Test, optimize, manage, and automate with AI. Take a free test drive of Quiq's AI Studio. Test drive AI Studio -->
Quiq

Tag: agents

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.

How Customer Service AI Can Change Your Business

Posted on Max Fortis

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

What is AI in Customer Service?

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

What are the Benefits of Using AI in Customer Service?

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

1. AI will automate routine work.

As with so many jobs, a lot of what customer service agents do day-to-day is fairly repetitive, as little imagination is required to do things like order tracking, balance checking, or password resetting. These days, customers are obsessed with quick and convenient service, so utilizing customer service AI to automate and speed up routine tasks benefits both customers (who want answers now) and agents (who don’t have to do the same thing all the time).

2. Scalability and Cost Savings

A related point concerns the fact that AI automating routine tasks and supporting agents with data-driven insights allows businesses to scale customer service without a proportional increase in costs. This lowers operating expenses, increases capacity to handle peak volumes, and frees-up human agents for high-value tasks.

3. Customer service AI can help make ‘smart’ documentation.

Many customers will begin by checking out your documentation to see if they can’t solve a problem first, so it’s important for yours to be top-notch. You can use large language models (LLMs) to draft or update documentation, of course, or you can go a step further. Modern AI agents can use documentation to answer questions directly, and can also guide customers to use the documentation themselves.

4. Customer Support AI Supercharges Chat.

Customer service leaders have long recognized that AI-powered agents for chat support are a cost-effective (and often preferred) alternative to traditional phone or email support. AI agents for chat are rapidly becoming a mainstay for contact centers because they can deliver personalized, round-the-clock support across any channel while seamlessly integrating with other tools in the CX, eCommerce, and marketing tech stacks.

5. AI contributes to a better customer experience.

All of the above ultimately adds up to a much better customer experience. When customers can immediately get their questions answered (whether at 2 p.m. or 2 a.m.), with details relevant to their specific situation, or even in their native language, that’s going to leave an impression!

6. Use customer service AI to learn about your customers.

Before moving on, let’s discuss the amazing capacity customer service AI has to help you discover trends in your customers preferences, predict customer needs, identify patterns, and proactively address issues before they become major problems. This can significantly speed up your response time, reduce churn, improve resource allocation, and establish your reputation for anticipating customer desires.

Where to Get Started with AI in Customer Service

If you’re looking to get started with customer support AI, this section will contain some pointers on where to begin.

Deploy AI Agents for Maximum Efficiency

The next frontier in customer service AI is ‘agents,’ which have evolved from the AI chatbot and are capable of much more flexible and open-ended behavior. Whereas a baseline large language model can generate a wide variety of outputs, agents are built to be able to pull information, hit APIs, and complete various tasks from start to finish.

Use Customer Service AI to Guide Humans and Optimize your Business Processes

AI-powered tools in customer service are changing how support teams operate by enhancing the productivity of human agents, as well as the efficiency of workflows. By providing agents with response suggestions specifically tailored to each customer’s unique needs, for instance, these tools enable agents to burn through issues more swiftly and confidently. This can be especially helpful during onboarding, where agents benefit a great deal from additional guidance as they learn the ropes.

More broadly, AI can automate many aspects of customer service and thereby streamline the support process. To take just one example, intelligent, AI-powered ticket routing can use sentiment analysis and customer intent to direct inquiries to the agent best able to resolve them.

As mentioned above, AI can also participate more directly by suggesting changes to responses and summarizing long conversations, all of which saves time. In addition to speeding up the overall support process, in other words, these optimizations make agents more efficient.

Use Voice AI for Customer Calls

Another exciting development is the rise of ‘multimodal models’ able to adroitly carry on voice-based interactions. For a long time now there have been very simple models able to generate speech, but they were tinny and artificial. No longer.

Today, these voice AI applications can quickly answer questions, are available 24/7, and are almost infinitely scalable. They have the added advantage of being able to translate between different natural languages on the fly.

Effectively use AI in Emails

In customer service, email automation involves leveraging technologies such as generative AI to automate and customize email interactions. This enhances your agents’ response speeds, increases customer satisfaction, and improves overall business efficiency. It enables businesses to handle a large number of inquiries while maintaining a high quality of customer interactions.

Given the email channel’s enduring importance, this is a prime spot to be looking at deploying AI.

Make the Most Out of Digital Channels

For a while now, people have been moving to communicating over digital channels like Facebook messenger, WhatsApp, and Apple Messages for Business, to name a few.

As with email, AI can help you automate and personalize the communications you have with customers over these digital channels, fully leveraging rich messaging and text messaging to meet your customers where they’re at.

AI can Transform your E-Commerce Operations

When you integrate AI with backend systems – like CRM or e-commerce platforms – it becomes easier to enhance upsells and cross-sells during customer support sessions (an AI agent might suggest products tailored to a customer’s previous purchases, items currently in their shopping cart, or aspects of the current conversation, for instance).

Moreover, AI can proactively deliver notifications featuring customized messages based on user activity and historical interactions, which can also increase sales and conversion rates. All of this allows you to boost profits while helping customers–everyone wins!

Things to Consider When Using AI in Customer Service

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

Augmenting Human Agents

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

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

CX Expertise

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

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

Time to Value

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

Channel Enablement

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

Security and Privacy

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

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

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

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

Observability

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

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

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

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

Risk Mitigation

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

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

AI Model Flexibility

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

What is the Future of AI in Customer Service?

This has been a high-level overview of the ways in which customer support AI can make you stand out in a crowded market. AI can help you automate routine tasks and free up agent time, personalize responses, gather insights about customers, and thoroughly optimize your internal procedures. However, you must also make sure your models are observable, your offering is flexible and dynamic, and you’re being careful with sensitive customer data.

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

10 Examples of AI Customer Service Solutions That Could Change Your Business

Posted on Michael Hartsog

From full-bore automation to multilingual speech and more, AI is already changing the way customer service works. We’ve written a lot about this over the past year, drawing on both industry statistics and our insider knowledge.

But it always helps to ground these claims with specific, real-world examples, which will be our focus today. In our judgment, there are ten domains where AI customer service helps businesses better serve their customers and improve their own profits, all of which we’ll walk through below.

Let’s get started!

What are the Ways AI can be used for Customer Service?

The following ten examples of AI in customer service are especially compelling. Read through them to see how you might use AI in your enterprise.

1. Instant, Multilingual, 24/7 Replies

Your customer service agents might require downtime, but an AI agent can operate round-the-clock. Capable of handling inquiries and resolving issues at any time of the day or night, AI agents ensure that matters are either resolved or neatly handed over to your human agents the next morning. This not only means that service is continuous, it also reduces the workload waiting for your agents while they’re getting their coffee.

Additionally, with the evolution of machine translation, it’s now possible to automatically translate between most languages, which is essential for serving a diverse, global customer base. Offering support in a customer’s native language not only improves key performance metrics like average handling time and resolution rates, but also significantly enhances customer satisfaction, demonstrating your commitment to providing a comforting, personalized experience (all this without the need to open up contact centers in each new region you operate in).

2. Automatically Sorting Emails and Tickets

Properly resolving an issue requires many steps, but one big one that must be handled up front is sorting and prioritizing incoming emails or tickets. A person could easily spend most of their day combing through communications with customers and deciding what should be handled first.

But, with AI, this is no longer required! Clever email automation can parse these incoming messages and route them to the relevant agents, boosting retention and improving your bottom line. Even better, AI agents are often good enough to solve problems directly (more on this later). Just make sure you’re following best practices when looking for an email automation for customer service platform.

3. Voice AI

Throughout this piece, we speak in general of AI agents, but one specific kind of AI worth singling out is the multimodal models able to parse voice commands and respond in kind.

On their own voice models aren’t new, but they’re now good enough to form a pillar of your customer experience strategy. Voice AI for customer experience can increase the efficiency of your operation, enhance the customer experience, and facilitate multilingual support.

4. Personalized Responses

Enhancing the customer experience by tailoring your interactions to their circumstances is easy enough to understand, but it’s far from trivial. However, a combination of advances in artificial intelligence and the vast amounts of data generated from our increasingly online lives is starting to change this picture.

However you’re reaching out to customers, people will respond better if you successfully draw on their specific data–purchase history, past interactions with your contact center, or whatever–to make it clear you’re talking to them.

Check out our guide to retrieval-augmented generation for more information.

5. Automating Content Generation

So, AI can help you personalize responses, but this is a special case of the more general fact that they can help you with content generation. Modern generative AI can create product information, summaries of calls or interactions, and even blog posts. These are huge time savers, reducing the workload for customer service teams and enabling them to handle more complex tasks.

6. AI Agents Are Handling Issues on Their Own

AI agents are great at automating routine tasks and asks, such as answering common questions or troubleshooting straightforward technical problems.

You’ll have to experiment with these tools to figure out which ones they can sort out alone, but we recommend maintaining robust checks to ensure they don’t behave in unexpected ways.

7. AI Systems are Letting Customers Solve Issues on Their Own

A related but distinct fact is that modern agents can help customers solve their own issues without the need for much oversight from agents.

AI agents can make your troubleshooting guides conversational, helping customers get their software working and guiding them through key steps while answering whatever questions come up along the way.

8. Natural Language Processing and Sentiment Analysis are Making Customers’ Feelings Clearer

There are different kinds of data, but two of the biggest categories are ‘structured’ and ‘unstructured.’ The former is the kind of thing you might find in clearly labeled columns in an Excel spreadsheet, while the latter consists of things like feedback from social media, product reviews, call transcriptions, etc.

Though unstructured data is profoundly informative, not much could be done with it until natural language processing in general – and sentiment analysis in particular – made significant strides. These techniques allow you to extract insights around how customers feel, at a much larger scale. AI agents can now automatically search for recurring issues or customer sentiment, while customer service teams can quickly respond to emerging problems and adapt in real time.

9. Predictive Analytics and Machine Learning are Helping Us Better Serve Customers

A similar idea is to use predictive analytics and machine learning. With these tools, enterprises can craft AI agents to analyze customer data to identify trends, preferences, and pain points. With enough data, for example, they might see cyclical patterns in customer buying behaviors or realize that a product feature consistently causes a certain kind of frustration.

This gives customer service teams and AI agents the ability to proactively address common issues and personalize responses (discussed above), thereby improving CSAT and other metrics by making interactions more helpful.

10. AI is Making Human Agents More Effective

We’ve made a few allusions to this already, but here we’ll make it explicit: AI agents can make your human agents much more effective.

Human agents can now use generative AI tools to help them craft responses, coach them to do their jobs better, and facilitate the automation of parts of their work. For example, Quiq’s Agent Assist offers suggested responses, agent coaching and process automation (see how it works here).

These are just a few examples, of course, but they’re enough to demonstrate the profound ways AI agents can augment (and improve) your workflows!

Leverage AI Customer Service Solutions Today

AI for customer service is among the most promising frontiers for our industry. To learn more about Quiq’s approach to customer-facing AI, click here.

These are the Most Essential Customer Service Chat Platform Types

Posted on Mark Kowal

Customer service has come a long way since the first contact centers. These days, most complaints are dealt with through a customer service platform, and those platforms are often focused on using chat to communicate.

In this piece, we’ll discuss customer service chat platforms, comparing various features you should be looking out for and how they’ll help your business. Let’s get going!

Key takeaways:

  • Customer service remains incredibly important, and there’s a ton of data to back that up.
  • More and more companies are turning to customer service platforms because they help you fit better into busy customers’ schedules, leverage advanced tools like generative AI, and provide a world-class experience.
  • When evaluating a potential platform, there are a few things you should keep in mind. It should support many different channels (from email and voice to Facebook Messenger and Wechat), it should allow you to have humans do what they’re best at and AI systems do what they’re best at, and you should be able to build a CRM, helpdesk, knowledge base, or agent workspace on top of it without too much difficulty.

Why You Should Be Using a Customer Service Chat Platform

As professionals in the customer service arena, you probably already understand why it’s important to have a dedicated customer service platform–especially when it enables chat.

Still, it’s worth pointing out how compelling the data supporting this conclusion is. High-quality customer service is a huge selling point, as 4 out of 10 customers indicate they will split with a business over bad service (this figure has been considerably higher in prior years). All told, it’s been estimated that U.S. businesses have lost as much as $1.6 trillion when customers switch after having a bad encounter with customer service.

On the other hand, the data also paints a clear picture of how valuable your reputation can be, as 68% of survey respondents have said they will select your company if you are well-known for being helpful and courteous.

How Can a Chat-Based Customer Service Platform Help?

Having said that, here are some of the high-level benefits that accrue to companies that invest in good customer service chat platforms:

  • Meeting your customers where they’re at: A good platform will give you many ways of talking to your customers, which means they can choose the option that makes the most sense given their schedules and preferences. Consult the next section for more information on customer service chat channels.
  • You can integrate with generative AI: The big story of the past few years has been the rise of large language models, with concomitant changes in how contact centers run. You’ll want to vet your platforms to make sure they’ll allow you to leverage this technology–as well as related abilities like advanced natural language processing and sentiment analysis–as it’s rapidly becoming tablestakes.
  • Personalization: One of the other significant applications of modern machine learning is tailoring content to each person’s tastes (think of how Netflix or Spotify learn what shows and music you like and recommend more of it). Using something like retrieval-augmented generation (RAG), you can draw on a customer’s prior interactions or purchases to answer their questions in a way that speaks to their unique circumstances.
  • You can gather better data for KPIs: It’s hard to know whether your strategies are working unless you have the right data. Quality customer service platforms make gathering and analyzing customer data a breeze.
  • Your agents can be more productive: Between generative AI, automation features, self-serve, and live chat, a customer service chat platform can make your agents far more effective. This acts to boost customer satisfaction and agent satisfaction at the same time.

The Main Customer Service Chat Channels–And How to Use Them

Okay, now let’s discuss some available options. There’s a lot to cover here, so we’ve chosen to break things up like this:

  • Customer service channels are the actual applications you use to talk to your customers, like voice chat, email, SMS, Apple Messages for Business, or WhatsApp.
  • Customer service modes are what we call the ways you use your channels, with the three big categories being “speaking to a human agent,” “speaking with an AI agent,” and “speaking with a mix of both.”
  • Customer service platforms are what we call products like Quiq, Zendesk, etc., that serve these capabilities through a user interface.

In the sections below, we’ll discuss all three.

The Major Customer Service Channels

  • Web chat has become a standard-issue channel for many websites. Everyone from energy companies to car dealerships has a portal on their web pages that allows you to speak with either a human or AI agent, and this is something you should offer as well.
  • SMS and rich chat are both crucial channels, given how prevalent phones have become. Many customers find they prefer the convenience of dealing with agents through text messages, as this enables asynchronous conversations that fit better into busy lives. Through multimedia messaging service (MMS), SMS can send more than text–it can handle pictures, videos, emojis, audio, buttons, carousel cards, quick replies, and more. Rich messaging supports this natively, so you have multiple options for creating engaging interactions with your customers.
  • Voice (over the phone) was once one of the dominant ways of handling customer service issues. Though it has lost a lot of ground to texting, email, and chat, it’s still worth having a phone number people can call if they need to.
  • Email is, of course, thoroughly embedded into modern life, and is a common way of communicating. You’re almost certainly already supporting email, and if you’re not, you should be.
  • WhatsApp for Business–a messaging, voice, and video-calling application managed by Meta–boasts over two billion users worldwide. Given its widespread use for texting, it has become a favored platform for businesses looking to utilize instant messaging for commercial purposes.
  • Facebook Messenger is another service Meta provides that customer-centric businesses should consider, especially due to its large user base. Furthermore, companies implementing effective automation solutions on Facebook Messenger can respond to 80% of incoming customer inquiries and attain customer satisfaction rates up to 95%.
  • Instagram Messenger is important because many members of your audience are already engaging with businesses on the widely-used Instagram platform. Additionally, its appealing API facilitates the setup of automation, enhancing the efficiency of your business.
  • Apple Messages for Business greatly enhances your customers’ access to your business by providing a “message” icon on Maps, Siri, Safari, Spotlight, or your company website, along with other contact options such as QR codes. Furthermore, the widespread popularity of Apple and its product ecosystem underscores why you should be investing in its instant messaging capabilities.
  • WeChat is an extremely popular platform in China, boasting over a billion users. Similar to the other platforms we’ve discussed, WeChat offers a Business version that enables you to interact with customers, market your services, and process payments. However, setting up a WeChat Business account requires verification of your business license. If you have a substantial customer base in China, this could be the optimal choice.
Convenient  Asynchronous Scalable AI integrations
Web chat Limited Limited Yes Yes
SMS, MMS, and Rich Messaging Yes Yes Yes Yes
Voice Limited No No (but will become more scalable as AI voice models improve, see next column) Kind of (voice models are getting good, and the best vendors already have multimodal voice support.)
Email Limited Yes Yes Yes
Messaging Application (Facebook, WhatsApp, etc.) Yes Yes Yes Yes

The Major Customer Service Modes

Now, let’s discuss the basic ways of using a customer service communication channel.

Human agents
Obviously, the original way of solving issues was to have a human manually walk through all the steps. The customer service industry remains large in part because there are many aspects of the “human touch” that cannot be automated or replaced.

This is one huge advantage of using human agents, and it’s why we’ll still need humans for a long time. The downside, of course, is that people need breaks, time off, and to sleep, or else they’ll burn out.

AI agents
Until just a few years ago, the best we could do with AI systems was build brittle, rule-based chatbots that were of limited use. That’s no longer the case, and today’s language models can handle many queries directly, or else route to the most qualified human being.

The advantages of AI agents are that they can scale almost infinitely, can work all day and night, and can almost instantly handle complex tasks like translating between different natural languages. The disadvantage of AI agents is that there are still many issues that they simply can’t handle.

A mix of both
But the real power lies in what are commonly called “centaurs,” i.e., systems combining human ingenuity and flexibility with the scalability of AI.

This will look different for different situations, but a common centaur setup is to have routine issues solved by an AI agent, and everything else sent to a human based on its content and priority. Even then, however, AI can be of enormous use. Quiq’s Human-Agent Assistants, for example, use AI to suggest replies to humans, making both the AI component and the human component of the system more effective.

This means you can allow humans and machines to play to their respective strengths, but it can take time and effort to get everything configured and running smoothly.

Human agents AI agents Centaurs
Adaptable Yes Limited Yes
Infinitely scalable No Yes No
Needs breaks Yes No Yes (the human part)

How This Figures Into Picking the Right Customer Service Chat Platform

Now, we’ll close the section by discussing customer service chat platforms like Quiq.

Today, most of these platforms offer functionality like data tracking, CRMs, various communication channels, and native support for generative AI. If you choose a good one, you’ll be able to create reports about the effectiveness of different agents, how happy your customers are on average, how long it takes you to resolve issues, etc. They should also make it easy for you to incorporate your own data sources–a knowledge base, a product catalog, an API–so that you can personalize replies across channels.

Another thing to look out for is how easy a given platform makes it to set up a helpdesk or knowledge base (or to incorporate an external one). The former allows you to track tickets and manage your agent workflows (another thing that AI agents can help with), while the latter offers resources customers can use to resolve their own problems. Both are important.

CRM  Help Desk Knowledge Base Agent workspace
Supports customer segmentation and bespoke communication Yes Yes No Yes
Gives granular data insights into customers Yes No No Yes (but only if the vendor has robust data integrations)
Facilitates multi-channel communication Yes No No Yes
Supports templates Yes Yes Yes Yes
Enables automation Yes Yes Yes Yes
Can integrate with other tools (including AI) Yes Yes Yes Yes

Getting Customer-Centric Chat Right

We’ve offered a lot of context about how to think about customer service chat platforms, but one thing we haven’t discussed is the difference between rolling your own solution vs. going with a third-party platform.

It’s a big topic, involving non-trivial tradeoffs on either side. To get up to speed as quickly as possible, check out our whitepaper!

Transforming Business with a Voice AI Platform

Posted on Mark Kowal

The CX Leaders’ Guide to Crush the Competition

As customer expectations continue to rise, businesses are under increasing pressure to provide fast, efficient, and personalized service around the clock. For CX leaders, keeping up with these demands can be challenging—especially when scaling operations while maintaining high-quality support. This is where a Voice AI platform can give you the edge you need to transform your customer service strategy.

Voice AI is a powerful technology that rapidly changes how businesses interact with their customers. From automating routine tasks to delivering personalized experiences at scale, Voice AI is truly changing the game in customer service.

This article explores how Voice AI works, why it’s more effective than traditional human agents in many areas, and the numerous benefits it offers businesses today. Whether you’re just beginning to explore Voice AI or looking to enhance your existing systems, this guide will provide valuable insights into how this technology can revolutionize your approach to customer service and help you stay ahead of the competition.

What is Voice AI and how does it work?

Voice AI refers to technology that uses artificial intelligence to understand, process, and respond to human speech. It enables machines to engage in natural, spoken conversations with users, typically using tools like automatic speech recognition (ASR), natural language processing (NLP), and text-to-speech (TTS) to convert spoken language into text, interpret intent, and generate verbal responses. Voice AI is commonly used in applications like virtual assistants, customer service, and AI agents.

A Voice AI platform is a comprehensive system that enables businesses to build, deploy, and manage voice-based interactions powered by artificial intelligence. It integrates all the technologies mentioned above into a single solution to provide tools to design conversational flows, customize voice AI agents, handle customer queries, and gather analytics to improve performance. Voice AI platforms are now being used to create virtual assistants, customer service, and contact centers to improve the customer experience and change the way customers interact with businesses.

Voice AI enables machines to understand, interpret, and respond to human speech in a natural, conversational way. Unlike the early days of chatbots and voice systems, today’s Voice AI agents are powered by advanced technologies like Large Language Models (LLMs), such as GPT and many others, which allow them to comprehend and respond to human language with impressive accuracy.

LLMs are trained on massive amounts of data, allowing them to recognize patterns in speech, understand different languages and dialects, and predict what a user asks—even if the question is phrased unexpectedly. This is a major leap from traditional, rules-based systems, which required rigid, predefined scripts to function. Now, Voice AI agents can understand intent and context, making conversations feel much more natural and intuitive.

When a customer speaks to a Voice AI agent, the process begins with Automatic Speech Recognition (ASR), which converts spoken language into text. Once the words are captured, Natural Language Processing (NLP) kicks in to interpret the meaning behind the words, analyzing context and intent to determine the best response. From there, the system generates a response using the LLM’s understanding of language, and finally, the text is converted back into speech with Text-to-Speech (TTS) technology. All this happens in real time through a conversational voice AI platform, allowing the customer to interact with the AI as if they were speaking to a human agent.

For CX leaders, this changes everything for your customers. Voice AI agents don’t just hear words—they understand them. This allows you to handle a wide range of customer inquiries, from simple requests like checking order status to more complex tasks such as troubleshooting issues or answering product questions. And because these AI agents constantly learn from each interaction, they continue to improve over time, becoming more efficient and effective with each use.

How Voice AI compares to human agents

One of the most common questions CX leaders ask is how Voice AI compares to human agents. While it’s true that AI agents can’t fully replace the human touch in all interactions, they offer several key advantages that are transforming customer service for the better.

1. Consistency and speed

Unlike human agents, who may vary in their responses or make mistakes, Voice AI agents provide consistent answers every time—as long as they have appropriate guardrails in place to prevent hallucinations. Without these safeguards, AI can generate misinformation and fail to meet customer needs. Properly trained AI agents, equipped with the necessary guardrails, can instantly access vast amounts of information and handle inquiries quickly, making them ideal for routine or frequently asked questions. This ensures that customers receive fast, accurate responses without the need to wait on hold or navigate through multiple layers of human interaction.

2. 24/7 availability

One of the biggest benefits of Voice AI is that it’s available around the clock. Whether it’s the middle of the night or during peak business hours, AI agents are always on, ready to assist customers whenever they need help. This is especially useful for global businesses that operate in different time zones, ensuring customers can access support without delay, no matter where they are.

3. Scalability

Another advantage of Voice AI agents is their ability to scale. Unlike human agents, who can only handle one conversation at a time, AI agents can manage thousands of interactions simultaneously. This makes them particularly valuable during busy periods, such as holidays or product launches, when call volumes can surge. Instead of overwhelming your team, Voice AI ensures that all customers receive the same high level of service, even during high-demand times.

Where human agents excel

Of course, there are still areas where human agents outperform AI. Empathy and emotional intelligence are crucial in customer service, especially when dealing with complex or sensitive issues.

While AI agents can empathize with a user who expresses emotion, they are limited in their ability to interpret those emotions, and lack the personal touch that human agents excel at. Similarly, when faced with complex problem solving that requires out-of-the-box thinking, a human agent’s creativity and judgment are often more effective.

For these reasons, many businesses find that a hybrid approach works best—using Voice AI to handle routine or straightforward tasks, while allowing human agents to focus on more complex or emotionally charged interactions. This not only ensures that customers receive the right level of support, but also frees up human agents to do what they do best: solve problems and connect with customers on a personal level.

5 big business impacts of Voice AI

Now that we’ve covered how Voice AI works and compares to human agents, let’s review the specific benefits it offers businesses. From cost savings to enhanced customer experiences, Voice AI is transforming the way companies approach customer service.

1. Increased efficiency and reduced costs

One of the most significant advantages of using Voice AI is the ability to automate routine tasks. Instead of relying on human agents to handle simple inquiries—such as checking an order status, answering frequently asked questions, or processing payments—AI agents can manage these tasks automatically. This reduces the workload for human agents, allowing them to focus on more strategic or complex issues.

As a result, businesses can operate with smaller customer service teams, reducing labor costs and maintaining high levels of service. This not only saves money, but also improves efficiency, as AI agents can handle repetitive tasks faster and more accurately than humans.

2. Scalability and availability

As mentioned earlier, Voice AI offers unmatched scalability. Whether you’re dealing with a sudden spike in customer inquiries or operating across multiple time zones, Voice AI agents ensure no customer is left waiting. They can manage unlimited interactions simultaneously, providing the same level of service to every customer, regardless of demand.

In addition, because Voice AI operates 24/7, businesses no longer need to worry about staffing for off-hours or paying overtime for extended support. This around-the-clock availability ensures that customers can access help whenever they need it, improving overall satisfaction and reducing wait times.

3.  Enhanced customer experience

One of the most important factors in customer service is the customer experience, and Voice AI has the potential to dramatically improve it. By offering quick, consistent responses, Voice AI agents eliminate the frustration that comes with long wait times and inconsistent answers from human agents.

Voice AI can also deliver personalized interactions by integrating with CRM systems and accessing customer data. This allows the AI to address customers by name, understand their preferences, and provide tailored solutions based on their history with the company. The result is a more engaging and satisfying customer experience that leaves customers feeling valued and understood.

4. Multilingual support

For businesses with different cultural customers, Voice AI offers another important advantage: multilingual support. Many Voice AI systems are equipped to handle multiple languages, making it easier for companies to support customers around the world. Voice AI can detect if your customer is speaking another language and translate their response instantaneously. This extraordinarily personalized service can transform your customer’s interactions and prevent many of the issues that come with language barriers. This not only improves accessibility, but also enhances the overall customer experience, as customers can interact with the company in their preferred language.

5. Improved data collection and insights

In addition to its customer-facing benefits, Voice AI also provides businesses with valuable insights into customer behavior. Because AI agents record and analyze every interaction, companies can use this data to identify trends, spot recurring issues, and improve their products or services based on customer feedback.

By understanding what customers are asking for and where they’re encountering problems, businesses can refine their customer support strategy, improve AI performance, and even identify areas where additional human intervention may be needed. This data-driven approach allows CX leaders to make more informed decisions and continuously improve their customer service operations.

Voice AI for CX is just getting started

Looking ahead, the future of Voice AI is full of exciting possibilities. As technology continues to advance, the gap between human and AI interactions will continue to narrow, with Voice AI agents becoming even more capable of handling complex and nuanced conversations.

Future developments in emotional intelligence and predictive capabilities will allow AI agents to not only understand what customers say, but also anticipate what they need before they even ask.

For CX leaders, staying ahead of these developments is crucial. Businesses that invest in a Voice AI platform will be well-positioned to reap the benefits of these advancements as they continue to evolve. By embracing Voice AI as part of a hybrid approach, companies can create a customer service model that combines the efficiency and scalability of AI with the empathy and creativity of human agents.

Voice AI is a game-changer for CX leaders

The rise of Voice AI revolutionizes how businesses approach customer service, offering scalable, cost-effective, and personalized solutions that were once only possible with large teams of human agents. From automating routine tasks to providing real-time, tailored experiences, Voice AI is reshaping customer interactions in ways that improve efficiency and satisfaction.

For CX leaders, the time to embrace Voice AI is now. As this technology continues to evolve, it will become an even more powerful tool for delivering superior customer experiences, optimizing operational processes, and driving long-term success. By integrating Voice AI agents into your customer service strategy, you can balance the speed and consistency of AI with the empathy and creativity of human agents—building a support system that meets the ever-growing demands of today’s customers.

Voice AI is not just a trend, it’s the future of customer service. Staying ahead of the curve now will ensure your business remains competitive in a world where customer expectations continue to rise, and the need for seamless, personalized interactions becomes even more critical.

How to Improve Contact Center Performance (With Data)

Posted on Michael Hartsog

Contact centers are a crucial part of offering quality products. Long after the software has been built and the marketing campaigns have been run, there will still be agents helping customers reset their passwords and debug tricky issues.

This means we must do everything we can to ensure that our contact centers are operating at peak efficiency. Data analytics is an important piece of the puzzle, offering the kinds of hard numbers we need to make good decisions, do right by our customers, and support the teams we manage.

That will be our focus today. We’ll cover the basics of implementing a data analysis process, as well as how to use it to assess and improve various contact center performance metrics.

Let’s get going!

How to Use Data Analytics to Increase Contact Center Performance

A great place to start is with a broader overview of the role played by data analytics in making decisions in modern contact centers. Here, we’ll cover the rudiments of how data analytics works, the tools that can be used to facilitate it, and how it can be used in making critical decisions.

Understanding the Basics of Data Analytics in Contact Centers

Let’s define data analytics in the context of contact center performance management. Like the term “data scientist”—which could cover anything from running basic SQL queries to building advanced reinforcement learning agents—“data analytics” is a nebulous term that can be used in many different conversations and contexts.

Nevertheless, its basic essence could be summed up as “using numbers to make decisions.”

If you’re reading this, the chances are good that you have a lot of experience in contact center performance management already, but you may or may not have spent much time engaging in data analytics. If so, be aware that data analysis is an enormously powerful tool, especially for contact centers.

Imagine, for example, a new product is released, and you see a sudden increase in average handle time. This could mean there is something about it that’s especially tricky or poorly explained. You could improve your contact center performance metrics simply by revisiting that particular product’s documentation to see if anything strikes you as problematic.

Of course, this is just a hypothetical scenario, but it shows you how much insight you can gain from even rudimentary numbers related to your contact center.

Implementing Analytics Tools and Techniques

Now, let’s talk about what it takes to leverage the power of contact center performance metrics. You can slice up the idea of “analytics tools and techniques” in a few different ways, but by our count, there are (at least) four major components.

Gathering the Data

First, like machine learning, analytics is “hungry,” meaning that it tends to be more powerful the more data you have. For this reason, you have to have a way of capturing the data needed to make decisions.

In the context of contact center performance, this probably means setting up a mechanism for tracking any conversations between agents and customers, as well as whatever survey data is generated by customers reflecting on their experience with your company.

Storing the Data

This data has to live somewhere, and if you’re dealing with text, there are various options. “Structured” textual data follows a consistent format and can be stored in a relational database like MySQL. “Unstructured” textual data may or may not be consistent and is best stored in a non-relational database like MongoDB, which is better suited for it.

It’s not uncommon to have both relational and non-relational databases for storing specific types of data. Survey responses are well-structured so they might go in MySQL, for instance, while free-form conversations with agents might go in MongoDB. There are also more exotic options like graph databases and vector databases, but they’re beyond the scope of this article.

Analyzing the Data

Once you’ve captured your data and stored it somewhere, you have to analyze it—the field isn’t called data analytics for nothing! A common way to begin analyzing data is to look for simple, impactful, long-term trends—is your AHT going up or down, for instance? You can also look for cyclical patterns. Your AHT might generally be moving in a positive direction, but with noticeable spikes every so often that need to be explained and addressed.

You could also do more advanced analytics. After you’ve gathered a reasonably comprehensive set of survey results, for example, you could run them through a sentiment analysis algorithm to find out the general emotional tone of the interactions between your agents and your customers.

Serving Up Your Insights

Finally, once you’ve identified a set of insights you can use to make decisions about improving contact center performance, you need to make them available. By far the most common way is by putting some charts and graphs in a PowerPoint presentation and delivering it to the people making actual decisions. That said, some folks opt instead to make fancy dashboards, or even to create monitoring tools that update in real time.

Effectively Leveraging Data

As you can see, creating a top-to-bottom contact center performance solution takes a lot of effort. The best way to save time is to find a tool that abstracts away as much of the underlying technical work as possible.

Ideally, you’d be looking for quick insights generated seamlessly across all the many messaging channels contact centers utilize these days. It’s even better if those insights can easily be published in reports that inform your decision-making.

What’s the payoff? You’ll be able to scrutinize (and optimize) each step taken during a customer journey, and discover how and why your customers are reaching out. You’ll have much more granular information about how your agents are functioning, giving you the tools needed to improve KPIs and streamline your internal operations.

We’ll treat each of these topics in the remaining sections, below.

How to Improve KPIs in Contact Center

After gathering and analyzing a lot of data, you’ll no doubt notice key performance indicators (KPIs) that aren’t where you want them to be. Here, we’ll discuss strategies for getting those numbers up!

Identifying Key Performance Indicators (KPIs)

First, let’s briefly cover some of the KPIs you’d be looking for.

  • First Contact Resolution (FCR) – The first contact resolution is the fraction of issues a contact center is able to resolve on the first try, i.e. the first time the customer reaches out.
  • Average Handle Time (AHT) – The average handle time is one of the more important metrics contact centers track, and it refers to the mean length of time an agent spends on a task (this includes both talking to customers directly and whatever follow-up work comes after).
  • Customer Satisfaction (CSAT) – The customer satisfaction score attempts to gauge how customers feel about your product and service.
  • Call Abandon Rate (CAR) – The call abandon rate is the fraction of customers who end a call with an agent before their question has been answered.
  • Net Promoter Score (NPS) – The net promoter score is a number (usually from 1-10) that quantifies how likely a given customer would be to recommend you to someone they know.

Of course, this is just a sampling of the many contact center performance metrics you can track. Ultimately, you want to choose a set of metrics that gives you a reasonably comprehensive view of how well your contact center is doing, and whether it’s getting better or worse over time.

Strategies for Improving Key KPIs

There are many things you can do to improve your KPIs, including up-training your personnel or making your agents more productive with tools like generative AI.

This is too big a topic to cover comprehensively, but since generative AI is such a hot topic let’s walk through a case study where using it led to dramatic improvements in efficiency.

LOOP is a Texas-based car insurance provider that partnered with Quiq to deploy a generative AI assistant. Naturally, they already had a chatbot in place, but they found it could only offer formulaic answers. This frustrated customers, prevented them from solving their own problems, and negatively impacted KPIs overall.

However, by integrating a cutting-edge AI assistant powered by large language models, they achieved a remarkable threefold increase in self-service rates. By the end, more than half of all customer issues were resolved without the need for agents to get involved, and fully three-quarters of customers indicated that they were satisfied with the service provided by the AI.

Now, we’re not suggesting that you can solve every problem with fancy new technology. No, our point here is that you should evaluate every option in an attempt to find workable contact center performance solutions, and we think this is a useful example of what’s possible with the right approach.

Tips to Boost Contact Center Operational Efficiency

We’ve covered a lot of ground related to data analysis and how it can help you make decisions about improving contact center performance. In this final section, we’ll finish by talking about using data analytics and other tools to make sure you’re as operationally efficient as you can be.

Streamlining Operations with Technology

The obvious place to look is technology. We’ve already discussed AI assistants, but there’s plenty more low-hanging fruit to be picked.

Consider CRM integrations, for example. We’re in the contact center business, so we know all about the vicissitudes of trying to track and manage a billion customer relationships. Even worse, the relevant data is often spread out across many different locations, making it hard to get an accurate picture of who your customers are and what they need.

But if you invest in solutions that allow you to hook your CRM up to your other tools, you can do a better job of keeping those data in sync and serving them up where they’ll be the most use. As a bonus, these data can be fed to a retrieval augmented generation system to help your AI assistant create more accurate replies. They can also form a valuable part of your all-important data analytics process.

What’s more, these same analytics can be used to identify sticking points in your workflows. With this information, you’ll be better equipped to rectify any problems and keep the wheels turning smoothly.

Empowering Agents to Enhance Performance

We’ve spent a lot of time in this post discussing data analytics, AI, and automation, but it’s crucial not to forget that these things are supplements to human agents, not replacements for them. Ultimately, we want agents to feel empowered to utilize the right tools to do their jobs better.

First, to the extent that it’s possible (and appropriate), agents should be given access to the data analytics you perform in the future. If you think you’re making better decisions based on data, it stands to reason that they would do the same.

Then, there are various ways of leveraging generative AI to make your agents more effective. Some of these are obvious, as when you utilize a tool like Quiq Snippets to formulate high-quality replies more rapidly (this alone will surely drop your AHT). But others are more out-of-the-box, such as when new agents can use a language model to get up to speed on your product offering in a few days instead of a few weeks.

Continuously Evaluating and Refining Processes

To close out, we’ll reiterate the importance of consistently monitoring your contact center performance metrics. These kinds of numbers change in all sorts of ways, and the story they tell changes along with them.

It’s not enough to measure a few KPIs and then call it a day, you need to have a process in place to check them consistently, revising your decisions along the way.

Next Steps for Improving Your Contact Center Metrics

They say that data is the new oil, as it’s a near-inexhaustible source of insights. With the right data analysis, you can figure out which parts of your contact center are thriving and which need more support, and you can craft strategies that set you and your teams up to succeed.

Quiq is well-known as a conversational AI platform, but we also have a robust suite of tools for making the most out of the data generated by your contact center. Set up a demo to figure out how we can give you the facts you need to thrive!

Request A Demo

WhatsApp Business: A Guide for Contact Center Managers

Posted on The Quiq Team

In today’s digital era, businesses continually seek innovative ways to connect with their customers, striving to enhance communication and foster deeper relationships. Enter WhatsApp Business – a game-changer in the realm of digital communication. This powerful tool is not just a messaging app; it’s a bridge between businesses and their customers, offering a plethora of features designed to streamline communication, improve customer service, and boost engagement. Whether you’re a small business owner or part of a global enterprise, understanding the potential of WhatsApp Business could redefine your approach to customer communication.

What is Whatsapp Business?

WhatsApp is an application that supports text messaging, voice messaging, and video calling for over two billion global users. Because it leverages a simple internet connection to send and receive data, WhatsApp users can avoid the fees that once made communication so expensive.

Since WhatsApp already has such a large base of enthusiastic users, many international brands have begun leveraging it to communicate with their own audiences. It also has a number of built-in features that make it an attractive option for businesses wanting to establish a more personal connection with their customers, and we’ll cover those in the next section.

What Features Does WhatsApp Business Have?

In addition to its reach and the fact that it reduces the budget needed for communication, WhatsApp Business has additional functionality that makes it ideal for any business trying to interact with its customers.

When integrated with a tool like the Quiq conversational AI platform, WhatsApp Business can automatically transcribe voice-based messages. Even better, WhatsApp Business allows you to export these conversations later if you want to analyze them with a tool like natural language processing.

If your contact center agents and the customers they’re communicating with have both set a “preferred language,” WhatsApp can dynamically translate between these languages to make communication easier. So, if a user sends a voice message in Russian and the agent wants to communicate in English, they’ll have no trouble understanding one another.

What are the Differences Between WhatsApp and WhatsApp Business?

Before we move on, it’s worth pointing out that WhatsApp and WhatsApp Business are two different services. On its own, WhatsApp is the most widely used messaging application in the world. Businesses can use WhatsApp to talk to their customers, but with a WhatsApp Business account, they get a few extra perks.

Mostly, these perks revolve around building brand awareness. Unlike a basic WhatsApp account, a WhatsApp Business account allows you to include a lot of additional information about your company and its services. It also provides a labeling system so that you can organize the conversations you have with customers, and a variety of other tools so you can respond quickly and efficiently to any issues that come up.

The Advantages of WhatsApp Messaging for Businesses

Now, let’s spend some time going over the myriad advantages offered by a WhatsApp outreach strategy. Why, in other words, would you choose to use WhatsApp over its many competitors?

Global Reach and Popularity

First, we’ve already mentioned the fact that WhatsApp has achieved worldwide popularity, and in this section, we’ll drill down into more specifics.

When WhatsApp was acquired by Meta in 2014, it already boasted 450 million active users per month. Today, this figure has climbed to a remarkable 2.7 billion, but it’s believed it will reach a dizzying 3.14 billion as early as 2025.

With over 535 million users, India is the country where WhatsApp has gained the most traction by far. Brazil is second with 148 million users, and Indonesia is third with 112 million users.

The gender divide among WhatsApp users is pretty even – men account for just shy of 54% of WhatsApp users, so they have only a slight majority.

The app itself has over 5 billion downloads from the Google Play store alone, and it’s used to send 140 billion messages each day.

These data indicate that WhatsApp could be a very valuable channel to cultivate, regardless of the market you’re looking to serve or where your customers are located.

Personalized Customer Interactions

Firstly, platforms like WhatsApp enable businesses to customize communication with a level of scale and sophistication previously unavailable.

This customization is powered by machine learning, a technology that has consistently led the charge in the realm of automated content personalization. For example, Spotify’s ability to analyze your listening patterns and suggest music or podcasts that match your interests is powered by machine learning. Now, thanks to advancements in generative AI, similar technology is being applied to text messaging.

Past language models often fell short in providing personalized customer interactions. They tended to be more “rule-based” and, therefore, came off as “mechanical” and “unnatural.” However, contemporary models greatly improve agents’ capacity to adapt their messages to a particular situation.

While none of this suggests generative AI is going to entirely take the place of the distinctive human mode of expression, for a contact center manager aiming to improve customer experience, this marks a considerable step forward.

Below, we have a section talking a little bit more about integrating AI into WhatsApp Business.

End-to-End Encryption

One thing that has always been a selling point for WhatsApp is that it takes security and privacy seriously. This is manifested most obviously in the fact that it encrypts all messages end-to-end.

What does this mean? From the moment you start typing a message to another user all the way through when they read it, the message is protected. Even if another party were to somehow intercept your message, they’d still have to crack the encryption to read it. What’s more, all of this is enabled by default – you don’t have to spend any time messing around with security settings.

This might be more important than you realize. We live in a world increasingly beset by data breaches and ransomware attacks, and more people are waking up to the importance of data security and privacy. This means that a company that takes these aspects of its platform very seriously could have a leg up where building trust is concerned. Your users want to know that their information is safe with you, and using a messaging service like WhatsApp will help to set you apart.

Scalability

Finally, WhatsApp’s Business API is a sophisticated programmatic interface designed to scale your business’s outreach capabilities. By leveraging this tool, companies can connect with a broader audience, extending their reach to prospects and customers across various locations. This expansion is not just about increasing numbers; it’s about strategically enhancing your business’s presence in the digital world, ensuring that you’re accessible whenever your customers need to reach out to you.

By understanding the value WhatsApp’s Business API brings in reaching and engaging with more people effectively, you can make an informed decision about whether it represents the right technological solution for your business’s expansion and customer engagement strategies.

Enhancing Contact Center Performance with WhatsApp Messaging

Now, let’s turn our attention to some of the concrete ways in which WhatsApp can improve your company’s chances of success!

Improving Response and Resolution Metrics Times

Integrating technologies like WhatsApp Business into your agent workflow can drastically improve efficiency, simultaneously reducing response times and boosting customer satisfaction. Agents often have to manage several conversations at once, and it can be challenging to keep all those plates spinning.

However, a quality messaging platform like WhatsApp means they’re better equipped to handle these conversations, especially when utilizing tools like Quiq Compose.

Additionally, less friction in resolving routine tasks means agents can dedicate their focus to issues that necessitate their expertise. This not only leads to more effective problem-solving, it means that fewer customer inquiries are overlooked or terminated prematurely.

Integrating Artificial Intelligence

According to WhatsApp’s own documentation, there’s an ongoing effort to expand the API to allow for the integration of chatbots, AI assistants, and generative AI more broadly.

Today, these technologies possess a surprisingly sophisticated ability to conduct basic interactions, answer straightforward questions, and address a wide range of issues, all of which play a significant role in boosting customer satisfaction and making agents more productive.

We can’t say for certain when WhatsApp will roll out the red carpet for AI vendors like Quiq, but if our research over the past year is any indication, it will make it dramatically easier to keep customers happy!

Gathering Customer Feedback

Lastly, an additional advantage to WhatsApp messaging is the degree to which it facilitates collecting customer feedback. To adapt quickly and improve your services, you have to know what your customers are thinking. And more specifically, you have to know the details about what they like and dislike about your product or service.

In the Olde Days (i.e. 20 years ago year, or so), the only real way to do this was by conducting focus groups, sending out surveys – sometimes through the actual mail, if you can believe it – or doing something similarly labor-intensive.

Today, however, your customers are almost certainly walking around with a smartphone that supports text messaging. And, since it’s pretty easy for them to answer a few questions or dash off a few quick lines describing their experience with your service, odds are that you can gather a great deal of feedback from them.

Now, we hasten to add that you must exercise a certain degree of caution in interpreting this kind of feedback, as getting an accurate gauge of customer sentiment is far from trivial. To name just one example, the feedback might be exaggerated in both the positive and negative direction because the people most likely to send feedback via text messaging are the ones who really liked or really didn’t like you.

That said, so long as you’re taking care to contextualize the information coming from customers, supplementing it with additional data wherever appropriate, it’s valuable to have.

Wrapping Up

From its global reach and popularity to the personalized customer interactions it facilitates, WhatsApp Business stands out as a powerful solution for businesses aiming to enhance their digital presence and customer engagement strategies. By leveraging the advanced features of WhatsApp Business, companies can avail themselves of end-to-end encryption, enjoy scalability, and improve contact center performance, thereby positioning themselves at the forefront of the contact center game.

And speaking of being at the forefront, the Quiq conversational CX platform offers a staggering variety of different tools, from AI assistants powered by language models to advanced analytics on agent performance. Check us out or schedule a demo to see what we can do for your contact center!

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!

Request A Demo