AI Alone Won’t Solve Your Customer Experience Problems, but It Will Expose Them


Companies are looking to AI as the ultimate solution to their customer service problems, but the technology’s real power lies in the flaws it exposes to the assumptions you’ve made. The first step in any effective AI implementation is pinpointing bottlenecks and data inefficiencies, says Chip Kahn, Founder & CEO, Boomtown.

The most common problem in customer service — when employees don’t have the information they need to assist customers — is often the most misunderstood. We call this the “information gap” at my company. How can something so seemingly simple be such a widespread problem?

It’s because the world changes and the pace of change is accelerating. For instance, software releases are now happening at a faster rate than many would have ever imagined. One 2020 studOpens a new window yOpens a new window conducted by the Cloud Native Computing Foundation found that “respondents with daily release cycles increased from 15% in 2018 to 27%, and weekly release cycles increased from 20% to 28%.”

When Car and DriverOpens a new window tested the Tesla Model 3, they reported a bevy of software updates in just the first half of their long-term test, with twelve software updates in just six months, averaging out to an update every 16 days. Imagine being in customer service at Tesla, having to verify the firmware and software versions of each customer’s vehicle before finding the right fix, all while knowing your decisions could affect the physical safety of that customer.

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Customer experience teams simply can’t keep up with the dizzying pace of change to products and services. We now live in a world where yesterday’s information is no longer relevant or accurate just 24 hours later. The result is that employees need to develop superhuman abilities to find information, which is not only unfeasible… it’s unscalable.

A customer service interaction is merely one touchpoint in a customer journey, but it’s the example that weighs most heavily on the customer experience teams I meet with. Why? Because customer-employee interactions are the canary in the coal mine. They are the first indicator that something is wrong with the customer experience.

But what if you don’t hear the canary?

AI Is More Than Automation

To ensure you don’t miss crucial customer experience warnings, you first need to ask: What are the primary causes of the customer service information gap?

  • The information doesn’t exist in employees’ systems
  • The information is too hard (or impossible) to find in employees’ systems, or
  • The information in the system is inaccurate or incomplete

These are all problems that fundamentally undermine the customer experience. And while employees experience these problems repeatedly throughout every workday, they have limited means to track, classify, and then solve them. After all, imagine trying to capture these insights manually from a department of 500 or 1000 employees distributed across the globe, all while you’re simultaneously trying to improve time-to-resolution.

Because a manual lift is impossible, many companies turn to AI. For example, a 1,000-person team uses AI to instantly bring up the relevant information for the employee to assist the customer with their specific problem. What happens when the AI can’t find relevant information? The information dead-end is logged in the system and reported back to the management team. No manual effort is required, the employee does not have to take additional action, and the reporting can be done at scale, allowing management to identify the problematic gaps in their knowledge systems.

If the AI is delivering information, say a knowledge base article, that is incomplete, you’ll have analytics showing that customers who are provided this information ultimately have to call back in for additional support, instantly exposing the problematic article.

In this scenario, AI is automating information discovery, which has immediate benefits for time-to-resolution and allows the employee to focus on listening to and engaging the customer. It’s a win-win-win for the company, customer experience teams, and the customer.

But this type of automation doesn’t solve the information gap problem, does it? In fact, automation may actually reinforce the problem, creating an endless loop where the customer is repeatedly served incomplete information.

Fortunately, AI is more than just automation. Its insights and the data the AI system generates and captures will expose the problem. The value of real-time intelligence is self-evident to most business leaders, but it’s almost never talked about in conversations about AI strategy.

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Focus On Experience Delivery

AI alone cannot solve your customer experience problems, but it’s certainly part of the solution. It exposes the problem, and from there, other parts of the solution, including people, processes, journey mapping and more, can be pulled in. The orchestration of this multifaceted solution is what I call experience delivery.

Sometimes an experience is delivered by a person, sometimes by an AI, sometimes by a static website. The channel or modality of an exceptional experience matters less than the successful delivery of that experience.

When leaders focus on delivering great experiences across the entire customer journey, it becomes very easy to identify which resources are needed and what process will best serve the customer.

Ask yourself this: what problem are you solving, and what goal will the solution serve? In the information gap example, we had several choices. If our goal was to streamline workflows for customer experience teams, we might choose to merely add the information needed to the knowledge base. If our goal was to drive down the cost of customer support, we might choose to automate several processes in customer interaction. But if our goal were to deliver exceptional customer experiences, we would choose a multifaceted solution that focused on outcomes for the customer along the entire journey.

A relentless focus on experience delivery isn’t just a “customer-first” mentality. Great customer experiences drive NPS scores, customer loyalty, repeat business and referrals. In this year’s IBM CEO StudyOpens a new window , the distinction between measuring experiences and delivering experiences could not have been more stark: “When asked where technology would have the greatest impact over the next two to three years, customer-focused Underperformers cited consumer insights. Yet for outperformers, the by-far dominant answer was consumer experience. The lagging organizations look to data for competitive clues. They collect data and use it to give consumers what they ask for. Outperformers take it one giant step further. They are proactive in how they apply data, using it to emphasize engagement.”

Sometimes you’ll use AI to deliver a customer experience, sometimes an employee; other times, you might even use an older piece of technology. What matters most is that you’re delivering an exceptional experience. Whatever you do, just don’t expect AI to do all the work for you.

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