might think the pandemic has made customers more patient and understanding, the opposite is true. Frustrated customers want things to return to “normal” and have higher expectations of all business, e-tailers included. According to Zendesk, 60% report that they now have higher customer service standards after the pandemic.

Messaging helps smooth the peaks of inbound support requests when you need it most. Since agents can respond to messages at different speeds, they can handle multiple inquiries at once. A message doesn’t require their full attention for a fixed amount of time. As a result, Quiq clients report work time is often reduced by 25–50%. That time savings leads to faster resolutions and an improved retail customer experience.

5. Delight your visually-driven audience.

Why spend 5 minutes describing a problem when you can take a picture of it in 5 seconds? Visual communication is an underrated part of creating a memorable customer experience in retail. Phone calls only give you one way to interact with your customer, and emails are too slow for problems that need immediate attention.

Rich messaging is the next step to improving your customer service experience. Found in Apple Messages for Business, Google’s Business Messaging, and more, rich messaging amplifies your customer conversations. From GIFs to images to videos, there are plenty of features to engage your audience visually.

You can even take it to the next level and build an entire customer experience with rich messaging. Process secure transitions, schedule appointments, and send reminders, all through messaging.

See how TechStyleOS integrated rich messaging with Quiq >

Improve your customer satisfaction and boost engagement with these advanced features that are sure to delight shoppers.

6. Entice customers to come back.

Remember those high customer expectations? Unfortunately, customers are quick to switch brands. Which means you need to consistently give them the best online shopping experience.

Sustained follow-up is a major contributor to customer experience in retail. It doesn’t stop at the sale. A good messaging strategy includes post-purchase engagement to encourage customers to come back. While email is currently the preferred method for online retail, it comes with low open rates and even lower click-through rates.

Instead, lean into outbound text messaging for post-purchase communications. Here are a few easy examples to get started:

  • Send an order confirmation
  • Share a shipment tracking link
  • Send a special discount code
  • Ask them to join your rewards program

With nearly a 100% read rate, outbound text messaging is a more engaging way to connect with customers.

Messaging is the way to customer satisfaction.

Online retailers face many challenges, but engaging with customers shouldn’t be one. Messaging is already helping many online retailers establish a stronger relationship with their customers and elevate the retail customer experience. For many retailers, adopting a messaging platform gave them a customer-centric way to chat with their shoppers.

Messaging has become a vital part of the online shopping experience, and implementing these smart strategies will help skyrocket customer satisfaction. And Quiq is there to help.

15 Tips to Friendly Customer Service

Posted on Max Fortis

We frequently talk about metrics and tools, and systems for providing excellent customer service. While those are all critical aspects of a great customer experience, there’s one simple thing to remember, above all else:

Start with friendly customer service.

And we don’t mean that fake-smile, roll-your-eyes-when-you-turn-your-back service from department stores of the past. We mean true, genuine, friendly customer service.

Let’s dig into what friendly customer service looks like in the digital age and why it’s vital to business success.

Friendly customer service is critical, especially online.

As commerce moves more and more online, it gets harder to convey friendly service. Customers can’t see your bright shining face, they can’t discern your helpful tone of voice. But those aren’t the only reasons friendly service is so important.

Customers have more choices than they used to. Products and services are harder to differentiate, so many customers rely on other intangible ways to decide between brands. Customer service is a great way to stand out, and having friendly customer service could put you miles ahead of your competitors.

In Salesforce’s State of the Connected Customer report, customers ranked “Treat me as a person, not a number” as one of the top 3 actions that build trust. And 94% say how a company treats its customers influences their decision to buy.

Plus, customers’ opinions of customer service are often cumulative. Even small interactions add up to their overall perception of your brand. Customer experience was the top factor (43%) that drives customer loyalty for online shopping, according to a consumer survey from BrizFeel.

Keep reading for some friendly customer service tips.

What does friendly customer service look like over messaging?

Even this writer will admit it—enthusiasm can get lost over messaging. It’s easy to read helpful sentences as condescending or patronizing. And periods? Don’t even get us started.

But there are ways to appear more friendly through online customer service. Here are a few of them.

1. Start with a *digital* smile.

You’ve heard of service with a smile—and even how a smile comes through over the phone—but what does that look like for customer service messaging? It’s all about enthusiasm!

Start with an enthusiastic welcome and a few pleasantries if your customer’s time permits.

For example, start with something like this:

Hello! How are you this morning/afternoon/evening? What can I help you with today?

Even small variations from the standard, “Hi, how can I help you?” will make a customer feel less like a number and more like a person.

2. Use exclamation points!

Don’t be afraid to throw in exclamation points! At times, exclamation points have been controversial (do we use them in emails?), but messaging lends itself to more casual conversations. Use them, especially in intros and goodbyes (i.e., Hello! and Let us know if there’s anything else we can help you with!). Just be sure to pay attention to the customers’ sentiment. If they’re upset or angry, an exclamation point can rub them the wrong way.

3. Embrace emojis.

It’s hard for your customers to see or hear the tone in your text, so use emojis to help connect with them, just like you would a friend. Okay, maybe not just like your friend. Avoid accidentally inappropriate emoji conversations by laying out which are and are not appropriate for your support staff to use.

As long as emojis fit within your brand voice, use them to punctuate a conversation, just like you would with real emotions in person. We’d stick with the simple smiley faces or a well-timed shocked face .

4. Use sentiment check-ins.

It’s hard to tell when a customer is satisfied with the conversation, frustrated, or confused. Ask questions throughout the conversation to check in with them. Simple questions like “Do you have any questions?” or “Is that what you were looking for?” can help you assess how the customer is feeling.

You can also use Agentic AI platforms to help track customer sentiment through written cues and even prioritize conversations based on it.

5. Use your manners.

Texting has shortened our written communications and eliminated a lot of the niceties of the past. But when you’re chatting with customers, it’s important to remember your manners. Say please when asking for information, and always say thank you after they’ve given it to you.

While many customers think manners are table stakes, it’s certainly worth repeating. Even though messaging is a much more casual communications channel, niceties work for every occasion.

6. Be mindful of customers’ time.

Your customers are busy! Although many digital communication channels are asynchronous (both you and the customer don’t have to be present at the same time), you want to keep conversations as short as possible, without losing that friendliness.

Sometimes that means skipping the small talk. While it works in person and sometimes over the phone, it rarely works over messaging. Asking about your customer’s day is fine, but if you’re getting short, clipped responses, that’s an indicator that they’re in a hurry. Most of the time, customers want to get in, get their questions answered, and get out. Respect that, and don’t draw out the conversations unnecessarily.

7. Respond as quickly as possible.

We know that this is a given (of course, you’re responding quickly), but it’s important to remember. When you’re chatting with a friend, an instant response will always show more enthusiasm than one that comes 30 minutes later. Do your best to respond quickly to problems that your customers deem urgent.

Responding quickly is also more likely to reflect the pace of an in-person conversation, which customers might find more natural and friendly.

8. Don’t skimp on product knowledge.

When agents can’t answer questions or spend the majority of their time searching for answers, friendly service can go out the window. While information is at your agents’ fingertips, they should still know as much about the business as possible.

Continually train agents on new products and services, along with ongoing soft skills training. It’ll keep agents on top of their product knowledge and keep them fresh and enthusiastic to serve customers better. Another avenue you can explore is an AI agent for customer service.

9. Be respectful.

It’s easy to get swept away in emotions, especially when agents have dealt with their 10th angry customer of the day. Customer service can be a difficult job, especially when customers are frustrated over products and services (or even with the world in general). While it’s easier said than done, agents should stay calm when chatting with customers.

Here are some ways to help agents get through tough conversations:

  • Step away if emotions get too high.
  • Loop in a manager or another support agent to help diffuse the situation.
  • Use role-playing to practice handling difficult situations.
  • Remember, it’s not personal.

Reducing agent stress will also help promote a more respectful environment for customers. When agents aren’t worried about meaningless metrics (only the important ones) or an unstable work environment, they’re much more likely to have friendly customer interactions. Only 15% of agents are extremely satisfied with their workload, according to Zendesk. That dissatisfaction will likely trickle down to your customers.

10. Be honest.

Ready for a cliche? Honesty is the best policy! Okay, maybe not always, but it’s certainly important when delivering friendly customer service.

Customers say communicating honestly and transparently is the #1 way to build trust, according to Salesforce. That means customer service reps should give real answers when customers ask why something went wrong and be upfront about internal mistakes.

Honesty also needs to be a top-down initiative. Agents can’t be open and honest with customers if they’re not getting the truth themselves. Incorporate honesty into every level of your organization, and your customers will feel it.

11. Active Listening

Active Listening is one of those underrated customer service tips that can instantly elevate the customer experience. It’s not just about hearing someone’s words, it’s about fully understanding what they mean,  how they feel, and what they need. Customers want to feel like they’re being heard, not just nodded along to.

When reps actively listen, they create space for the customer to express themselves. A great way to show this is by paraphrasing what the customer said. Try something like, “What I’m hearing is that your order didn’t arrive on time, and you’re hoping we can make that right.” This not only confirms understanding but shows the customer you’re paying attention.

Make active listening a core part of your customer service training. Encourage team leads to role-play real conversations, highlight great listening behavior, and provide scripts that include empathetic reflection. Listening may seem like a soft skill, but it’s the foundation of strong, friendly customer service.

12. Empathy.

Empathy is the ability to step into your customer’s shoes, see the situation from their perspective, and respond with compassion. In customer support, that means recognizing emotions, especially frustration, and showing you genuinely care about resolving the issue.

An empathetic phrase can shift the tone of a conversation in seconds. For example: “I can see how that would be frustrating. Let’s fix this together.” Simple, but powerful.

Empathy isn’t just a personality trait; it should be embedded into your customer service culture. Regularly surface examples of great empathetic responses in team huddles, and coach agents on tone and emotional intelligence. When empathy becomes second nature, so does excellent service.

13. Patience.

Let’s face it: not every customer interaction is quick or easy. Some people need more time to explain their issue, or they may be feeling overwhelmed. In those moments, patience is more than a virtue; it’s a necessity.

Train your team to pause before responding, give customers space to speak without interruption, and allow silences to settle. Rushing to solve a problem might seem efficient, but it can make a customer feel dismissed.

Make sure managers call out patient behavior in coaching sessions. When agents are praised for taking the time to do things right, rather than fast, it reinforces the importance of true customer care.

14. Personalization.

A personalized customer service experience doesn’t just solve problems, it builds relationships. When customers feel like you know them, remember them, and value their preferences, they’re far more likely to stay loyal.

Something as simple as referencing a past interaction, “I see you’ve ordered this before, want to try the new version?” It can create a moment of delight. Tools like CRMs and AI-powered customer service messaging platforms help reps deliver these experiences at scale.

Personalized service isn’t just nice to have anymore; it’s expected. Make sure your team uses the data available to treat each customer like an individual, not a ticket number.

15. Customer feedback utilization.

Gathering customer feedback is great, but acting on it is where the magic happens. Customers want to feel like their voice matters and their insights lead to improvements. 

Make it a habit to follow up on feedback, especially if it influenced a change. A quick message like, “Thanks to your input, we’ve improved our delivery notifications,” turns a suggestion into a loyalty-building moment.

Incorporate feedback review into your regular cadence with operations and product teams. When everyone is aligned, you can close the loop and create a system that continuously improves your service and your relationship with your customers.

Friendly customer service pays off.

Need some motivation to implement these friendly customer service tips? How about higher revenue?

According to Zendesk, 81% of customers are more likely to make another purchase after a positive customer service experience. There’s more:

  • 74% of customers are more likely to forgive a mistake after excellent customer service.
  • 70% have made a purchase decision based on customer service.
  • 61% say they would switch to a competitor after just one bad customer service experience.

Friendly customer service is the key to building brand loyalty, enhancing customer retention, and increasing revenue.

Remember: Friendly service first.

If you only remember one thing from these friendly customer service tips, let it be that friendliness trumps most. It turns mistakes into opportunities, bad experiences into good ones, and good experiences into great ones.

Yes, metrics and tools and processes, and surveys are all important aspects of running a working customer service center. But friendly agents with a heart are what make it truly successful. With Quiq’s AI-powered platform, you can give your team the tools to deliver that kind of service at scale.

5 Customer Experience Predictions for 2025

Posted on Cristina Bravo-Olmo

Customer expectations are evolving faster than ever, fueled by rapid technological advancements and shifting preferences. As we look toward 2025, it’s clear that businesses must adapt or risk falling behind. The future of customer experience will be shaped by the ability to meet customers where they are—quickly, personally, and intelligently.

Brands that anticipate and act on key customer experience trends will gain a powerful advantage. By investing in the right technologies and strategies, companies can deliver memorable experiences that drive loyalty and growth.

Here are five Customer Experience Predictions for 2025 that businesses need to watch, and why acting on them now will make all the difference.

1. AI Agents Revolutionizing Self-Service

AI agents are redefining the concept of self-service in 2025. Unlike the rigid, scripted chatbots of the past, today’s AI agents, powered by large language models, can understand complex queries, adapt in real time, and carry customer conversations from start to finish. These AI-powered systems aren’t just transactional—they’re agentic, meaning they can reason, plan, and personalize interactions dynamically.

The rise of large language models has fueled this transformation, enabling AI agents to provide human-like service with speed and precision. Brands leveraging agentic AI are seeing dramatic improvements: faster resolution times, lower support costs, and higher customer satisfaction.

Companies across industries are now deploying AI agents to manage full customer journeys—from answering questions and troubleshooting issues to processing transactions—all without human intervention. In many cases, customers don’t even realize they’re interacting with AI, highlighting the growing trust and comfort consumers have with AI-powered support.

However, this shift brings new challenges. Businesses must rethink workforce training, focusing on preparing teams to collaborate with AI Assistants and to step in strategically when human empathy is critical. Support design also needs to evolve, with workflows built to optimize both human and AI capabilities.

AI agents are no longer a nice-to-have; they’re setting a new baseline for customer service excellence. Expect the future of customer experience to become even more agentic, intelligent, and efficient in the years ahead.

2. Hyper-Personalization Becoming Standard

Personalization is no longer a competitive advantage; it’s becoming an expectation. In 2025, hyper-personalization will be the new normal, driven by real-time data, predictive analytics, and agentic AI platforms capable of delivering uniquely tailored experiences at scale.

Hyper-personalization goes beyond simply addressing a customer by name. It means anticipating needs, understanding preferences, and delivering the right message, product, or service at exactly the right moment. Think product recommendations based on purchase history, personalized content that reflects browsing behavior, or proactive service offers when issues are detected.

Brands like Netflix and Amazon have set a high bar for individualized experiences, and customers now expect that level of insight from every company they engage with.

The business impact of hyper-personalization is significant: higher conversion rates, improved customer retention, and stronger loyalty. Personalized experiences demonstrate that a brand truly understands and values its customers, turning casual buyers into lifelong advocates.

However, executing hyper-personalization comes with challenges. Companies must navigate growing concerns around data privacy and consent, as well as the technical complexity of integrating disparate systems to create a unified customer view.

Still, brands that invest in the right data infrastructure and agentic AI tools today will reap major rewards in the future of customer experience.

3. Real-Time Feedback Loops Enhancing CX Agility

One of the most actionable customer experience predictions for 2025 is the rise of real-time feedback loops as a standard practice. These tools, like in-app surveys, feedback buttons, and live chat sentiment analysis, allow businesses to capture customer sentiment in the moment, rather than relying solely on post-interaction surveys.

Real-time feedback provides instant insight into how customers are feeling and where friction points are emerging. More advanced systems now use AI to analyze this input on the fly; detecting negative sentiment, identifying emerging trends, and even escalating issues to supervisors before a customer disengages.

Across industries, we’re seeing this trend take shape. In e-commerce, brands are deploying checkout feedback forms to reduce cart abandonment. Hotels are using mid-stay surveys to address concerns before checkout. SaaS platforms are embedding product experience prompts to guide onboarding and resolve usability issues in real time.

The result is a more agile CX operation, one that can quickly adapt to user needs, improve satisfaction, and reduce churn. But to be effective, companies must avoid common pitfalls like survey fatigue or collecting feedback without follow-through. As real-time engagement becomes the norm, customers will expect not just to be heard, but to see changes based on what they say.

4. Unification of Customer Data Across Platforms

Today’s customer data is often scattered across CRMs, marketing automation systems, support platforms, and social channels, creating fragmented experiences and missed opportunities. In 2025, we’ll see a major push toward unifying customer data to power more consistent, personalized interactions.

Customer Data Platforms (CDPs) and unified customer experience systems are becoming essential tools for organizations seeking a 360-degree view of their audience. By centralizing data from across the customer journey, businesses can better understand behaviors, preferences, and needs—and act on those insights in real time.

The benefits are clear: consistent messaging across channels, more accurate personalization, and deeper customer insights that drive smarter decision-making.

Yet challenges remain. Integration costs, legacy systems, and internal data silos can slow down unification efforts. Businesses will need to invest in flexible, scalable platforms that can aggregate and activate customer data without overwhelming existing operations.

Ultimately, unifying customer data is about delivering the kind of seamless, agentic experiences that customers now expect—and that future customer experience trends will demand.

5. The Rise of Voice AI: Transforming Customer Service Interactions

Voice AI is poised to reshape how brands engage with customers. Moving beyond traditional phone support, Voice AI platforms leverage agentic AI to understand context, detect intent, and deliver human-like conversations at scale.

Early voice bots were limited and often frustrating, but today’s Voice AI agents are capable of handling complex interactions with natural language understanding and adaptive learning. They can answer questions, troubleshoot issues, complete transactions, and even provide empathetic responses—all without a live agent.

For businesses, the benefits are substantial. Voice AI offers 24/7 availability, dramatically reducing wait times and operational costs. Automating routine interactions frees human agents to focus on more complex and sensitive customer needs, boosting both efficiency and customer satisfaction.

As consumer expectations for fast, personalized service continue to rise, Voice AI meets the demand by offering consistent, context-aware support that feels natural.

The adoption of Voice AI also supports broader customer experience predictions around personalization, efficiency, and omnichannel engagement. Companies that embrace this technology today will be better equipped to meet and exceed customer expectations tomorrow.

Strengthen Your Customer Experience in 2025

Even though the future is uncertain, brands have the ability to give customers a top-notch experience with every interaction. You can be the bright spot in a customer’s day, a moment of reprieve in an otherwise tumultuous week.

Use these customer experience predictions to anticipate what’s to come in 2025 and plan ahead. And if you need help facilitating customer conversations, scaling, or meeting your customers where they are, Quiq can help.

Ready to take a deeper look at the power of an agentic AI platform and see what Quiq can do for your customer service team? Schedule a Quiq demo.

Contact Center Management Strategies For Your Team

Posted on Michael Hartsog

Effective contact center management is essential to running a contact center. It’s not as simple as setting up a few phones and handing your team a script (although we’re sure no one has thought that since 2005). But it’s equally likely that you’re so bogged down with managing the everyday realities that you can’t see the forest through the trees.

That is, you can’t see just how cluttered the contact center has become.

From staffing and training to managing operations and tracking KPIs, you spend too much time keeping a contact center running instead of doing what you do best: Connecting with customers.

That’s where Quiq comes in. Our Conversational AI Platform uses breakthrough technology to make it easier to engage customers, whether through live chat (also known as web chat), text messaging, or social media.

Let’s take a look at ways to improve your call center efficiency and how Quiq can help you reduce the clutter with 9 effective call center strategies in a handy infographic:

9 ways to improve call center efficiency

Download as a PDF instead

What is Contact Center Management?

Contact center management is the practice of overseeing all aspects of a contact center to ensure it consistently delivers exceptional customer service. This includes managing day-to-day operations, aligning teams, implementing strategies, and leveraging technology to create efficient and satisfying customer experiences.

At its core, contact center management involves responsibilities like workforce scheduling, performance tracking, and customer experience oversight. Managers must ensure the right number of agents are available at the right times, and that those agents are supported with the tools and coaching they need to succeed.

A critical part of effective management is maintaining consistency across all communication channels—whether customers are reaching out via phone, live chat, SMS, or social messaging. Customers expect seamless experiences, and it’s the job of contact center leadership to make that happen.

Contact center management also includes implementing smart strategies to drive better results. Techniques like skill-based routing ensure customers are connected with the most qualified agents, while self-service tools empower users to resolve issues quickly on their own. Together, these strategies enhance operational efficiency and improve customer satisfaction—two key outcomes of strong contact center management.

What Does a Successful Contact Center Manager Look Like?

Behind every high-performing contact center is a skilled manager who acts as the foundation of effective contact center management. This role requires balancing people, performance, and technology to keep operations running smoothly while driving customer satisfaction.

A successful contact center manager is a strategic thinker—someone who doesn’t just manage the present but plans for the future. They design and implement forward-thinking contact center strategies that improve operational efficiency and enhance the customer experience.

They are also data-driven decision-makers, skilled at interpreting performance metrics and turning insights into action. Strong contact center management means identifying trends, adjusting workflows, and setting measurable goals that lead to real results.

As an empowering leader, the manager coaches agents regularly, helping them adopt successful call center strategies that build confidence and improve every customer interaction.

Today’s managers must also be tech-savvy operators, leveraging tools like CRMs, AI agents, and workforce management systems to streamline workflows and scale customer support without sacrificing quality.

Lastly, a great manager is a customer advocate, aligning team performance with broader service goals—a defining trait of contact center management excellence.

The 9 effective call center strategies recap

Check out these call center strategies below:

  1. Streamline your current system.
  2. Boost agent productivity and efficiency.
  3. Drive down costs.
  4. Manage seasonal spikes and fluctuating demands.
  5. Remove friction.
  6. Improve the quality of your conversations with rich messaging.
  7. Engage more qualified leads.
  8. Increase conversions.
  9. Increase customer satisfaction.

1. Streamline your current system.

How do you currently connect with your customers? Fielding phone calls, emails, and the occasional DMs can leave communications scattered and your systems fragmented.

Here’s what can happen if you don’t have a single, consolidated platform:

  • Customer conversations can slip through the cracks.
  • Your team wastes time switching between apps, programs, and windows.
  • Disparate technology becomes outdated and overpriced.
  • With no support for asynchronous communication, conversations can only happen one at a time.
  • Measuring performance requires pulling metrics from multiple sources, a time-consuming and arduous process.

Quiq lets your agents connect with customers across various channels in a single platform. You’ll improve your contact center operational efficiency with conversations, survey results, and performance data all in one easy-to-use interface.

2. Boost agent productivity and efficiency.

How do your customer service agents go about their day? Are they handling one call at a time? Reinventing the wheel with every new conversation? Switching between apps and email, and phone systems?

Outdated technology (or a complete lack of it) makes handling customer conversations inherently more difficult. Switching to a messaging-first strategy with Quiq increases the speed with which agents can tackle customer conversations.

Switching to asynchronous messaging (that is, messaging that doesn’t require both parties to be present at the same time) enables agents to handle 6–8 conversations at once. Beyond conversation management, Quiq helps optimize agent performance with AI-enhanced tools like bots, snippets, sentiment analysis, and more.

3. Drive down costs.

It’s time to stop looking at your contact center as a black hole for your profits. At the most basic level, your customer service team’s performance is measured by how many people they can serve in a period of time, which means time is money.

The longer it takes your agents to solve problems, whether they’re searching for the answer, escalating to a higher customer service level, or taking multiple conversations to find a solution, the more it impacts your bottom line.

Even simple questions, like “Where’s my order?” inquiries, needlessly slow down your contact center. Managing your contact center’s operations is overwhelming, to say the least.

Need a Quiq solution? We have many. Let’s start with conversation queuing. Figuring out a customer’s problem and getting to the right person or department eats away at time that could be spent finding a solution. Quiq routes conversations to the right person, significantly reducing resolution times. Agents can also seamlessly loop in other departments or a manager to solve a problem quickly.

Beyond improving your contact center strategies and operations, messaging is 3x less expensive than the phone.

4. Manage seasonal spikes and fluctuating demands.

All contact centers face the eternal hiring/firing merry-go-round struggle. You probably get busy around the holidays and slow down in January. Or maybe September is your most active season, and your team shrinks through the rest of the year. While you can’t control when you’re busy and when you’re slow, you can control how you respond to those fluctuations.

Manage seasonal spikes by creating your own AI agent using Quiq’s AI engine. Work with our team to design bot conversations that use Natural Language Processing (NPL) to assist customers with simple questions. AI agents can also improve agent resolution times by collecting customer information upfront to speed up conversations.

Daily Harvest’s AI agent, Sage, was able to contain 60% of conversations, which means their human agents saw a vast reduction in call volume. Perfect for managing the holiday rush.

5. Remove friction.

How hard is it for your customers to contact your help center? Do they have to fill out a web form, wait for an email, and set up a phone call? Is there a number in fine print in the depths of your FAQ page? Some companies make it difficult for customers to interact with their team, hoping that they’ll spend less money if there are fewer calls and emails. But engaging with customers can improve company perception, boost sales, and deepen customer loyalty.

That’s why Quiq makes it easy for your team and customers to connect. From live chat to SMS/text and Google Business Messaging to WhatsApp, customers can connect with your team on their preferred channel.

6. Improve the quality of your conversations with rich messaging.

Email and phone conversations are, in a word, boring. Whether you’re an e-commerce company selling products or a service provider helping customers troubleshoot problems with their latest device, words aren’t always enough. That’s why Quiq offers rich messaging.

What is rich messaging? It’s an advanced form of text messaging that includes multimedia, like GIFs, high-resolution photos, or video. It also includes interactive tools, like appointment scheduling, transaction processing, and more.

You can use rich messaging to give customers a better service experience. Whether sending them product recommendations or a video walkthrough, they’ll get a fully immersed experience.

7. Engage more qualified leads.

Do leads die in your contact center? Let’s face it: your contact center isn’t the place to handle high-value leads. Yet when warm leads find themselves there, you need a way to track, qualify, and engage them.

Here’s where AI agents can help with marketing. Quiq’s AI agents can help you identify qualified leads by engaging with your prospect and collecting information before it ever gets to your sales team.

A great example we’ve seen is from General Assembly. With the Quiq team by their side, they created an AI agent that helped administer a quiz and captured and nurtured leads interested in specific courses. This helped them strengthen the quality of their leads and achieve a 26% conversion rate, which leads us to our next factor for an effective call center strategy.

8. Increase conversions.

If you haven’t stopped viewing your call center as a cost center, this next topic should change your mind. While many contact center strategies focus on customer service, which can lean heavily toward complaints and post-purchase problems, there’s also tons of profit potential via effective contact call center strategies.

Adding messaging to your contact center opens up more opportunities to engage with your customers across the web. Live chat is a great way to talk to your customers at key points in the buyers’ journey. Using an AI agent to assist shoppers in navigating your website makes shoppers 3x more likely to convert to a sale than unassisted visitors.

Combining AI and human agents with Quiq’s conversational platform gives your customers the best experience possible without adding to your contact center’s workload—and it can lead to an 85% reduction in abandoned shopping carts. Plus, Quiq integrates with your ERP system so customer data is always at your team’s fingertips.

9. Increase customer satisfaction.

Customer satisfaction is likely your call center’s #1 goal. Outdated phone systems and substandard technology aren’t the best solution to improve call center agent performance.

Quiq empowers agents to be more efficient, which reduces your customers’ wait time and helps ensure customers get the best service possible. Quiq customers often increase their customer satisfaction ratings by about 15 points.

And the best way to increase your ratings? With regular, in-context surveys. Our agentic platform helps you and your agents get instant customer feedback. Customers can seamlessly respond to surveys right from within the channel they used to connect with your customer service.

Give contact center clutter a Quiq goodbye with effective call center strategies.

There’s no place in an efficient business for a cluttered contact center. Outdated systems, slow processes, and a lack of support can overwhelm your agents and keep them from performing their best for your customers.

Now that you’re equipped with ways to improve call center efficiency, it’s time to see it in action. Quiq’s Agentic AI Platform empowers your team to work more efficiently and create happier customers.

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