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Tag: contact center

Real Time Customer Support: 2026 Guide for Enterprise Brands

Posted on Lauren Winder

Key Takeaways

  • Real time customer support directly drives higher customer satisfaction by meeting the modern expectation of instant responses — research shows that 76% of customers expect to engage with someone the moment they reach out.
  • AI-powered systems and human agents working together create the most effective support strategy, allowing routine inquiries to be automated while freeing support agents to focus on more complex tasks that require empathy.
  • Customer data and customer feedback gathered during service interactions deliver valuable real time insights into customer behavior, helping businesses provide personalized experiences and continuously refine processes.
  • Measuring success through KPIs like response times, sentiment scores, and satisfaction ratings enables continuous improvement and keeps your strategy aligned with evolving customer needs.

Why real time customer support is no longer optional

Customer expectations have permanently shifted. The same people who expect same-day delivery and on-demand streaming now bring that mindset to customer service — they want a response right away, not a three-day email chain. Real time customer support has moved from competitive differentiator to table stakes for any business serious about growth and retaining customers.

Real time support means any customer interaction where help is delivered immediately — through live chat, phone support, social media platforms, video support, or AI-powered messaging.

Transform your real-time phone support by moving from IVR to voice AI. Learn more >

Whether a customer is wrestling with a billing discrepancy or needs guidance before completing a purchase, the ability to assist in that exact moment is what separates businesses that delight customers from those that frustrate them.

Businesses that treat real time customer service as a cost center rather than a growth driver consistently underinvest in the technology and staffing required to meet modern expectations — and it shows in their churn rates.

Forward-thinking enterprises, by contrast, recognize that reducing back and forth messages and solving customer issues on first contact is one of the most powerful levers for increasing customer satisfaction and long-term revenue.

Real time customer support and customer satisfaction: The direct connection

There is a well-documented relationship between response speed and customer satisfaction. Every additional minute a customer waits increases frustration and erodes brand confidence. The data is clear: 76% of customers expect to engage with a representative immediately upon first contact, and those expectations intensify each year.

When they aren’t met, customers leave — 61% will defect to a competitor after just one bad experience, and 76% are gone after two.

Real time support drives satisfaction in several ways: it eliminates wait anxiety, minimizes the need for back and forth communication across multiple sessions, and allows support agents to apply empathy in the moment — de-escalating tension and turning a frustrated customer into a satisfied one.

Consistent support across every touchpoint further reinforces trust and is a foundation for building loyal customers who drive repeat purchases.

Elevating the customer experience through personalized support

Customer experience encompasses every touchpoint across the customer journey, and real time service sits at its heart. When a customer receives an immediate, accurate, and thoughtful response, it shapes how they feel about your brand.

Personalized experiences are central to this. Customers don’t want to feel like ticket numbers — they want to feel recognized. When agents have access to relevant customer data (purchase history, previous interactions, preferred channels), they can tailor responses in ways that genuinely resonate rather than offering generic scripted replies. That emotional connection is the foundation of customer loyalty, turning one-time buyers into advocates.

It’s no coincidence that 90% of consumers say they’ll spend more with companies that personalize the service experience.

Social media support has added a new visibility layer: a fast, genuine public response on social media platforms doesn’t just retain the individual customer — it signals your commitment to service quality to everyone watching. Empower customers to reach out on their preferred platform and ensure your support team is equipped to provide personalized support wherever those conversations happen.

Using customer feedback and customer data to drive continuous improvement

One of the most underappreciated advantages of real time support is valuable insights it generates. Every live interaction is a direct window into customer needs and pain points that no quarterly survey can replicate.

Customer data collected during interactions — the language customers use, issues that surface repeatedly, questions revealing gaps in documentation — is raw material for meaningful improvement.

Businesses that analyze this systematically can understand behavior more deeply, identify emerging problems before they become widespread, and optimize processes proactively. Real time insights derived from live conversations give operations leaders the ability to course-correct quickly rather than waiting weeks for survey data to arrive.

AI-powered sentiment tracking adds another dimension, flagging emotionally charged conversations so supervisors can intervene before things escalate. Aggregated over time, sentiment data tells a detailed story about how customers feel about specific products, policies, or experiences.

Closing the feedback loop is equally important: customers who see their input shapes your business become more engaged and more honest in future interactions.

Implementing AI in customer support without losing the human touch

AI tools built on natural language processing and machine learning can now handle a substantial share of repetitive customer questions automatically — answering common questions, routing conversations intelligently, and providing instant responses around the clock.

The efficiency gains are significant: by automating routine work, businesses reduce operational costs, compress time to response, and free agents for more difficult issues requiring judgment and empathy. In fact, 90% of CX leaders report positive ROI from AI customer service tools.

That said, AI tools demand thoughtful design and human oversight. They excel at speed, consistency, and processing data at scale — but lack the nuanced understanding that defines excellent human service. This is where seamless escalation paths are essential.

The most effective strategies deploy AI and humans in genuine partnership: AI handles high-volume straightforward customer inquiries while humans manage more complex tasks and emotionally sensitive conversations.

Human agents, in turn, are empowered with real time AI assistance — suggested responses, relevant data, and context that helps them resolve issues faster. 73% of agents believe an AI copilot would help them do their jobs better.

Self service is another critical pillar of a scalable real time customer support strategy. Well-designed self service tools — AI Agents, dynamic knowledge bases, and interactive FAQs — empower customers to resolve straightforward issues independently, without ever needing to contact your support team. This reduces volume for agents and delivers the immediate response customers expect, around the clock. When self service and live support are well-integrated, the result is a faster, lower-cost operation that still delivers a high-quality customer experience.

Modern interactive voice response tools have also evolved significantly, using natural language processing to understand customer intent more accurately and route callers more intelligently.

Addressing customer needs across every channel

Today’s customers move fluidly between channels — starting on social media platforms, following up via live chat, and expecting any agent they reach to have full context. 70% of customers expect any employee they engage with to know their situation completely.

A strong omnichannel approach ensures that wherever a customer reaches out — web chat, phone, social media, or video — they receive consistent help with continuity of context. Customers should never have to repeat themselves.

Understanding channel preferences is what makes this possible. Younger customers may expect near-instant chat responses, while others prefer phone for complex issues. A data-informed strategy maps these preferences and ensures the right resources are in place.

Social media deserves particular strategic attention. Customers increasingly use social media platforms not just to ask questions but to air grievances publicly, share positive experiences, and seek help in real time. A dedicated social media support capability — staffed with trained agents and supported by AI tools for monitoring and routing — is now a non-negotiable component of enterprise customer support.

Video support deserves particular attention for complex products or high-stakes interactions. For technical troubleshooting, product walkthroughs, or emotionally sensitive conversations, video can dramatically improve FCR rates.

Higher customer satisfaction through emotional intelligence and customer sentiment

Speed is necessary but not sufficient. Customers who receive fast responses that feel robotic or dismissive are not satisfied — they’re customers who got their issue addressed but left feeling undervalued. Emotional intelligence (EQ) remains indispensable in real time customer service even as AI handles growing transactional volume.

EQ in support means reading a customer’s emotional state and responding with genuine empathy — acknowledging inconvenience before jumping to solutions, and knowing when to slow down and prioritize the human dimension over closing the ticket.

Sentiment data helps surface these moments at scale.

When AI detects an emotionally charged conversation, teams can prioritize human involvement rather than allowing automation to handle something requiring a personal touch. Customers are 2.4 times more likely to stick with a brand when their problems are solved quickly — a reminder that the combination of speed, accuracy, and empathy converts satisfied customers into loyal customers who drive repeat orders.

Measuring operational efficiency and success

From an operational standpoint, real time customer support is about building an operation that scales without proportionally growing operational costs. When AI handles repetitive customer inquiries efficiently and first contact resolution (FCR) rates are high, support costs remain manageable even as volume increases. This is how customer support evolves from cost center to strategic asset.

Key performance indicators should include response times, FCR rates, customer satisfaction scores, sentiment trends, and operational metrics like cost per interaction and agent utilization. Tracking these consistently creates the foundation for continuous improvement in operational efficiency.

Real time interactions also generate rich data about product and service quality that is valuable far beyond support.

When customers repeatedly contact your team about the same customer issues, something upstream — in product design, onboarding, or documentation — needs attention. A well-maintained knowledge base, kept current with questions that arise in live interactions, allows customers to empower themselves through self service without contacting support at all.

Building a real time support strategy that scales

A few principles are foundational:

Start by mapping your customer journey and identifying where immediate assistance is most critical — where delay is most likely to cause frustration, abandonment, or churn. These high-stakes moments are the highest priority for investment.

Design deliberately for the blend of AI and human involvement your volume and complexity require. AI tools should handle the majority of straightforward interactions, with clear escalation paths and robust human oversight for anything outside their scope. Equip your agents with real time AI assistance, comprehensive data, and a robust knowledge base so they can resolve more complex queries efficiently and with confidence.

Instrument your operation for measurement from day one. Define KPIs, build in data collection, and establish regular review cycles. Real time customer service requires ongoing adaptation as customer needs continue to evolve.

Finally, build a support culture that treats every interaction as an opportunity to create a genuinely positive experience. The best care teams are efficient and empathetic, curious about the root causes of consistent issues, and invested in providing instant assistance that makes a real difference. That culture — backed by the right technology and processes — is what consistently delivers the service quality that drives lasting business growth, retaining customers and building lifetime customers over time.

Frequently Asked Questions (FAQs)

What is real time customer support and how does it differ from traditional support?

Real time support refers to customer service delivered immediately — through live chat, phone, social media, video, or AI-powered messaging — rather than channels like email where responses may take hours or days. The key distinction is responsiveness: real time interactions meet customers in the moment of need, resolving issues in a single session.

What role does AI play in real time customer support?

AI tools allow businesses to handle high volumes of routine customer inquiries automatically — providing instant 24/7 responses without human involvement for straightforward questions.

The most effective approach pairs AI tools with a human in the loop: AI handles routine work, while human agents focus on more complex queries and emotionally nuanced conversations. This balance maximizes efficiency while preserving the customer experience quality that drives customer loyalty.

How does real time customer support contribute to customer loyalty and repeat purchases?

Retaining customers is far more cost-effective than acquiring new ones, and real time customer service is one of the most direct drivers of customer loyalty. When customers receive an instant response that genuinely resolves their issue — without excessive back and forth or the need to repeat themselves across channels — they form a positive association with your brand.

Personalized experiences built on accurate customer data deepen that connection further. Loyal customers not only drive repeat purchases but also become advocates who reduce your acquisition costs over time.

What KPIs should I track to measure real time support performance?

The most important KPIs for real time customer support include first contact resolution (FCR) rate, average response time, customer satisfaction score (CSAT), net promoter score (NPS), customer sentiment trends, cost per interaction, and agent utilization rate. Together, these metrics give a complete picture of both operational efficiency and the quality of interactions, enabling your support team to continuously improve.

How can I use real time customer support to understand customer behavior?

Every live service interaction is a rich data source. The questions customers ask, the issues they escalate, and the language they use all reveal patterns that help you understand your customers’ behavior at a granular level.

AI-powered analytics applied to this data surface insights your support team can act on immediately — whether that means updating a knowledge base, flagging a product defect, or adjusting onboarding materials. Businesses that systematically mine customer feedback from live interactions gain a significant competitive advantage in product development and customer experience design.

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.

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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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.

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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The 12 Most Asked Questions About AI

Posted on Lauren Winder

Key Takeaways

  • Agentic AI is the ability of machines to perform tasks requiring human intelligence, such as learning, decision-making, and problem-solving.
  • Main branches of AI include Machine Learning, NLP, Computer Vision, Robotics, and Expert Systems, each unlocking different applications.
  • Agentic AI is reshaping industries from healthcare and finance to contact centers by boosting efficiency and personalization.
  • Ethical challenges like bias, transparency, and privacy remain central concerns as AI expands.
  • Economic and social impacts include job displacement and inequality, but current evidence shows AI often enhances rather than eliminates roles.
  • Risks range from misinformation and deepfakes to speculative existential risks tied to future AGI development.
  • The future of AI raises open questions around control, alignment with human values, and specialized capabilities emerging from new platforms.

The term “artificial intelligence” was coined at the famous Dartmouth Conference in 1956, put on by luminaries like John McCarthy, Marvin Minsky, and Claude Shannon, among others.

These organizers wanted to create machines that “use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.” They went on to claim that “…a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer.”

Half a century later, it’s fair to say that this has not come to pass; brilliant as they were, it would seem as though McCarthy et al. underestimated how difficult it would be to scale the heights of the human intellect.

Nevertheless, remarkable advances have been made over the past decade, so much so that they’ve ignited a firestorm of controversy around this technology. People are questioning the ways in which it can be used negatively, and whether it might ultimately pose an extinction risk to humanity; they’re probing fundamental issues around whether machines can be conscious, exercise free will, and think in the way a living organism does; they’re rethinking the basis of intelligence, concept formation, and what it means to be human.

These are deep waters to be sure, and we’re not going to swim them all today. But as contact center managers and others begin the process of thinking about using AI, it’s worth being at least aware of what this broader conversation is about. It will likely come up in meetings, in the press, or in Slack channels in exchanges between employees.

And that’s the subject of our piece today. We’re going to start by asking what artificial intelligence is and how it’s being used, before turning to address some of the concerns about its long-term potential. Our goal is not to answer all these concerns, but to make you aware of what people are thinking and saying.

What is Artificial Intelligence?

Artificial intelligence is famous for having many, many definitions. There are those, for example, who believe that in order to be intelligent, computers must think like humans, and those who reply that we didn’t make airplanes by designing them to fly like birds.

For our part, we prefer to sidestep the question somewhat by utilizing the approach taken in one of the leading textbooks in the field, Stuart Russell and Peter Norvig’s “Artificial Intelligence: A Modern Approach”.

They propose a multi-part system for thinking about different approaches to AI. One set of approaches is human-centric and focuses on designing machines that either think like humans – i.e., engage in analogous cognitive and perceptual processes – or act like humans – i.e., by behaving in a way that’s indistinguishable from a human, regardless of what’s happening under the hood (think: the Turing Test).

The other set of approaches is ideal-centric and focuses on designing machines that either think in a totally rational way – conformant with the rules of Bayesian epistemology, for example – or behave in a totally rational way – utilizing logic and probability, but also acting instinctively to remove itself from danger, without going through any lengthy calculations.

From a practical standpoint, AI can also be defined as the ability of machines to perform tasks that normally require human intelligence, such as learning, problem-solving, and decision-making. AI systems learn from data to identify patterns and make predictions.

Main branches of AI include:

  • Agentic AI: refers to artificial intelligence systems capable of taking autonomous, goal-directed actions rather than simply responding to inputs.
  • Machine Learning (ML): algorithms that improve performance over time with data.
  • Natural Language Processing (NLP): enables human-computer interaction through text and speech.
  • Computer Vision: powers machines to interpret and analyze visual data.
  • Robotics: supports autonomous systems that perform tasks in the physical world.
  • Expert Systems: encode domain-specific knowledge for decision-making.

What we have here, in other words, is a framework. Using the framework not only gives us a way to think about almost every AI project in existence, it also saves us from needing to spend all weekend coming up with a clever new definition of AI.

Joking aside, we think this is a productive lens through which to view the whole debate, and we offer it here for your information.

How Does Agentic AI Differ From Traditional AI?

Traditional AI systems were designed to perform specific, rule-based tasks like predicting loan defaults or detecting spam emails. They rely on structured data and follow defined parameters to reach a decision.

Agentic AI, however, represents a new frontier. Instead of merely analyzing data, it creates new data, producing text, code, images, or audio that mimic human expression. These models learn from massive datasets to understand structure, style, and context, allowing them to generate entirely original outputs.

This distinction matters because agentic AI expands the role of machines from assistive tools to creative collaborators.

  • In contact centers, it drafts responses, summarizes conversations, and adapts to tone.

  • In marketing, it generates campaigns and copy tailored to audiences.

  • In software, it writes or optimizes code in seconds.

Agentic AI doesn’t replace human creativity; it scales it. It can handle repetitive cognitive work so humans can focus on judgment, empathy, and innovation.

What Are the Limitations of AI?

AI’s potential is vast, but it has clear and important limitations.

Despite its sophistication, AI still struggles with context, common sense, and abstract reasoning. A model can produce coherent text or make accurate predictions, but it doesn’t understand the world the way humans do.

Key Limitations Include:

  • Lack of true comprehension: AI interprets patterns, not meaning.
  • Dependence on data quality: Poor or biased data leads to flawed outputs.
  • Limited adaptability: Most models perform poorly outside their training domain.
  • Ethical blind spots: AI has no intrinsic moral compass or emotional intelligence.

For contact centers and other industries, this means AI should be used as a co-pilot, not a substitute for human decision-making. The best outcomes come from combining machine efficiency with human empathy and oversight.

Who Is Accountable When AI Makes a Mistake?

Accountability is one of the thorniest questions in AI ethics. If an algorithm makes a wrong decision denying a loan, misclassifying a medical image, or providing biased recommendations, who bears the blame?

Is it the developer who built the system, the organization that deployed it, or the AI itself?

At present, humans remain fully accountable. AI is a tool, not an entity capable of responsibility. That’s why governance and transparency are critical. Companies deploying AI should: Maintain human oversight in high-stakes decisions. Establish audit trails that document how outputs are produced. Implement explainability features to clarify reasoning. Define escalation protocols when AI outputs seem unreliable.

Ultimately, the ethical principle is simple: AI assists, but humans decide. As AI becomes more capable, accountability frameworks must evolve in parallel to ensure technology remains under human control.

How Can We Prevent AI Bias?

Bias is one of AI’s most persistent and challenging problems. When AI systems are trained on biased or incomplete data, they can unintentionally replicate or even amplify human prejudice.

In sectors like hiring, law enforcement, or lending, these biases can have real-world consequences. For contact centers, bias can subtly affect how language models interpret tone or prioritize customer queries.

Strategies to Reduce Bias:

  1. Use diverse, representative training data. Ensure datasets reflect varied demographics, dialects, and contexts.
  2. Conduct regular bias audits. Test models under different conditions and measure fairness outcomes.
  3. Include human review. Use human judgment in quality assurance loops to catch biased outputs.
  4. Apply explainability tools. Tools like SHAP and LIME help visualize how models make decisions.
  5. Adopt ethical AI frameworks. Follow established standards like NIST’s AI Risk Management Framework or ISO/IEC 42001.

Bias prevention isn’t about perfection; it’s about constant vigilance. AI must evolve alongside our understanding of fairness and equity.

What is Artificial Intelligence Good For?

Given all the hype around ChatGPT, this might seem like a quaint question. But not that long ago, many people were asking it in earnest. The basic insights upon which large language models like ChatGPT are built go back to the 1960s, but it wasn’t until 1) vast quantities of data became available, and 2) compute cycles became extremely cheap that much of its potential was realized.

Today, large language models are changing (or poised to change) many different fields. Our audience is focused on contact centers, so that’s what we’ll focus on as well.

There are a number of ways that agentic AI is changing contact centers. Because of its remarkable abilities with natural language, it’s able to dramatically speed up agents in their work by answering questions and formatting replies. These same abilities allow it to handle other important tasks, like summarizing articles and documentation and parsing the sentiment in customer messages to enable semi-automated prioritization of their requests.

Though we’re still in the early days, the evidence so far suggests that large language models like Quiq’s agentic ai platform will do a lot to increase the efficiency of contact center agents.

Beyond contact centers, AI is transforming healthcare (diagnostics, drug discovery), finance (fraud detection, algorithmic trading), transportation (autonomous vehicles), and education (personalized learning). Its flexibility is why AI is considered one of the most impactful technologies across industries.

Will AI be Dangerous?

One thing that’s burst into public imagination recently has been the debate around the risks of artificial intelligence, which fall into two broad categories.

The first category is what we’ll call “social and political risks”. These are the risks that large language models will make it dramatically easier to manufacture propaganda at scale, and perhaps tailor it to specific audiences or even individuals. When combined with the astonishing progress in deepfakes, it’s not hard to see how there could be real issues in the future. Most people (including us) are poorly equipped to figure out when a video is fake, and if the underlying technology gets much better, there may come a day when it’s simply not possible to tell.

Political operatives are already quite skilled at cherry-picking quotes and stitching together soundbites into a damning portrait of a candidate – imagine what’ll be possible when they don’t even need to bother.

But the bigger (and more speculative) danger is around really advanced artificial intelligence. Because this case is harder to understand, it’s what we’ll spend the rest of this section on.

Artificial Superintelligence and Existential Risk

As we understand it, the basic case for existential risk from artificial intelligence goes something like this:

“Someday soon, humanity will build or grow an artificial general intelligence (AGI). It’s going to want things, which means that it’ll be steering the world in the direction of achieving its ambitions. Because it’s smart, it’ll do this quite well, and because it’s a very alien sort of mind, it’ll be making moves that are hard for us to predict or understand. Unless we solve some major technological problems around how to design reward structures and goal architectures in advanced agentive systems, what it wants will almost certainly conflict in subtle ways with what we want. If all this happens, we’ll find ourselves in conflict with an opponent unlike any we’ve faced in the history of our species, and it’s not at all clear we’ll prevail.”

This is heady stuff, so let’s unpack it bit by bit. The opening sentence, “…humanity will build or grow an artificial general intelligence”, was chosen carefully. If you understand how LLMs and deep learning systems are trained, the process is more akin to growing an enormous structure than it is to building one.

This has a few implications. First, their internal workings remain almost completely inscrutable. Though researchers in fields like mechanistic interpretability are going a long way toward unpacking how neural networks function, the truth is, we’ve still got a long way to go.

What this means is that we’ve built one of the most powerful artifacts in the history of Earth, and no one is really sure how it works.

Another implication is that no one has any good theoretical or empirical reason to bound the capabilities and behavior of future systems. The leap from GPT-2 to GPT-3.5 was astonishing, as was the leap from GPT-3.5 to GPT-4. The basic approach so far has been to throw more data and more compute at the training algorithms; it’s possible that this paradigm will begin to level off soon, but it’s also possible that it won’t. If the gap between GPT-4 and GPT-5 is as big as the gap between GPT-3 and GPT-4, and if the gap between GPT-6 and GPT-5 is just as big, it’s not hard to see that the consequences could be staggering.

As things stand, it’s anyone’s guess how this will play out. But that’s not necessarily a comforting thought.

Next, let’s talk about pointing a system at a task. Does ChatGPT want anything? The short answer is: as far as we can tell, it doesn’t. ChatGPT isn’t an agent, in the sense that it’s trying to achieve something in the world, but work into agentive systems is ongoing. Remember that 10 years ago most neural networks were basically toys, and today we have ChatGPT. If breakthroughs in agency follow a similar pace (and they very well may not), then we could have systems able to pursue open-ended courses of action in the real world in relatively short order.

Another sobering possibility is that this capacity will simply emerge from the training of huge deep learning systems. This is, after all, the way human agency emerged in the first place. Through the relentless grind of natural selection, our ancestors went from chipping flint arrowheads to industrialization, quantum computing, and synthetic biology.

To be clear, this is far from a foregone conclusion, as the algorithms used to train large language models are quite different from natural selection. Still, we want to relay this line of argumentation, because it comes up a lot in these discussions.

Finally, we’ll address one more important claim, “…what it wants will almost certainly conflict in subtle ways with what we want.” Why do we think this is true? Aren’t these systems that we design and, if so, can’t we just tell it what we want it to go after?

Unfortunately, it’s not so simple. Whether you’re talking about reinforcement learning or something more exotic like evolutionary programming, the simple fact is that our algorithms often find remarkable mechanisms by which to maximize their reward in ways we didn’t intend.

There are thousands of examples of this (ask any reinforcement-learning engineer you know), but a famous one comes from the classic Coast Runners video game. The engineers who built the system tried to set up the algorithm’s rewards so that it would try to race a boat as well as it could. What it actually did, however, was maximize its reward by spinning in a circle to hit a set of green blocks over and over again.

biggest questions about AI

Now, this may seem almost silly – do we really have anything to fear from an algorithm too stupid to understand the concept of a “race”?

But this would be missing the thrust of the argument. If you had access to a superintelligent AI and asked it to maximize human happiness, what happened next would depend almost entirely on what it understood “happiness” to mean.

If it were properly designed, it would work in tandem with us to usher in a utopia. But if it understood it to mean “maximize the number of smiles”, it would be incentivized to start paying people to get plastic surgery to fix their faces into permanent smiles (or something similarly unintuitive).

Does AI Pose an Existential Risk?

Above, we’ve briefly outlined the case that sufficiently advanced AI could pose a serious risk to humanity by being powerful, unpredictable, and prone to pursuing goals that weren’t-quite-what-we-meant.

So, does this hold water? Honestly, it’s too early to tell. The argument has hundreds of moving parts, some well-established and others much more speculative. Our purpose here isn’t to come down on one side of this debate or the other, but to let you know (in broad strokes) what people are saying.

At any rate, we are confident that the current version of ChatGPT doesn’t pose any existential risks. On the contrary, it could end up being one of the greatest advancements in productivity ever seen in contact centers. And that’s what we’d like to discuss in the next section.

What is the Biggest Concern with AI?

Ethical Challenges 

While AI’s potential is vast, so are the concerns surrounding its rapid advancement. One of the most pressing concerns is the ethical challenge of transparency. AI models often operate as “black boxes,” making decisions without clear explanations. This lack of visibility raises concerns about hidden biases that can lead to unfair or even discriminatory outcomes, especially in areas like hiring, lending, and law enforcement.

Economic Ramifications

Beyond ethics, AI’s economic impact is another major concern: automation is reshaping entire industries. While it creates new opportunities, it also threatens traditional jobs, particularly in sectors reliant on repetitive tasks. This shift could complicate wealth disparities, favoring companies and individuals who own or develop AI technologies while leaving others behind.

The bigger conversation is whether AI will replace humans or serve as a “copilot.” Current evidence suggests AI is enhancing productivity by supporting humans rather than replacing them outright.

Social Impacts

On a broader scale, AI’s social implications are hard to ignore. The displacement of jobs, increasing socio-economic inequality, and reduced human oversight in decision-making all point to a future where AI plays an even greater role in shaping society. This raises questions about the balance between automation and human oversight.

Privacy and data security are also critical concerns, since AI requires massive datasets to function. Without safeguards, personal data could be misused or breached.

Will AI Take All the Jobs?

The concern that someday a new technology will render human labor obsolete is hardly new. It was heard when mechanized weaving machines were created, when computers emerged, when the internet emerged, and when ChatGPT came onto the scene.

We’re not economists and we’re not qualified to take a definitive stand, but we do have some early evidence that is showing that large language models are not only not resulting in layoffs, they’re making agents much more productive.

Erik Brynjolfsson, Danielle Li, and Lindsey R. Raymond, three MIT economists, looked at the ways in which generative AI was being used in a large contact center. They found that it was actually doing a good job of internalizing the ways in which senior agents were doing their jobs, which allowed more junior agents to climb the learning curve more quickly and perform at a much higher level. This had the knock-on effect of making them feel less stressed about their work, thus reducing turnover.

Now, this doesn’t rule out the possibility that GPT-10 will be the big job killer. But so far, large language models are shaping up to be like every prior technological advance, i.e., increasing employment rather than reducing it.

AI is more likely to shift job responsibilities than eliminate them entirely. By automating repetitive tasks, it frees workers to focus on higher-value skills like problem-solving, empathy, and creativity. In contact centers, for example, AI helps agents train faster, reduce stress, and improve retention.

What is the Future of AI?

The rise of AI is raising stock valuations, raising deep philosophical questions, and raising expectations and fears about the future. We don’t know for sure how all this will play out, but we do know contact centers, and we know that they stand to benefit greatly from the current iteration of large language models.

These tools are helping agents answer more queries per hour, do so more thoroughly, and make for a better customer experience in the process.

If you want to get in on the action, set up a demo of our technology today.

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Frequently Asked Questions (FAQs)

What is artificial intelligence in simple terms?

AI is when machines can perform tasks that normally require human intelligence, like learning, analyzing data, making predictions, or interacting with people.

What are the main types of AI?

The core branches include Machine Learning, Natural Language Processing, Computer Vision, Robotics, and Expert Systems. Each serves a different purpose.

How does AI actually work?

AI systems are trained on data, which they use to detect patterns and make predictions. Machine Learning enables them to improve over time as they’re exposed to more data.

What are the biggest risks of AI today?

Key concerns include bias in decision-making, lack of transparency (“black box” models), privacy issues, misinformation and deepfakes, and potential job displacement.

Will AI take all the jobs?

Most evidence shows AI acts as a “copilot” that boosts productivity rather than replacing workers outright. It automates repetitive tasks while humans focus on higher-value work.

What’s the future of AI?

People are asking how powerful AI will become, whether it can be controlled safely, and how to align it with human values.

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.

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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Business Messaging: What it Means for Your Business

Posted on Max Fortis

What is business messaging, you ask? Oh, it’s only a way to get better customer engagement, attract more customers, and deliver a better customer experience. That seems like a tall order for something as simple and commonplace as messaging, right? The truth is, the simplicity and reach of business messaging is what makes it so powerful for your business and preferred by your customers.

What is Business Messaging?

Business messaging is a set of channels over which companies and consumers can communicate with each other. The most common business messaging channel is SMS or text messaging. We’ve all had experiences with shipping notifications, marketing offers, promotional campaigns, and appointment reminders. These are the kinds of messages we typically associate with business messaging.

But business messaging isn’t just one-way, and it isn’t just SMS/texting. Business messaging can happen on any digital channel where your customers already spend their time and it’s expected that dialogue can flow in both directions.  Here are a few scenarios that happen all the time:

  • A home security subscriber who needs help setting up their new video camera.
  • A shopper on your website who needs help finding a product and reaches out via web chat for help
  • Direct messages exchanged over social platforms like Facebook and X (Twitter) to provide one-to-one customer service
  • A retailer proactively communicating shipping and delivery information to consumers to help prevent an inbound phone call

Business messaging delivers the ease and convenience consumers have come to expect when they engage with family and friends in pre-sales and post-sales interactions with companies. In fact, 66% of consumers rank messaging as their preferred channel for contacting a company.

What Messaging Means to Your Customers

Your customers want to message you.  Consumers are looking for a company to:

  • Meet them where they already are – on mobile, social, and on the web
  • Proactively reach out to them with relevant products and services
  • Make it easy to do business with you

CONVENIENCE: Messaging lets customers reach out via SMS, Facebook, or live chat, and respond on their own time instead of stopping to call. With messaging, they can respond and engage in 5 seconds, 5 minutes, or 5 days.

EASE:  Customers keep their mobile device within an arm’s reach at all times. Business messaging makes it easy for customers to shoot off a message whenever they need and then get on with their lives. They don’t have to wait until they are in a quiet place to call or vigilantly watch their email for a response.

FLEXIBILITY: Messaging means flexibility for your customers. Customers have the real-time response of a phone call with the ease of reference that an email provides. That flexibility around their busy lives is more than a welcome mat. It’s more like the red carpet, and it’s what differentiates companies among competitors and turns prospects into customers.

What Messaging Means to Your Revenue Growth

Increasing revenue is the number one thing that companies focus on. Every strategy and tactic is a means to that end. Often, companies will consider introducing a new product line or service, or increasing prices as a way to bolster revenue.

New products take time and money to develop. Raising prices risks losing customers to competitors. There are people ready to buy what you already offer, and existing customers who can be encouraged to return. That’s why companies turn to customer experience, where messaging makes the biggest impact

Messaging makes it easy for consumers to engage with your company when, where, and how they prefer. Prospective buyers can have questions answered with ease, speed, and convenience. Returning customers get timely service and support at their moment of need, which means they’ll be back for more and will tell others how great you are.

Consider these examples and how your business can help customers move closer to purchase with business messaging:

  • Service companies win when their prospects are able to get the answers they need to make a decision on a provider. Prospects can book an appointment to receive an estimate easily with business messaging. Messaging avoids delays and missed calls that can drive consumers to take their business elsewhere.
  • Companies in the travel and hospitality industry use messaging to provide a premium experience from the very first interaction. Questions on weather conditions and cancellation policies are answered quickly so that potential guests can ease right into the booking process with peace of mind.

What Messaging Means to Your Employees

In any other day and age, allowing customers to engage with your company through so many channels would have been overwhelming. But it’s not that day, and we’re past that age. In today’s modern messaging world, Quiq makes it easy for employees to manage conversations.

In fact, Quiq Messaging can help optimize agent performance by providing advanced productivity features that improve the customer experience. With Quiq, employees are able to handle multiple messaging conversations at once, thereby increasing their efficiency and reducing the cost to serve.

There isn’t any downtime for training. Adding business messaging is a pretty flat learning curve for your employees. They are likely using messaging in their daily lives and are familiar with sending and receiving messages. The only difference is that they’ll have an easy way to manage conversations.

All messaging conversations are managed within a single, unified desktop with features that help employees prioritize conversations, monitor customer sentiment, and make every conversation more personal and effective. Employees can feel empowered to provide the best customer experience possible.

Business Messaging Means Business

Business messaging makes a significant impact in two ways to grow your business: get new customers or have your existing customers buy more.

  • Attract new customers – Make your business accessible so that it’s easy to do business with you.
  • Keep existing customers happy  – Empower your customers to get service 24/7 through business messaging. Make it easy for customers to address questions and issues that may arise after the sale, and they’ll be more likely to come back again.

The key takeaway here is that business messaging isn’t just good for your business. It’s a main ingredient in the secret sauce that can keep your business running successfully. Ready to see Quiq Messaging in action? Request a custom demo.

Enterprise AI Chatbot Solutions are Failing Businesses: Why Agentic AI is the Path Forward

Posted on Max Fortis

The integration of AI into enterprise operations is no longer a futuristic concept—it’s the present. From customer service to supply chain management, enterprises are adopting AI at an unprecedented rate, transforming workflows and outcomes.

The global AI chatbot market is expected to be worth $455 million by the end of 2027, underscoring its growing importance. But while conventional AI chatbots have proven beneficial, they are no longer enough in an era demanding higher adaptability, smarter decision-making, and process integration.

Enter agentic AI, the next leap in enterprise technology. Evolving beyond chatbots, agentic AI agents offer enterprises proactive and autonomous solutions designed to optimize operations across departments.

This blog will explore the limitations of traditional enterprise AI chatbot solutions, introduce agentic AI as a transformational catalyst, and highlight how enterprise leaders can leverage it for sustained competitive advantage.

What is an enterprise AI chatbot solution?

Enterprise AI chatbot solutions are software platforms driven by artificial intelligence, natural language processing (NLP), and machine learning (ML) to automate customer interactions and internal processes. With natural language understanding (NLU), these chatbots can interpret customer intent, offer personalized responses, and escalate complex issues to human agents.

Legacy conversational AI in enterprise AI chatbot solutions

Conversational AI in enterprise solutions represents technology that enables natural, human-like interactions between businesses and their customers through intelligent chatbots and virtual assistants. These systems combine the technologies described above—Natural Language Processing (NLP), Machine Learning, and Deep Learning—to understand, process, and respond to human language in context.

But as we will see, agentic AI takes over from conversational AI to handle complex dialogues, remember conversation history, understand user intent, and provide personalized responses across multiple channels and languages in a way that prior-gen AI could not. These solutions can integrate with existing business systems (like CRM, ERP, and knowledge bases) to automate customer service, sales support, and internal operations, while continuously learning from interactions to improve accuracy and effectiveness.

Core features of enterprise AI chatbot solutions

1. Handling high volumes of requests

Enterprise chatbots aim to manage thousands of simultaneous interactions, offering round-the-clock availability without human intervention.

2. Escalation to human agents

When complex issues arise, chatbots transfer customers to live agents without losing conversation context for continuity and smooth interactions.

3. Integration with other enterprise tools

Integrating AI chatbots with existing tech stacks improves efficiency and customer experience. By connecting with tools like CRMs, ERPs, HR systems, and helpdesk software, chatbots access data to deliver personalized, accurate responses. For instance, they can check inventory, update orders, or enable targeted upselling, streamlining operations and enhancing service quality for customers and employees.

4. Support for internal processes

Beyond customer service, chatbots help employees with onboarding, training, and data collection, making them indispensable for growing enterprises.

Benefits of enterprise AI chatbot solutions

Cost savings

Automating repetitive tasks reduces reliance on human agents, leading to savings in labor costs.

Enhanced operations

Chatbots streamline workflows, reduce wait times, and improve customer satisfaction scores.

Scalable and consistent service

Whether answering FAQs or managing complex queries, these bots offer consistent service quality at scale.

However, despite their utility, traditional enterprise AI chatbots remain reactive—responding to instructions, but unable to anticipate problems or dynamics. This is where agentic AI paves the way forward.

From chatbots to agentic AI for enterprises

Agentic AI represents an evolution in enterprise artificial intelligence. While chatbots are reactive tools limited to predefined interactions, agentic AI agents are capable of proactive decision-making and autonomous action. With capabilities rooted in real-time adaptation, agentic AI has redefined AI’s role in the enterprise landscape.

Chatbots vs. agentic AI agents

Reactive vs. proactive

Chatbots react to user queries; agentic AI anticipates needs before they are expressed. For example, instead of merely answering a customer’s inquiry about delayed shipments, agentic AI could autonomously identify delays, notify affected customers, and initiate remediation.

Static decision-making vs. dynamic learning

Where chatbots rely on static rules, agentic AI improves continuously by learning from interactions, refining its predictive capabilities.

Siloed functionality vs. cross-departmental efficiency

Traditional chatbots typically serve a single function (e.g., customer service). Agentic AI spans departments, breaking silos by automating workflows in HR, supply chains, marketing, and more.

Cost vs. ROI

Agentic AI is already providing faster time-to-value than last-gen enterprise AI chatbot solutions. While implementing agentic AI requires an initial investment in technology and training, the returns justify the expenditure. Organizations typically see ROI through reduced operational costs, increased efficiency in process completion, higher customer satisfaction scores, and improved employee productivity.

When evaluating costs, consider not just platform pricing, but also integration expenses, training requirements, and maintenance—then weigh these against projected gains in automation, reduced error rates, faster resolution times, and the ability to scale operations without proportional increases in headcount.

Practical applications of agentic AI in enterprises

1. Customer service

Agentic AI can revolutionize customer service by going beyond simply answering customer queries. Imagine an AI that not only resolves issues efficiently, but also analyzes customer sentiment, behavior, and usage patterns to predict potential churn well in advance.

By identifying dissatisfied customers, it can automatically trigger personalized retention efforts, such as offering discounts, tailored recommendations, or proactive solutions, ensuring a more seamless and satisfying customer experience while boosting loyalty.

2. Human resources

Agentic AI can significantly streamline and enhance human resources operations. For example, it can handle the initial stages of hiring by screening resumes and applications for relevant skills and experience, thereby reducing the workload of HR teams.

It can also manage interview scheduling, ensuring candidates and hiring managers are aligned with minimal manual intervention.

Once employees are onboarded, agentic AI can be used to monitor engagement and morale. By integrating these agents with dedicated employee onboarding automation tools, companies can create a frictionless first-day experience that spans HR systems and conversational interfaces.

3. Supply chain management

In the realm of supply chain management, agentic AI can help businesses maintain agility and cost-efficiency. By analyzing historical data, market trends, and real-time inputs, it can accurately anticipate demand surges and adjust inventory levels dynamically to prevent shortages or overstocking.

This is particularly valuable during peak seasons or unforeseen disruptions.

Moreover, agentic AI can optimize logistics by suggesting the most efficient routes and delivery schedules, reducing costs and improving supply chain performance. By automating these complex processes, businesses can react faster to changes in demand and ensure smoother operations.

These examples illustrate why enterprises can no longer rely solely on static chatbot solutions. Agentic AI offers dynamic, intelligent, and proactive capabilities that go beyond traditional automation, driving better outcomes across various business functions. Investing in these advanced AI solutions is becoming essential for staying competitive.

9 key features that set agentic AI apart in enterprise applications

To fully grasp agentic AI’s potential, it’s essential to understand the distinct features that differentiate it from its chatbot predecessors.

1. Contextual understanding

Agentic AI excels at maintaining context across multi-turn conversations, enabling more natural, human-like interactions compared to general chatbots, which often reset or lose track of context.

2. Proactive adaptability

Agentic AI evolves dynamically by analyzing patterns, allowing it to predict user needs and act without user prompting. For example, an agentic AI might automatically notify customers of service disruptions and provide alternatives.

3. Enhanced decision-making

Agentic AI provides real-time data-driven insights, enabling businesses to act swiftly and effectively. By analyzing patterns, it identifies opportunities and offers strategic recommendations.

4. Scalability without compromise

Despite handling vast interactions, agentic AI maintains the precision and personalization that differentiate high-quality customer experiences from generic ones.

5. Dynamic integrations

With the ability to integrate into multiple systems—be it CRMs or ERPs—agentic AI streamlines sophisticated workflows and data sharing, and facilitates cross-departmental communication effortlessly.

6. Multilingual capabilities

Designed for global enterprises, agentic AI can carry out region-specific conversations in multiple languages, ensuring effective communication across borders.

7. Security and compliance

Given the growing scrutiny of AI technologies, agentic AI comes with built-in safeguards to ensure user data is protected and compliance thresholds are met.

8. Human handoff recognition

Unlike basic chatbots that can create frustrating experiences when escalating to human agents, agentic AI possesses sophisticated recognition capabilities to identify when human intervention is necessary.

The system can intelligently determine the complexity and emotional nuance of interactions, seamlessly transferring conversations to human agents at the optimal moment, while providing them with full context and relevant customer data to ensure a smooth transition.

9. Learning and adaptation

Agentic AI continuously learns and adapts from interactions, improving over time and delivering increasingly accurate and efficient responses.

How to get started with agentic AI

Transitioning from conventional chatbot solutions to agentic AI may seem daunting, but it can be achieved with a structured approach.

Step 1: Conduct a needs assessment

Evaluate your enterprise’s current processes and identify areas where greater autonomy and efficiency are required.

Step 2: Choose the right agentic AI solution

You’ll need to decide whether to build or buy your AI, or buy-to-build. Prioritize solutions like Quiq’s AI Studio, which focus on AI practices like scalability, integration, and observability.

Step 3: Plan for phased implementation

Adopt a phased strategy to minimize operational disruptions during the transition from traditional tools to agentic AI systems.

Step 4: Train your teams

Equip employees with the resources and skills needed to leverage agentic AI effectively within their workflows.

Step 5: Monitor and optimize

Continuously analyze the impact of agentic AI on KPIs like cost savings, customer satisfaction, and employee productivity. Use this data to refine operations.

Agentic AI is the strategic advantage of tomorrow

The transition from basic enterprise AI chatbot solutions to the cutting-edge potential of agentic AI has begun. Enterprises that adopt this new technology will unlock operational efficiencies, improve customer experiences, and gain competitive advantages that were once unimaginable.
Agentic AI is not just a tool—it’s a strategy for building future-ready enterprises prepared for the demands of a dynamic business ecosystem.

Apple Business Updates – A New Way To Proactively Engage Customers on Apple Messages for Business

Posted on Max Fortis

Key Takeaways

  • Businesses can now start the conversation. Apple’s new update lets companies send approved messages to customers without waiting for them to reach out first.
  • Limited to approved use cases.  It currently applies to things like order updates or offering to switch a phone call to messaging.
  • A smoother experience for everyone. Customers get faster updates, and businesses can reduce call volume while improving response times.
  • Privacy and accessibility are built in. Apple doesn’t read messages, and non-iPhone users will still receive messages through SMS.
  • Requires an approved provider.  Businesses need to work with an Apple-approved partner, like Quiq, to use this feature.

In mid-September 2024, Apple announced an exciting improvement to Messages for Business called Business Updates that will allow your business to proactively contact your customers in specific use cases—improving the customer experience, security, and making it easier for you to connect with your customers.

What is Apple Messages for Business?

As you’re no doubt aware, one of the most used apps on an iPhone is the Messages app. Apple Messages for Business is the technology that makes it possible for businesses to interact with their customers using Apple Messages. For customers, their conversations with businesses live alongside their other messages with other Apple devices (blue blurbs) and SMS messages (green blurbs) and work just like any other conversation.

This is a powerful way for contact centers like yours to reach the more than 1 billion people worldwide who use iPhones for daily communication, so it’s worth paying careful attention to.

Apple’s Big Announcement – Business Updates

Business Updates will allow you to reach out to your customers proactively, in a private and secure way, utilizing just their phone number and Apple’s pre-approved templates.

This will have positive impacts on both customer experience and your business. As you can see, there’s no downside here—which is why we’re so excited about it!

1. How will Business Updates Improve Customer Experiences?

Previously, Apple provided a world-class branded experience for businesses to message with their customers right inside the Messages app everyone is used to. In order to prevent spam and protect privacy, Apple previously required that customers send the first message. This limited the use cases for Apple Messages for Business to inbound customer support questions. As compared to SMS, this eliminated the ability to send proactive notifications, such as order updates.

Apple Business Updates lets businesses send proactive messages to customers—and it protects against spam by only allowing this option for approved use cases. This is great for business, too: a little over 60% of customers have stated they want businesses to be more proactive in reaching out, and (in a charming coincidence), offering text messaging can reduce per-customer support costs by about 60%. It’s nice when things work out like that!

Let’s say a little bit more about those use cases. Initially, Apple is focused on sending proactive, business-initiated messages related to orders, but a “Connect Using Messages” notification is also supported, which businesses can use to switch phone calls to Apple Messages.

The data indicates that IVR is a sensible self-service option, but this ability to switch will give customers the choice to switch channels from a call to text messaging, meaning you can better meet them where they are and meet their preferences.

This is all done using templates. The full list can be found in Apple’s documentation, but here are a few samples. The first two are examples of “Connect Using Messages” which could be used to offer a customer the option to switch a phone call to messages:

Apple Messages for Business

2. How will the Apple Messages for Business Update Improve Your Business?

Now, let’s turn to the other side of the equation, the impact of the announcement on your business operations.

Apple has released Business Updates in iOS 18, the newest iPhone operating system that was announced in September 2024, allowing businesses that work with an Apple Messaging Service Provider (MSP), like Quiq, to initiate a conversation with a customer from their branded experiences. Order updates and converting calls to messaging (discussed above) are two obvious early use cases.

Consistent with Apple’s commitment to security, Apple does not read messages or store conversations. In a world more and more besieged by data breaches, hacks, and invasions of privacy, your users need not fear that Apple is using the messages inappropriately.

A final note: Android devices, or devices that do support Apple Messages for Business, will automatically fall back to SMS when messages are sent in Quiq. This means that you can configure your business processes to send notifications to all customers and Quiq will make sure they are delivered on the best possible channel.

The Future of Apple Messages for Business

Contact centers and CX teams are always looking for new ways to better meet customer needs, and this announcement opens up some exciting possibilities. You can now reach out in more ways and integrate more robustly with the rest of the Apple ecosystem, leading to a reduction in distraction and search fatigue for your users—and a reduction in expenses for you.

If you want to learn more about how Quiq enables Apple Messages for Business, you can do that here.

Frequently Asked Questions (FAQs)

What is Apple’s new Business Updates feature?

Apple’s Business Updates feature allows companies to send approved, proactive messages to customers through Apple Messages for Business – without requiring the customer to start the conversation.

What types of messages can businesses send?

Right now, proactive messages are limited to Apple-approved use cases like order updates, appointment reminders, or offering to switch from a phone call to messaging.

Do customers need to opt in to receive these messages?

Yes. Customers must have shared their phone number and consented to receive messages from the business, ensuring compliance with Apple’s privacy standards.

How does Apple protect customer privacy?

Apple doesn’t read or store message content. All conversations are end-to-end encrypted, and customer data stays private.

What happens if the customer doesn’t use an Apple device?

If the recipient isn’t using an iPhone or iPad, messages will automatically be sent via SMS to ensure they’re still received.

How can businesses get started with Apple Business Updates?

To enable this feature, businesses need to work with an Apple-approved Messaging Service Provider (MSP) like Quiq to handle setup, approvals, and integration.

Reinventing Customer Support: How Contact Center AI Delivers Efficiency Like Never Before

Posted on Michael Hartsog

Contact centers face unprecedented pressure managing sometimes hundreds of thousands of daily customer interactions across multiple channels. Traditional approaches, with their rigid legacy systems and manual processes, often buckle under these demands, leading to frustrated customers and overwhelmed agents. This was certainly the case during the past few years, when many platforms and processes collapsed under the weight of astronomical volumes due to natural disasters and other unplanned events.

So we set out to build a solution to tackle these pressures.

Our solution? Contact center AI – an agentic AI-based solution that transforms how businesses handle customer support.

In this article, I will give you a lay of the contact center AI land. I’ll explain what it is and how it’s best used, as well as ways to start implementing it.

What is contact center AI?

Contact center AI represents a sophisticated fusion of artificial intelligence and machine learning technologies designed to optimize every aspect of customer service operations. It’s more than just basic automation—it’s about creating smarter, more efficient systems that enhance both customer and agent experiences.

This advanced technology incorporates tools like Large Language Models (LLMs), which allow it to understand and respond to customer queries in a conversational and human-like manner. It also leverages real-time transcription, allowing customer interactions to be recorded and analyzed instantly, providing actionable insights for improving service quality. Additionally, intelligent task automation streamlines repetitive tasks, freeing agents to focus on more complex customer needs.

By understanding customer intent, analyzing context, and processing natural language queries, contact center AI can even make rapid, data-driven decisions to determine the best way to handle every interaction.

Whether routing a customer to the right department or providing instant answers through AI agents, this technology ensures a more dynamic, responsive, and efficient customer service environment. It’s a game-changer for businesses looking to improve operational efficiency and deliver exceptional customer experiences.

AI-powered solutions for contact center challenges

1. Managing high volumes efficiently

During peak periods, managing high customer interaction volumes can be a significant challenge for contact centers. This is where contact center AI steps in, offering intelligent automation and advanced routing capabilities to streamline operations.

AI-powered systems can automatically deflect routine inquiries, such as negative value, redundant conversations—like ‘where’s my order?’ or account updates—to AI agents that provide quick and accurate responses. This ensures that customers get instant answers for simpler questions without wait.

Meanwhile, human agents are free to focus on more complex or sensitive cases that require their expertise. This smart delegation not only reduces wait times, but also helps maintain high customer satisfaction levels by ensuring every interaction is handled appropriately. Each human agent has all the information gathered in the interaction at the start of the conversation, eliminating repetition and frustration.

2. Real-time AI to empower your agents

Injecting generative AI into your contact center empowers human agents by significantly enhancing their efficiency and effectiveness in managing customer interactions. These AI systems provide real-time assistance during conversations, suggesting responses for agents to send, as well as taking action on their behalf when appropriate—like adding a checked bag to a customer’s flight.
This gives agents the time to focus on issues that require human judgment, reducing the effort and time needed to resolve customer concerns. The seamless collaboration between AI and human agents elevates the quality of customer service, boosts agent productivity, and enhances customer satisfaction.

3. Improving complex case routing

Advanced AI solutions now integrate into various systems to streamline customer service operations. These systems analyze multiple factors, including customer history, intent, preferences, and the unique expertise of available agents, to match each case to the most suitable representative. Then, AI can analyze call data in real time, continuously optimizing routing processes to further enhance efficiency during high-demand periods.

By ensuring the right agent handles the right query from the start, these AI-driven systems significantly enhance first-call resolution rates, reduce wait times, and improve customer satisfaction. This not only boosts operational efficiency, but also fosters stronger customer loyalty and trust in the long term.

4. Enabling 24/7 customer support

Modern consumers expect round-the-clock support, but maintaining a full staff 24/7 can be both costly and impractical for many businesses—especially if they require multilingual global support. AI-powered virtual agents step in to bridge this gap, offering reliable and consistent assistance at any time of day or night.

These tools are designed to handle a wide range of customer inquiries, all while adapting to different languages and maintaining a high standard of service. Additionally, they can manage high volumes of inquiries simultaneously, ensuring no customer is left waiting. By leveraging AI, businesses can not only meet customer expectations, but also enhance efficiency and reduce operational costs.

4 key benefits of contact center AI

Now that we’ve touched on what contact center AI is and how it can help businesses most, let’s go into the top benefits of implementing AI in your contact center.

Contact Center AI-4-AI-benefits

1. Enhanced customer experience

AI is revolutionizing the customer experience through multiple transformative capabilities. By providing instant response times through always-on AI agents, customers no longer face frustrating queues or delayed support. These agentic AI agents deliver personalized interactions by analyzing customer history and preferences, offering tailored recommendations and maintaining context from previous conversations. And all this context is available to human agents, should the issues be escalated to them.

Problem resolution becomes more efficient through predictive analytics and intelligent routing, ensuring customers connect with the most qualified agents for faster first-call resolution.

The technology also maintains consistent service quality across all channels, offering standardized responses and multilingual support without additional staffing, even during peak times. AI takes customer service from reactive to proactive by identifying potential issues before they escalate, sending automated reminders, and suggesting relevant products based on customer behavior.

Perhaps most importantly, AI enables a seamless customer experience across all channels, maintaining conversation context across multiple touch points and facilitating smooth transitions between automated systems and human agents. This unified approach creates a more efficient, personalized, and satisfying customer experience that balances automated convenience with human expertise when needed.

2. Boosted agent productivity

AI automation significantly enhances agent productivity by taking over time-consuming routine tasks, such as call summarization, data entry, and follow-up scheduling.

By automating these repetitive processes, agents can save significant time, giving them more freedom to engage with customers on a deeper level. This shift allows agents to prioritize building meaningful relationships, addressing complex customer needs, and delivering a more personalized service experience, ultimately driving better outcomes for both the business and its customers.

3. Cost savings

Organizations can significantly cut operational expenses by leveraging automated interactions and improving agent processes. Automation allows businesses to handle much higher volumes of customer inquiries without the need to hire additional staff, reducing labor costs.

Optimized processes ensure that agents are deployed effectively, minimizing downtime and maximizing productivity. Together, these strategies help organizations save money while maintaining high levels of service quality.

4. Increased (and improved) data insights

Analytics into AI performance offers businesses a deeper understanding of their operations by delivering actionable insights into customer interactions, agent performance, and operational efficiency.

These data-driven insights help identify trends, pinpoint areas for improvement, and make informed decisions that enhance both service quality and customer satisfaction. With continuous monitoring and analysis, businesses can adapt quickly to changing demands and maintain a competitive edge.

Implementation tips to start your contact center AI

If you want to add AI to your contact center, there are a handful of important decisions you need to make first that’ll determine your approach. Here are the most important ones to get you started.

1. Define your business objectives

Begin by assessing specific challenges and objectives, so that you can identify areas where automation could have the most significant impact later on—such as streamlining processes, reducing costs, or improving customer experiences.

Consider how AI can address these pain points and align with your long-term goals, but remember to start small. You just need one use case to get going. This allows you to test the solution in a controlled environment, gather valuable insights, and identify potential challenges.

2. Identify the best touch points in your customer journey

After you define your business objectives, you’ll want to identify the touch points within your customer journey that are best for AI. Within those touch points are End User Stories that will help you determine the data sources, escalation and automation paths, and success metrics that will lead you to significant outcomes. Our expert team of AI Engineers and Program Managers will help you map out the correct path.

3. Decide how you’ll acquire your AI: build, buy, or buy-to-build?

When choosing AI solutions, ensure they align with your organization’s size, industry, and specific requirements. Look at factors such as scalability to accommodate future growth, integration capabilities with your existing systems, and the level of vendor support offered.

It’s important to consider the solution’s ease of use, cost-effectiveness, and potential for customization to meet your unique needs. Another critical factor is observability, so you can avoid “black box AI” that’s nearly impossible to manage and improve.

You’ll also need to evaluate whether it’s best to buy an off-the-shelf solution, build a custom AI system tailored to your needs, or opt for a buy-to-build approach, which combines pre-built technology with customization options for greater flexibility.

4. Prep for human agent training at the outset

Invest in robust training programs to equip agents with the knowledge and skills needed to work effectively alongside AI tools. This includes developing expertise in areas where human input is crucial, such as managing complex emotional situations, problem-solving, and building rapport with customers.

5. Plan for integration and compatibility

Remember: Your AI will only be as good as the data and systems it can access. Verify compatibility with your existing systems, like CRM, ticketing platforms, or live chat tools. Integration to these systems is critical to the success of your contact center AI solution.
You also want to plan how AI will seamlessly integrate into human agents’ daily tasks without disrupting their workflows, and include all data within your project scope.

6. Establish monitoring and feedback loops

Before making any changes to your contact center, benchmark KPIs like first-call resolution, average handling time, and customer sentiment. Then regularly update and retrain the AI based on human agent and customer feedback to experiment and make the most critical changes for your business.

7. Plan for scalability

Implement AI solutions in phases, beginning with just one or two specific use cases. Look for solutions designed to help your business scale by accommodating different communication channels and adapting to evolving technologies.
By focusing on skills that complement AI capabilities, agents can provide a seamless, empathetic, and personalized experience that enhances customer satisfaction.

Final thoughts on contact center AI

Contact center AI represents a true organizational transformation opportunity in customer support, offering unprecedented ways to improve efficiency while enhancing customer experiences. Rather than replacing human agents, it empowers them to work more effectively, focusing on high-value interactions that require emotional intelligence and complex problem-solving skills.

The future of customer support lies in finding the right balance between automated efficiency and human touch. Organizations that successfully move from a conversational AI contact center to fully generative AI experiences will see significant lifts in key metrics and will be well-positioned to meet evolving customer expectations.

Google Business Messaging: How to Adapt & Alternatives

Posted on Max Fortis

Key Takeaways

  • Google Business Messaging is officially gone. The channel has been fully shut down, so businesses can no longer rely on Google Search or Maps as a messaging entry point for customer conversations.
  • Customer expectations haven’t changed; messaging is still critical. While GBM has ended, customers still expect fast, conversational support, making it essential to replace it with modern messaging channels rather than reverting to phone or email alone.
  • The best path forward is a multi-channel messaging strategy. Alternatives like SMS, WhatsApp, Apple Messages for Business, web chat, and social messaging allow brands to meet customers where they already are — with automation and AI to scale support efficiently.

Google messaging for business has long been one of the primary rich messaging channels for Android, but it’s now in the process of being phased out.

Google messaging for business has been sunsetted, but that doesn’t mean your customer experience has to suffer. This piece will walk you through the main alternatives to GBM, ensuring you have everything you need to keep your organization running smoothly.

What are the Alternatives to Google Messaging for Business?

If you’re wondering which communication channel you should switch to now that Google messaging for business is gone, here are some you should consider. They’re divided into two groups. Group one consists of the channels we personally recommend, based on our years of experience in customer service and contact center management. Section two deals with communication channels that we still support but which, in our view, are not as promising as alternatives to GBM.

Recommended Alternatives to Google Business Messaging

Here are the best channels to serve as replacements for Google messaging for business

  • WhatsApp: WhatsApp enables text, voice, and video communications for over two billion global users. The platform includes several built-in features that appeal to businesses looking to forge deeper, more personal connections with their customers. Most importantly, it is a cross-platform messaging app, meaning it will allow you to chat with both Android and Apple users.
  • Rich Communication Services (RCS): RCS is best positioned as a modern, feature-rich upgrade to SMS, rather than a direct competitor to apps like WhatsApp. It’s designed to deliver richer, branded messaging experiences directly within native messaging apps on supported Android devices.
  • Text Messaging or Short Message Service (SMS): SMS is a long-standing staple for a reason, and with a conversational AI platform like Quiq, you can put large language models to work automating substantial parts of your SMS-based customer interactions.

Other Alternatives to Google Business Messaging

Here are the other channels you might look into.

  • Live web chat: Live chat is used to provide an interactive experience, with readily available, helpful agents, and swift responses. There are plenty of ways to encourage your customers to actually use your live chat offering, including mentioning it during phone calls, linking to it in blog posts or emails, and promoting it on social media.
  • Apple Messages for Business: Unlike standard text messaging available on mobile phones, Apple Messages is a specialized service designed for businesses to engage with customers. It facilitates easy setup of touchpoints such as QR codes, apps, or email messages, enabling appointments, issue resolution, and payments, among other things.
  • Facebook Messenger: Facebook Messenger for Business enables brands to handle incoming queries efficiently, providing immediate responses through AI assistants or routing complex issues to human agents. Clients integrating with a tool like Quiq have seen a massive ROI – a 95% customer satisfaction (CSAT), a 70-80% resolution rate for incoming customer inquiries automatically, and more. Like WhatsApp, FB Messenger is a cross-platform messaging app, meaning it can help you reach users on both Android and Apple devices.
  • Instagram: Instagram isn’t just for posting pictures anymore – your target audience is likely using it to discover brands, shop, and make purchases. They’re reaching out through direct messages (DM), responding to stories, and commenting on posts. Integrating Quiq’s conversational AI with Instagram’s messaging API makes it easier to automate responses to frequently asked questions, thereby reducing the workload on your human agents.
  • X (formerly Twitter): With nearly 400 million registered users and native, secure payment options, X is not a platform you can ignore. And the data supports this. By utilizing X business messaging, you can connect with your customers directly, providing them with excellent service experiences. Over time, this approach helps you build strong relationships and positive brand perceptions.

How to Switch Away From Google Business Messaging

Even though GBM is going the way of the Dodo, the good news is that you have tons of other options. Check out our dedicated pages to learn more about SMS, WhatsApp, and Facebook Messenger, and you’re warmly invited to consult with our team if you are currently using GBM with another managed service provider and are not sure what the best direction forward is!

Frequently Asked Questions (FAQs)

How should I choose which alternative to use?

Focus on where your customers already communicate most — for example, global audiences may prefer WhatsApp, while domestic audiences often rely on SMS/text messaging. Social channels like Messenger and Instagram are valuable if your brand has strong social engagement. Consider factors like cross-platform access, support automation, and integration with your existing systems.

What other messaging channels can I consider?

Beyond the top recommendations, there are additional channels you can integrate to broaden your reach and support capabilities: 

X (formerly Twitter) Messaging: Offers conversational engagement and public brand interaction.

Live Web Chat: Adds an on-site support option for real-time conversations.

Apple Messages for Business: Lets iPhone users message your business directly with rich features like appointment scheduling and payments.

Facebook Messenger: A cross-platform social messaging channel that supports automation and human-powered chats.

Instagram DMs: Useful for supportive messaging as well as brand discovery and social engagement.

5 Tips for Coaching Your Contact Center Agents to Work with AI

Posted on Michael Hartsog

Generative AI has enormous potential to change the work done at places like contact centers. For this reason, we’ve spent a lot of energy covering it, from deep dives into the nuts and bolts of large language models to detailed advice for managers considering adopting it.

Here, we will provide tips on using AI tools to coach, manage, and improve your agents.

How Will AI Make My Agents More Productive?

Contact centers can be stressful places to work, but much of that stems from a paucity of good training and feedback. If an agent doesn’t feel confident in assuming their responsibilities or doesn’t know how to handle a tricky situation, that will cause stress.

Tip #1: Make Collaboration Easier

With the right AI tools for coaching agents, you can get state-of-the-art collaboration tools that allow agents to invite their managers or colleagues to silently appear in the background of a challenging issue. The customer never knows there’s a team operating on their behalf, but the agent won’t feel as overwhelmed. These same tools also let managers dynamically monitor all their agents’ ongoing conversations, intervening directly if a situation gets out of hand.

Agents can learn from these experiences to become more performant over time.

Tip #2: Use Data-Driven Management

Speaking of improvement, a good AI platform will have resources that help managers get the most out of their agents in a rigorous, data-driven way. Of course, you’re probably already monitoring contact center metrics, such as CSAT and FCR scores, but this barely scratches the surface.

What you really need is a granular look into agent interactions and their long-term trends. This will let you answer questions like “Am I overstaffed?” and “Who are my top performers?” This is the only way to run a tight ship and keep all the pieces moving effectively.

Tip #3: Use AI To Supercharge Your Agents

As its name implies, generative AI excels at generating text, and there are several ways this can improve your contact center’s performance.

To start, these systems can sometimes answer simple questions directly, which reduces the demands on your team. Even when that’s not the case, however, they can help agents draft replies, or clean up already-drafted replies to correct errors in spelling and grammar. This, too, reduces their stress, but it also contributes to customers having a smooth, consistent, high-quality experience.

Tip #4: Use AI to Power Your Workflows

A related (but distinct) point concerns how AI can be used to structure the broader work your agents are engaged in.

Let’s illustrate using sentiment analysis, which makes it possible to assess the emotional state of a person doing something like filing a complaint. This can form part of a pipeline that sorts and routes tickets based on their priority, and it can also detect when an issue needs to be escalated to a skilled human professional.

Tip #5: Train Your Agents to Use AI Effectively

It’s easy to get excited about what AI can do to increase your efficiency, but you mustn’t lose sight of the fact that it’s a complex tool your team needs to be trained to use. Otherwise, it’s just going to be one more source of stress.

You need to have policies around the situations in which it’s appropriate to use AI and the situations in which it’s not. These policies should address how agents should deal with phenomena like “hallucination,” in which a language model will fabricate information.

They should also contain procedures for monitoring the performance of the model over time. Because these models are stochastic, they can generate surprising output, and their behavior can change.

You need to know what your model is doing to intervene appropriately.

Wrapping Up

Hopefully, you’re more optimistic about what AI can do for your contact center, and this has helped you understand how to make the most out of it.

If there’s anything else you’d like to go over, you’re always welcome to request a demo of the Quiq platform. Since we focus on contact centers we take customer service pretty seriously ourselves, and we’d love to give you the context you need to make the best possible decision!

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Leveraging Agent Insights to Boost Efficiency and Performance

Posted on The Quiq Team

In the ever-evolving customer service landscape, the role of contact center agents cannot be overstated. As the frontline representatives of a company, their performance directly impacts the quality of customer experience, influencing customer loyalty and brand reputation.

However, the traditional approach to managing agent performance – relying on periodic reviews and supervisor observations – has given way to a more sophisticated, data-driven strategy. For this reason, managing agent performance with a method that leverages the rich data generated by agent interactions to enhance service delivery, agent satisfaction, and operational efficiency is becoming more important all the time.

This article delves into this approach. We’ll begin by examining its benefits from three critical perspectives – the customer, the agent, and the contact center manager – before turning to a more granular breakdown of how you can leverage it in your contact center.

Why is it Important to Manage Agent Performance with Insights?

First, let’s start by justifying this project. While it’s true that very few people today would doubt the need to track some data related to what agents are doing all day, it’s still worth saying a few words about why it really is a crucial part of running a contact center.

To do this, we’ll focus on how three groups are impacted when agent performance is managed through insights: customers, the agents themselves, and contact center managers.

It’s Good for the Customers

The primary beneficiary of improved agent performance is the customer. Contact centers can tailor their service strategies by analyzing agent metrics to better meet customer needs and preferences. This data-driven approach allows for identifying common issues, customer pain points, and trends in customer behavior, enabling more personalized and effective interactions.

As agents become more adept at addressing customer needs swiftly and accurately, customer satisfaction levels rise. This enhances the individual customer’s experience and boosts the overall perception of the brand, fostering loyalty and encouraging positive word-of-mouth.

It’s Good for the Agents

Agents stand to gain immensely from a management strategy focused on data-driven insights. Firstly, performance feedback based on concrete metrics rather than subjective assessments leads to a fairer, more transparent work environment.

Agents receive specific, actionable feedback that helps them understand their strengths and which areas need improvement. This can be incredibly motivating and can drive them to begin proactively bolstering their skills.

Furthermore, insights from performance data can inform targeted training and development programs. For instance, if data indicates that an agent excels in handling certain inquiries but struggles with others, their manager can provide personalized training to bridge this gap. This helps agents grow professionally and increases their job satisfaction as they become more competent and confident in their roles.

It’s Good for Contact Center Managers

For those in charge of overseeing contact centers, managing agents through insights into their performance offers a powerful tool for cultivating operational excellence. It enables a more strategic approach to workforce management, where decisions are informed by data rather than gut feeling.

Managers can identify high performers and understand the behaviors that lead to success, allowing them to replicate these practices across the team. Intriguingly, this same mechanism is also at play in the efficiency boost seen by contact centers that adopt generative AI. When such centers train a model on the interactions of their best agents, the knowledge in those agents’ heads can be incorporated into the algorithm and utilized by much more junior agents.

The insights-driven approach also aids in resource allocation. By understanding the strengths and weaknesses of their team, managers can assign agents to the tasks they are most suited for, optimizing the center’s overall performance.

Additionally, insights into agent performance can highlight systemic issues or training gaps, providing managers with the opportunity to make structural changes that enhance efficiency and effectiveness.

Moreover, using agent insights for performance management supports a culture of continuous improvement. It encourages a feedback loop where agents are continually assessed, supported, and developed, driving the entire team towards higher performance standards. This improves the customer experience and contributes to a positive working environment where agents feel valued and empowered.

In summary, managing performance by tracking agent metrics is a holistic strategy that enhances the customer experience, supports agent development, and empowers managers to make informed decisions.

It fosters a culture of transparency, accountability, and continuous improvement, leading to operational excellence and elevated service standards in the contact center.

How to Use Agent Insights to Manage Performance

Now that we know what all the fuss is about, let’s turn to addressing our main question: how to use agent insights to correct, fine-tune, and optimize agent performance. This discussion will center specifically around Quiq’s Agent Insights tool, which is a best-in-class analytics offering that makes it easy to figure out what your agents are doing, where they could improve, and how that ultimately impacts the customers you serve.

Managing Agent Availability

To begin with, you need a way of understanding when your agents are free to handle an issue and when they’re preoccupied with other work. The three basic statuses an agent can have are “available,” “current conversations” (i.e. only working on the current batch of conversations), and “unavailable.” All three of these can be seen through Agent Insights, which allows you to select from over 50 different metrics, customizing and saving different views as you see fit.

The underlying metrics that go into understanding this dimension of agent performance are, of course, time-based. In essence, you want to evaluate the ratios between four quantities: the time the agent is available, the time the agent is online, the time the agent spends in a conversation, and the time an agent is unavailable.

As you’re no doubt aware, you don’t necessarily want to maximize the amount of time an agent spends in conversations, as this can quickly lead to burnout. Rather, you want to use these insights into agent performance to strike the best, most productive balance possible.

Managing Agent Workload

A related phenomenon you want to understand is the kind of workload your agents are operating under. The five metrics that underpin this are:

  1. Availability
  2. Number of completions per hour your agents are managing
  3. Overall utilization (i.e. the percentage of an agent’s available conversation limit they have filled in a given period).
  4. Average workload
  5. The amount of time agents spend waiting for a customer response.

All of this can be seen in Agent Insights. This view allows you to do many things to hone in on specific parts of your operation. You can sort by the amount of time your agents spend waiting for a reply from a customer, for example, or segment agents by e.g. role. If you’re seeing high waiting and low utilization, that means you are overstaffed and should probably have fewer agents.

If you’re seeing high waiting and high utilization, by contrast, you should make sure your agents know inactive conversations should be marked appropriately.

As with the previous section, you’re not necessarily looking to minimize availability or maximize completions per hour. You want to make sure that agents are working at a comfortable pace, and that they have time between issues to reflect on how they’re doing and think about whether they want to change anything in their approach.

But with proper data-driven insights, you can do much more to ensure your agents have the space they need to function optimally.

Managing Agent Efficiency

Speaking of functioning optimally, the last thing we want to examine is agent efficiency. By using Agent Insights, we can answer questions such as how well new agents are adjusting to their roles, how well your teams are working together, and how you can boost each agent’s output (without working them too hard).

The field of contact center analytics is large, but in the context of agent efficiency, you’ll want to examine metrics like completion rate, completions per hour, reopen rate, missed response rate, missed invitation rate, and any feedback customers have left after interacting with your agents.

This will give you an unprecedented peek into the moment-by-moment actions agents are taking, and furnish you with the hard facts you need to help them streamline their procedures. Imagine, for example, you’re seeing a lot of keyboard usage. This means the agent is probably not operating as efficiently as they could be, and you might be able to boost their numbers by training them to utilize Quiq’s Snippets tool.

Or, perhaps you’re seeing a remarkably high rate of clipboard usage. In that case, you’d want to look over the clipboard messages your agents are using and consider turning them into snippets, where they’d be available to everyone.

The Modern Approach to Managing Agents

Embracing agent insights for performance management marks a transformative step towards achieving operational excellence in contact centers. This data-driven approach not only elevates the customer service experience but also fosters a culture of continuous improvement and empowerment among agents.

By leveraging tools like Quiq’s Agent Insights, managers can unlock a comprehensive understanding of agent availability, workload, and efficiency, enabling informed decisions that benefit both the customer and the service team.

If you’re intrigued by the possibilities, contact us to schedule a demo today!

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6 Questions to Ask Generative AI Vendors You’re Evaluating

Posted on The Quiq Team

With all the power exhibited by today’s large language models, many businesses are scrambling to leverage them in their offerings. Enterprises in a wide variety of domains – from contact centers to teams focused on writing custom software – are adding AI-backed functionality to make their users more productive and the customer experience better.

But, in the rush to avoid being the only organization not using the hot new technology, it’s easy to overlook certain basic sanity checks you must perform when choosing a vendor. Today, we’re going to fix that. This piece will focus on several of the broad categories of questions you should be asking potential generative AI providers as you evaluate all your options.

This knowledge will give you the best chance of finding a vendor that meets your requirements, will help you with integration, and will ultimately allow you to better serve your customers.

These are the Questions you Should ask Your Generative AI Vendor

Training large language models is difficult. Besides the fact that it requires an incredible amount of computing power, there are also hundreds of tiny little engineering optimizations that need to be made along the way. This is part of the reason why all the different language model vendors are different from one another.

Some have a longer context window, others write better code but struggle with subtle language-based tasks, etc. All of this needs to be factored into your final decision because it will impact how well your vendor performs for your particular use case.

In the sections that follow, we’ll walk you through some of the questions you should raise with each vendor. Most of these questions are designed to help you get a handle on how easy a given offering will be to use in your situation, and what integrating it will look like.

1. What Sort of Customer Service Do You Offer?

We’re contact center and customer support people, so we understand better than anyone how important it is to make sure users know what our product is, what it can do, and how we can help them if they run into issues.

As you speak with different generative AI vendors, you’ll want to probe them about their own customer support, and what steps they’ll take to help you utilize their platform effectively.

For this, just start with the basics by figuring out the availability of their support teams – what hours they operate in, whether they can accommodate teams working in multiple time zones, and whether there is an option for 24/7 support if a critical problem arises.

Then, you can begin drilling into specifics. One thing you’ll want to know about is the channels their support team operates through. They might set up a private Slack channel with you so you can access their engineers directly, for example, or they might prefer to work through email, a ticketing system, or a chat interface. When you’re discussing this topic, try to find out whether you’ll have a dedicated account manager to work with.

You’ll also want some context on the issue resolution process. If you have a lingering problem that’s not being resolved, how do you go about escalating it, and what’s the team’s response time for issues in general?

Finally, it’s important that the vendors have some kind of feedback mechanism. Just as you no doubt have a way for clients to let you know if they’re dissatisfied with an agent or a process, the vendor you choose should offer a way for you to let them know how they’re doing so they can improve. This not only tells you they care about getting better, it also indicates that they have a way of figuring out how to do so.

2. Does Your Team Offer Help with Setting up the Platform?

A related subject is the extent to which a given generative AI vendor will help you set up their platform in your environment. A good way to begin is by asking what kinds of training materials and resources they offer.

Many vendors are promoting their platforms by putting out a ton of educational content, all of which your internal engineers can use to get up to speed on what those platforms can do and how they function.

This is the kind of thing that is easy to overlook, but you should pay careful attention to it. Choosing a generative AI vendor that has excellent documentation, plenty of worked-out examples, etc. could end up saving you a tremendous amount of time, energy, and money down the line.

Then, you can get clarity on whether the vendor has a dedicated team devoted to helping customers like you get set up. These roles are usually found under titles like “solutions architect”, so be sure to ask whether you’ll be assigned such a person and the extent to which you can expect their help. The benefits of IT staff augmentation become clear here — you gain access to these specialized experts without long-term hiring commitments. Some platforms will go to the moon and back to make sure you have everything you need, while others will simply advise you if you get stuck somewhere.

Which path makes the most sense depends on your circumstances. If you have a lot of engineers you may not need more than a little advice here and there, but if you don’t, you’ll likely need more handholding (but will probably also have to pay extra for that). Keep all this in mind as you’re deciding.

3. What Kinds of Integrations Do You Support?

Now, it’s time to get into more technical details about the integrations they support. When you buy a subscription to a generative AI vendor, you are effectively buying a set of capabilities. But those capabilities are much more valuable if you know they’ll plug in seamlessly with your existing software, and they’re even more valuable if you know they’ll plug into software you plan on building later on. You’ve probably been working on a roadmap, and now’s the time to get it out.

It’s worth checking to see whether the vendor can support many different kinds of language models. This involves a nuance in what the word “vendor” means, so let’s unpack it a little bit. Some generative AI vendors are offering you a model, so they’re probably not going to support another company’s model.

OpenAI and Anthropic are examples of model vendors, so if you work with them you’re buying their model and will not be able to easily incorporate someone else’s model.

Other vendors, by contrast, are offering you a service, and in many cases that service could theoretically by powered by many different models.

Quiq’s Conversational CX Platform, for example, supports OpenAI’s GPT models, and we have plans to expand the scope of our integrations to encompass even more models in the future.

Another thing you’re going to want to check on is whether the vendor makes it easy to integrate vector databases into your workflow. Vectors are data structures that are remarkably good at capturing subtle relationships in large datasets; they’re becoming an ever-more-important part of machine learning, as evinced by the fact that there are now a multitude of different vector databases on offer.

The chances are pretty good that you’ll eventually want to leverage a vector database to store or search over customer interactions, and you’ll want a vendor that makes this easy.

Finally, see if the vendor has any case studies you can look at. Quiq has published a case study on how our language services were utilized by LOOP, a car insurance company, to make a far superior customer-service chatbot. The result was that customers were able to get much more personalization in their answers and were able to resolve their problems fully half of the time, without help. This led to a corresponding 55% reduction in tickets, and a customer satisfaction rating of 75% (!) when interacting with the Quiq-powered AI assistant.

See if the vendors you’re looking at have anything similar you can examine. This is especially helpful if the case studies are focused on companies that are similar to yours.

4. How Does Prompt Engineering and Fine-Tuning Work for Your Model?

For many tasks, large language models work perfectly fine on their own, without much special effort. But there are two methods you should know about to really get the most out of them: prompt engineering and fine-tuning.

As you know, prompts are the basic method for interacting with language models. You’ll give a model a prompt like “What is generative AI?”, and it’ll generate a response. Well, it turns out that models are really sensitive to the wording and structure of prompts, and prompt engineers are those who explore the best way to craft prompts to get useful output from a model.

It’s worth asking potential vendors about this because they handle prompts differently. Quiq’s AI Studio encourages atomic prompting, where a single prompt has a clear purpose and intended completion, and we support running prompts in parallel and sequentially. You can’t assume everyone will do this, however, so be sure to check.

Then, there’s fine-tuning, which refers to training a model on a bespoke dataset such that its output is heavily geared towards the patterns found in that dataset. It’s becoming more common to fine-tune a foundational model for specific use cases, especially when those use cases involve a lot of specialized vocabulary such as is found in medicine or law.

Setting up a fine-tuning pipeline can be cumbersome or relatively straightforward depending on the vendor, so see what each vendor offers in this regard. It’s also worth asking whether they offer technical support for this aspect of working with the models.

5. Can Your Models Support Reasoning and Acting?

One of the current frontiers in generative AI is building more robust, “agentic” models that can execute strings of tasks on their way to completing a broader goal. This goes by a few different names, but one that has been popping up in the research literature is “ReAct”, which stands for “reasoning and acting”.

You can get ReAct functionality out of existing language models through chain-of-thought prompting, or by using systems like AutoGPT; to help you concretize this a bit, let’s walk through how ReAct works in Quiq.

With Quiq’s AI Studio, a conversational data model is used to classify and store both custom and standard data elements, and these data elements can be set within and across “user turns”. A single user turn is the time between when a user offers an input to the time at which the AI responds and waits for the next user input.

Our AI can set and reason about the state of the data model, applying rules to take the next best action. Common actions include things like fetching data, running another prompt, delivering a message, or offering to escalate to a human.

Though these efforts are still early, this is absolutely the direction the field is taking. If you want to be prepared for what’s coming without the need to overhaul your generative AI stack later on, ask about how different vendors support ReAct.

6. What’s your Pricing Structure Like?

Finally, you’ll need to talk to vendors about how their prices work, including any available details on licensing types, subscriptions, and costs associated with the integration, use, and maintenance of their solution.

To take one example, Quiq’s licensing is based on usage. We establish a usage pool wherein our customers pre-pay Quiq for a 12-month contract; then, as the customer uses our software money is deducted from that pool. We also have an annual AI Assistant Maintenance fee along with a one-time implementation fee.

Vendors can vary considerably in how their prices work, so if you don’t want to overpay then make sure you have a clear understanding of their approach.

Picking the Right Generative AI Vendor

Language models and related technologies are taking the world by storm, transforming many industries, including customer service and contact center management.

Making use of these systems means choosing a good vendor, and that requires you to understand each vendor’s model, how those models integrate with other tools, and what you’re ultimately going to end up paying.

If you want to see how Quiq stacks up and what we can do for you, schedule a demo with us today!

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