This week, we were thrilled to participate in CCW’s Modernizing Customer Experiences with AI & Digital event. In case you missed it, below we’ve recapped the Executive Roundtable session from Tuesday afternoon featuring our own founder & CEO George Davis, Osman Javed, Head of Product Marketing at Cresta, and Frank Golden, Business Development at Airkit.
Here at Frame AI, we automatically measure customer sentiment and effort and extract actionable themes from every interaction to help CX leaders activate feedback that moves the needle for their customers and their business. At Cresta, Osman and his team provide expertise AI to contact centers to help improve agent performance. At Airkit, Frank and his team offer a low-code customer experience platform that facilitates self-service digital customer experiences.
CCW Principal Analyst Brian Cantor moderated the discussion about using AI to scale great customer experiences by capturing customer intent, improving agent performance, and orchestrating the right set of touchpoints. Here are our top three takeaways:
Change Management Is a Core CX Competency
The discussion kicked off with some context about how CX organizations are weathering change management. Whether you’re playing catch-up following a particularly tumultuous past year or executing a mandate to implement AI and digital transformation in your CX strategy, change management is a critical core competency for any CX team. CX plays a mission-critical role in synthesizing changes that affect customer relationships and the impact of those changes on the business at large. Each panelist shared their perspective on how CX teams can rise to meet change management challenges effectively.
George reflected on CX leaders’ increased urgency to improve how effectively they respond to shifting customer expectations. “Once the fog started to clear in Q4/Q1, people started retrospecting around, ‘how did we do as an organization with change management? How well did we learn what’s new about our customers and how well did we react to it?’”
But most importantly, “When the next change happens in our customer base, how soon can we know about it, and how quickly can we act on it? More specifically, how can we take an up-to-date view of the experience that our customers already have, rapidly understand what’s changing for them and what we need to proactively engage with, and quickly convert that into an improvement in our customer experience?”
On how organizations approach AI in the contact center, Osman explained that “it’s up to you as a business to identify the highest leverage areas where you can apply AI. The first question is, what’s the nature of your business? If you’re a transactional business, you might think about automation and deflection. If you have high lifetime value customer relationships, what are you doing to assist your agents as they’re talking to customers? Secondly, it’s critical to know where the data lies, know what goals you have, and be honest with yourself about building vs. buying solutions.”
Frank shared some insight on how CX teams should think about digital transformation.
“Going digital means scaling your business with a mix of headcount and technology, rather than just throwing bodies at problems. Some advantages include automating tier 1 support and documenting the context of customers’ outreach. For example, automating tier 1 support frees up agents to handle the most important calls. Maintaining the context of a conversation, too, is critical, as customers go from a chat conversation to a phone call or email. It’s incredibly frustrating for customers when they are passed off from one agent to another, and the next agent isn’t aware of what they’ve just spend 20 minutes describing.”
Using AI Is the Key to Harnessing the Most Impactful Data
The panelists described various ways that companies can leverage AI to better understand and improve their customer experience. Different channels and modes of interaction offer CX teams valuable opportunities to meet their customers where they are. But traditionally, spreading the customer experience across multiple channels has made it very difficult to measure.
George described how measuring organic customer feedback helps CX teams close problematic gaps in cross-channel measurement.
“When it comes to measuring the customer experience, different channels can become a huge drag if you let them. But there’s also a universal language, which is literally natural human language. When you’re making yourself available on these channels and give customers a chance to communicate with you in their own words, they’re likely to bring up the things that are most important to them. You’re giving your customers a chance to inform what your next best actions should be, and that’s a massive opportunity.”
“One of the biggest traps is saying, ‘This data consolidation problem is too hard. When I’m finished deploying a bunch of surveys, I’ll know what’s going on and have the insight I need to make decisions.’ Not only does that take a long time and bring a long feedback loop, but you’re not actually measuring the customer experience when you’re doing that. You’re creating a new experience. Surveys can be really important, but they are more about your needs, not your customers’ needs. We are focused on measuring the customer experience that you already have via your organic interactions. We’ve crossed a threshold where you can use AI to understand the signals customers are giving you on many channels at the same time. If you can actually use those signals to predict what actions customers will take and connect those to business outcomes, then you’re really measuring the customer experience.”
Similarly, Osman emphasized that using AI, contact centers have a significant opportunity to learn and improve based on what’s already happening in their organization.
“Rather than looking outside your walls, so much of the opportunity to use AI is to improve agent performance by learning from the experiences that are already unfolding. The agents who are delivering customer experiences represent so much of your total customer experience, so it’s essential to have visibility into how your team is performing today. Many teams only have 1-2% coverage in terms of agent interactions. But when you look at all interactions, you can use AI to build a model of team behavior and assess 100% of interactions based on your definition of what good looks like. For example, I recently saw that a top-performing agent cohort was 6.3x more likely to set customer expectations than the bottom-performing cohort. So the opportunity is to take that insight, codify it, and amplify it through the company.”
Frank also emphasized that AI can play an instrumental role in making data more actionable for CX teams, especially when it’s spread across disparate systems.
“Disparate systems always present a challenge to making data actionable. My view is that Fortune 500 companies aren’t moving away from their core databases. It’s their job to find the next systems that can connect to theirs and then fire off the automations that they need across certain platforms and into the hands of their customers.”
Short, Smooth Feedback Loops Empower Every Team To Improve CX
On its own, data isn’t going to solve any problem, whether that’s improving customer sentiment or reducing effort, improving agent performance, or giving customers more seamless self-service options. So regardless of the CX use case, it’s critical that data is delivered to empower the stakeholders that need to take action.
George explained that when you’re trying to activate data, it needs to be delivered to people and tools in a format that they can understand and empowers them to act.
“Our philosophy is, ‘measure once, deliver in however many ways it takes. Once a CX team can lead the effort to drive the outcomes you care about, the next step is, ‘how do we translate that into the taxonomies that people already use to understand the customer journey on their own teams? Don’t try to build a single version of the customer journey. Build a Rosetta Stone that can relate what you’re measuring to what other teams need to know. There are several ways that using organic customer feedback and the themes you detect in those interactions help facilitate that translation.”
Osman said it’s critical to find efficient ways to disseminate what you’re learning about what good looks like to the agent team to empower agents to improve performance.
“Whether it’s via real-time agent assistance, traditional coaching methods, or post-call analytics, make sure that you’re creating mechanisms for bringing in information from the edges of your business, streamlining how you use that information to update what you’re doing at an agent or team level, and make it as easy as possible to get that insight back out to the edge of your business.”
In digitizing customer touchpoints, Frank shared some insight into proactively improving customer experience by re-orchestrating parts of their overall journey.
“The question is, ‘are we engaging with the right customers at the right time, on the right channel? Also, do you know what your customers’ preferred channel is? We have a customer that is a health insurance company. We learned that at the time they are completing a quote, their customers are 2x as likely to engage with an agent, and spend 4x as much time with an agent.”
Putting Strategy Into Action
The discussion concluded with each panelist providing an example of how customers use their AI-based technology to bring the strategies that each described to fruition.
Frame AI works with Fastly, a powerful edge-cloud platform that developers use to build groundbreaking apps. George explained that Fastly works with Frame AI in two primary ways — (1) to holistically and accurately measure their customer experience across channels and understand what drives sentiment and effort at any given time, and (2), to rapidly identify changing customer expectations to get out ahead of them. As a result, Fastly has seen a >20% reduction in customer effort, a 25% reduction in cost of service, and visibility into 100% of customer interactions, with sentiment and effort metrics on every interaction.
Cresta works with EarthLink, a large ISP. Using Cresta, EarthLink developed and implemented product recommendations and rightsizing strategies across contact center interactions. For example, in moments where customers have issues with their current subscription, EarthLink’s agents are empowered to help them select a new product offering or bundle. Cresta has enabled EathLink’s agents to acquire the skills they need to be sellers and drive more conversions.
Airkit has helped OpenTable migrate more of their customer experience to digital channels and drive more chat-based conversations. They helped OpenTable develop a solution where instead of waiting on hold, customers get a text offering the option of a live chat conversation or a self-service option. “When given the option, we found that 30-40% of people will take that option.”