Customer Experience AI: Elevating Call Center Operations

Contact centers are finding new ways of elevating the customer experience with AI, and the pace of innovation is only going to quicken as comfort levels rise.

Customer experience is the lead measure of contact center success, so we naturally direct a lot of time and resources toward trying to improve it.

As we think about the customer journey, though, it’s easy to focus mostly on the point of contact between the customer and agent, on the quality of the human-on-human interaction. Did the agent say the right things at the right time? Were they empathetic? Did they resolve the customer issue correctly, and was it all handled in a timely manner?

While it's right to ask these questions, the answers identify symptoms of a successful or sub-par customer experience. They don’t directly address the cause - the underlying machinery customers never see and probably don’t even know exists, yet it’s pivotal to their experience.

It’s in the machinery of customer experience – Scheduling, Quality Management and Conversation Analytics - where human capabilities take a back seat to the transformational power of artificial intelligence, generative AI, machine learning and automation.

Call centers that leverage AI have a powerful CX differentiator at their disposal.


Elevating Customer Experience with AI: A Deep Dive into Contact Center Success


  • What if, with the single keystroke, AI could produce an agent schedule fully optimized your agent resources, taking into consideration the full range of variables, from an agent’s skills to their availability?


  • What if, by employing machine learning, you could improve your demand forecast accuracy with every iteration?


  • What if AI could review and analyze 100% of the calls your contact center handles every day?


  • What if AI could identify customers most at risk of moving to a competitor by monitoring for keywords or phrases and analyzing their speech for sentiment and emotional intensity.


These are just a few customer experience-related areas where using AI makes an unseen (by the customer) but real impact. By elevating the contact center’s operational efficiency and effectiveness AI enables managers to better fulfill their organization's obligation to the customer.


Customer Experience AI: Forecasting and Scheduling


Most customers will tell you they judge the quality of their experience on two basic criteria: "Was my issue resolved to my satisfaction?" and "How long did it take?".

Your call center’s ability to forecast customer demand and schedule agent staff accordingly impacts how the customer answers those questions. But, we all know forecasting and scheduling isn't a simple task.

Scheduling is time-consuming and complex. It’s a data-heavy, variable-driven exercise, and few call centers have the budget for a dedicated scheduling staff. And even if they do, a schedule created by human beings is, by definition, subject to human error and inevitably suboptimal.

Schedules optimized by AI – which can create thousands of iterations built on countless scenarios and assumptions in seconds - ensure qualified agents are in the right seats and available to interact with the customer in a timely manner. AI can build shift templates and forecasts that solve for variables, like:

  • Multi-skilled agents
  • Agent break frequencies and durations
  • Agent working hours and shift durations
  • Agent vacations
  • Unplanned events, like sick days
  • Demand forecasts
  • Channel assignments (voice, chat, email)

An AI-driven Auto Scheduling tool will tirelessly test all possible data permutations – and learn - until it develops the best possible schedule. What does that mean for the customer experience? It means they’re not waiting and they’re talking to the agents best suited to resolve their problem or question.

Customer Experience AI: Quality Management


AI is equally pivotal in Quality Management, where customer attitudes and sentiment are identified and agent performance is analyzed, graded and used to inform agent training. Within the actual agent/customer interaction – the call – lies a treasure trove of insights. Call center managers need to access and use those insights to improve customer experience.

Without AI, the biggest challenge is the number of call recordings managers can physically listen to. They’ll be lucky to carve out enough time in a month to thoroughly evaluate a few calls per agent…one to two percent of all calls coming into the contact center. The decisions they make based on such a small (and probably random) sample size are inevitably going to be compromised. And what about the decisions they can’t make because they simply don’t have enough information?

Generative AI-driven Auto Quality Management and Speech Analytics tools will not only automatically review 100% of the customer/agent interactions, they’ll expose decision-making insights that simply are not accessible to call centers fully reliant on their managers’ limited capabilities. It’s not a sign of weakness to admit humans aren’t as exacting, thorough and efficient as these advanced technologies.

Ironically, it’s AI-fueled Speech Analytics tools that enable call centers to mine every one of those calls for intel on decidedly human emotions. By analyzing conversations for attributes like voice-tone, cross-talk, silence, volume, keywords and phrases and more, this tool can identify the nuances and character of a conversation, such as whether a customer or agent was angry, frustrated or happy. Particular words and phrases can be flagged so managers will know if an agent used a required greeting or drifted away from the recommended script.

AI-driven Auto Call Summarization can take that burden from agents and free them for the next customer call. How many more customer interactions could your agents have if they didn’t have to interrupt their flow to summarize their previous call. Could that shorten every customer’s wait time? You bet it could.

AI-driven tools not only enhance the customer experience but also provide secure handling of customer data, ensuring trust and compliance with regulatory requirements.


Customer Experience AI: Preventing Customer Churn


You could argue that, at their core, call centers are in the revenue protection business. They are the hub of customer service and the venue where customer loyalty can be won or lost. That’s why every call center manager should want to identify negative interactions as quickly as possible – in order to identify disgruntled customers and proactively work to repair the relationship and prevent customer churn.

With AI’s ability to review and analyze 100% of the interactions moving through the call center, the Speech Analytics technology can be set up to flag certain words that may indicate customer dissatisfaction (perhaps a competitor’s brand name, or a phrase like "I'm not getting my money's worth...") and alert managers so they look deeper into interactions containing that word and take action to salvage a customer relationship.

By integrating AI, call centers can now understand customer needs in real-time, improve customer interactions, and ensure a superior employee experience.


Call centers operate in a world where customer experience is king. AI is transforming the quality of that experience and the way it’s delivered, improving it in ways the customers may not see, but call center managers and decision-makers certainly can. Put simply, the technology is making it easier to keep customers happy, and there’s nothing wrong with that. The time to embrace it is now.

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