Customer Experience in 2026: Balancing AI Innovation with Human Connection

[Music] Welcome to Future Proof, the marketing podcast from Cantar, the world's leading marketing data and analytics company, and side business school, University of Oxford. In each episode, we speak with marketing leaders and share insights to help brands and business leaders navigate the ever-changing marketing landscape, and hopefully dispel some myths and misconceptions along the way. [Music] So our guest today is a bell Zadatni, who's head of thought leadership for the XM Institute at Qualtrics, and Amy Cashman, who's global managing director for brand CX and marketing at Cantar. So welcome to you both. Isabel, let's start with you. Why don't you tell us a bit about yourself and your role at Qualtrics, and a little bit about customer experience? Absolutely. Well, thank you so much for having me undelated to be here. So hi, everyone. My name is Isabel Zadatni, again, head of thought leadership for Qualtrics XM Institute. For those of you who aren't familiar with Qualtrics, we provide experience management software that helps organizations to understand and improve their customer and employee experiences. And then within the broader organization, XM Institute operates almost like a little research think tank. So rather than focus on the technology, our team is really focused on equipping customer experience leaders and employee experience leaders with the data and the practices and the tools and the advice that they need to build these really mature high impact programs. So in my role, I lead our quantitative research, like the Consumer Experience Trends reports, so we'll be talking about in a moment. I also do quite a bit of qualitative work with organizations to really understand what's actually working inside customer and employee experience programs. And then I share those insights out through quite a bit of writing, speaking, and advisory work with large organizations. And I am particularly within the discipline of experience management focus on customer experience management. So how are you systematically understanding and optimizing the experiences that customers have with your organization? Fantastic. Okay, so Amy, why don't you tell us a bit about yourself and your role at Canter? Yeah, so my role at Canter, I have the global responsibility for our brand and customer experience areas, which are obviously major lines of business for Canter. Brand is what we're famous for, but customer experience is something where we do a huge amount of work, as well, particularly with important partners like Haltrex. And I always say responsible for our marketing efforts globally and that I've thought leads it within that. So it's great to have the opportunity to talk to you both today. Fantastic. So customer experience is like it's a really critical element of brand promise and a predictor of brand success. And it's one of the key things that real consumers are exposed to, right? They have these real experiences. So what are the trends that you're seeing right now, Isabelle? How are you shaping up for your customers? Yeah, so this is actually the fifth year we've conducted a global study to understand consumer trends. We started in 2021. In order to understand those trends this year, we surveyed about 20,000 consumers from 14 different countries across 18 different industries. And I would say as we enter 2026, we found an unusual combination, both genuine opportunity paired with some really widespread execution failures across organization. So on the surface, customer experience actually looks pretty good. All of our core cx, so customer experience metrics, improved by about three percentage points year over year. We also saw that people are engaging with AI at much higher rates. So about three and four consumers have now used these technologies for daily tasks. And they're feeling much more optimistic about these technologies affecting society. So lots of optimism, but at the same time, there's a really troubling gap between this consumer openness we're seeing an organizational execution. So many companies are deploying AI in ways that are actually a roading consumer trust rather than building it up. We're seeing a lot of traditional feedback systems. So one of the main drivers of customer experience practices are collapsing just when organizations really need visibility into those experiences the most. And we saw that while nearly half of consumers today are choosing companies based on price and value, that doesn't actually translate into long-term loyalty. And then against that backdrop, we're seeing consumer relationships becoming increasingly transactional. So as traditional barriers to switching fall organizations today are increasingly having to earn loyalty with every single interaction. So that's kind of big picture what we saw in the trends. We also broke it down into four very specific trends we're seeing for consumer experience as we had into the new year. So first of all, AI-powered customer service is failing pretty spectacularly so far. Second, survey fatigue leaves businesses guessing about customer churn. Third, value won't be enough to secure customer loyalty in 2026. And then finally, my favorite trend of our lives are favorite trends. Consumers are increasingly demanding transparency over personalization tactics. So overall, I'd say organizations have this real window right now to capitalize on this consumer openness, but it's going to require them to shift how they operate. So they can't just rely on captive customers anymore. They need to listen in new ways beyond surveys. And again, they need to continuously earn consumer trust through responsible and transparent practices. Wow. So it sounds like it's quite a critical time for the customer experience industry, like the rules of changing technology is changing how things work. So that's really interesting. Tell us, Amy, about how can TARV use customer experience and how brands can close the gap between the perceptions and the experience and about the meaningfully different experience framework? Yeah, absolutely. So I think people probably know of Cantar as an organization that's always been about supporting brands and about helping clients build really strong brands, which in our parlances, that brands that are meaningful and different to consumers. And what we've seen through the work we've done over many, many years with things like our brands, you database, is the really powerful effect at having meaningful difference and having a strong brand has on your revenue growth over time and things like your share price. And many, many really important business outcomes. And what we've tried to understand, then, okay, that's so important. What is the things that build that that strong brand growth? And what we know, particularly in certain categories, service categories, for example, up to 75% of the way that people feel about brands is driven by the experience they have of them. And I think sometimes we talk about brand people think, oh, it's marketing, it's advertising, it's all of these things. And of course it is. That is what sets the promise of the brand. And that is what sets the view that people may think about the brand if they haven't necessarily experienced it themselves. But it's the actual, you know, effective using a brand of having the service, of phoning the call center, all of those things and what actually then delivers that brand promise or not to the customer. And that's really what we look at in Cantar is understanding that, that element of the way that the experience fuels or doesn't the brand and why and what do the things organisations need to do as a result of that. And it's really interesting to talk about things like AI, for example, is about like one of the key things we look at when we're trying to understand whether a brand is delivering a meaningful experience is it one that's connecting with consumers? Is it building affinity with consumers? And it's so interesting the kind of way that AI can do that or not do that because increasingly people are aware when they're talking to AI during a customer experience. And that doesn't, we tend to find support that kind of meaning. And the different element as well is where we're expecting brands to deliver an experience that is leading within their category as well as feeling different to the customer. And again, like the role of AI and that is really interesting. It does allow you and personalisation as you mentioned. So it does allow you to give different types of experiences to your customers. But do they feel like meaningful still to them? Do they just feel different? Because that isn't going to build the overall feeling that we want people to have about that experience. Well, there is a lot going on in how we measure and how we codify experiences as well. So it's about let's talk about the key factors which are driving any sort of changes, any improvements in customer experience trust, for example. And also let's just dive a little bit into why it's different across different categories. Yeah. So again, as I said, a frontline proven for surprisingly significant element. I was a little shocked by this finding. But all of our course, the ex-matrix, we look at satisfaction, trust, likelihood to recommend, and likely to repurchase again, all increased about three percentage points year over year. But when we break those numbers down a little further, what we found was that these improvements are not distributed equally across the board. So industries where it is really easy to switch between brands, think fast food, retail, Airlines hotels, they all saw much more substantial gains compared to industries with much higher barriers to switching, like utilities companies or health insurance or government agencies. So as a quick example, those in competitive markets where it's easy to switch, they earned an average satisfaction score this year of 84%, whereas those in those harder to switch industries earned just 73%, so gap of 11 percentage points. And the reason I think is pretty straightforward, which is just competitive pressure. Right, when customers can easily leave, companies have no choice but to get better. So these organizations again have to earn that loyalty with every single interaction they deliver, they have to be bringing their brand promises to life, meeting or exceeding customer expectations, because there is nothing preventing those customers from just going somewhere else tomorrow. So we have seen major investments from those industries in consistently designing and delivering positive customer experiences. The protected industries on the other hand just haven't had those same pressures, right? They've been able to rely on things like regulatory barriers and contracts and high switching costs. Often there aren't even other options like government agencies. And so all of these things keep their customers captive even when experiences are bad. So there's just much less urgency for those sectors to improve. And what we're seeing now is that those protections are eroding. There's a lot of digital alternatives emerging, regulatory barriers are weakening. Switching is just getting much easier across the board. And we are seeing the consequences of that in our data. So those traditionally protected industries are now putting just over 6% of their sales at risk from delivering bad experiences, because when they deliver bad experiences, consumers can decrease or stop spending for resulting in revenue loss. And that is two percentage points higher than the sales at risk for companies in those hyper-competitive markets. And that's the first time we've seen that, because hyper-competitive markets often put more of their sales at risk from bad experiences, because it is so much easier for consumers to decrease or stop their spending afterwards. So I would say these types of uneven gains aren't just about who's doing well and who's lagging. I think it's a preview of what starts to happen when market protection disappears. And you have not yet built the capability to compete on customer experience. From experience in the UK around current account switching, you know, for many, many years, people were able to switch their current account. But there wasn't the technology and the in place to sort of help them do that easily. And as that has happened, you know, fundamentally, that nothing's changed in the market. You could switch your current account before and you can now, but what's happened is the technology's there now to make that so much easier for people. And that behavior started changing. So, you know, complacency is not the answer with these things. Is it particularly with the rate of change or technology in AI? All sorts of markets are going to be disrupted you wouldn't have thought of before. Yeah, and there'll be new entrance into the market who are able to offer more specialized offerings. So, yeah, it's not just your competitors. It's those new disruptors companies have to watch out for now as well. Yeah. And I guess the other angle on this is, you know, it's with categories where it's fairly easy to switch, for example, with intermediaries where you can compare prices, you know, actually, those brands have a job to do on promoting their brand, not just on a price point as well. Isabel, do you have a point of view on that about how brands can stand out in a hyper-combestive world? This is such a good question. I would say that making those emotional connections is really critical and exactly to the point that Amy was making before. One of the things that we're seeing with AI is that companies are really focused on increasing their efficiency and speed, which is great. You should absolutely be doing that to some degree. However, if you are just automating away all your consumer interactions, there is nothing to differentiate you from the next company over who's using the exact same technologies and AI to also automate all of their interactions, right? If you're competing on price, someone comes along that's a few cents less than you. Your customers are gone. If you're competing on speed and convenience, like Amazon, you can check out in three clicks. A competitor comes along, you can check out in two clicks. So I think making brand promises consistently delivering on them that emotionally resonate with your target customers, that build trust, especially as we move into an era of increased uncertainty and financial pressures, the ability to be reliable and ensure that consumers know if they interact with you and something goes wrong. Even if it's outside your control, prices increase, supply chain disruptions. You will do your best to make it right. You have the integrity and the confidence to deliver on your brand promises. I think those companies are going to stand out in an era where everything, AI makes everything commoditized, except those human connections. Amy, can you give us perhaps an example bringing it to life of how a customer experienced data can be used in a really smart way to drive business outcomes? Yeah, absolutely. We were working recently with a client actually who was seeing some unfortunate churn levels, shall we say, and we were working with them and they had a lot of different data sources that they were looking at to try and understand this problem. We did quite a lot of analytical work with them to try and pull together a framework they could use to segment the customer base and really get a bit more granular about where they were seeing the churn. From that, obviously, understand the implications and probably why they were seeing that churn. Then what we were able to do from that was build targets around the different issues that were being faced by those segments and then strategies and tactics for how you would go about, you know, bringing a more positive experience for those individuals. So it could have been some of them were, it was about more personalisation in what they were being targeted on. Others, it was about faster response times around challenges they were having, but it really enabled us to get quite granular on what the problems were and but use more sort of technical analytics to get down to the problem and then use technology as well to really answer the problem. And I think that's where things like AI and technology can be so exciting for the customer experience. I know we talked earlier about, you know, some of the challenges of keeping experiences feeling more human, more connected, more meaningful in these AI, but then there's other ways that in the background it can be used to really target things in a way that makes people feel that you are answering their challenges. Let's talk a bit on Amy about the point that Isabel mentioned about declining customer feedback and survey fatigue. So what is it that the industry do you think needs to do to promote the continued feedback loop that customers can bring and particularly in this crucial area of customer experience? Yeah, I mean, there's several steps, I think. I mean, one of the first steps I think is just asking yourself whether the questions you're asking need to be asked in the first place. So, you know, I get sent surveys sometimes and there's very basic facts about me as a customer that I am having to fill in for that survey. So when I attended a particular place or how long I've been a customer for or, you know, really obvious things that to me, why are you asking me that question? So question number one is like, are you asking the right questions? Are you asking questions you really shouldn't need to be asking? Then the second thing and you know, obviously we have a history and survey, which is called trickstee, is about great survey design, it's about engaging your respondents, engaging them to participate in the survey, to stay in the survey, to give it the level of concentration. You want them to have as they're answering their questions. And that's, you know, simple things like gamey-fying the survey, using more visually appealing platforms to fit the survey, direct questions that are simple language, not sort of convoluted, that people will always like have a cognitive overload having to read what the question is, things like that as well. And then obviously, you know, just very good discipline about like absolutely minimum survey lengthy possibly can to get what you want to achieve. And thinking about what are the other data sets that I have available to me? Does this have to be a survey? Does it have to be a question? Like, could I get more of like looking at say, trip advisor or reviews or data signals from digital data or even synthetic data? You know, there's so many ways now to find out how people are feeling about things that the survey shouldn't always be the default option anyway, in my opinion. Is it well? Is there anything you want to add to that? Because I think it's sort of, it is an industry-wide issue. And that, you know, the pressure is on to better detect and respond to customer dissatisfaction. And yet, it's getting harder than it has ever been. Yeah, I'd say this is actually probably the trend I talk about most with clients. So just to give you a little bit of additional data around this, we found this year that for every 10 poor experiences a customer has five results in decreased or stop spending, but only three are now resulting in feedback. So just like Amy said, those companies that are relying solely on traditional surveys to understand customer experiences, They are losing both their customers and their revenue often without really understanding why. If we look even deeper in these feedback patterns, which we've been asking how consumers share about their experiences since 2021, we found that direct feedback, so telling companies about a good or about experience has dropped about eight percentage points over the last few years. That's just 29% today. We even found things like social sharing on third party, review sites like TripAdvisor or social media. That's down five percentage points and then people aren't even telling their friends or family about their experiences to the same extent that they used to. The only response option that's increased in this time is I did not tell anyone about this experience, which actually had an all-time high this year. So this is happening across the board. It would echo everything Amy just said that this is happening because consumers have a lot of survey fatigue and then there's also this why bother factor because companies often ask questions and then don't visibly act on that feedback. And so customers just stop participating. It's not worth their time to scream into a block hole, right? We have very little time today. Why would we take our precious cognitive load to put towards winning feedback when they're not gonna act on it? I think this also reflects the increasingly transactional nature of customer relationships. There's just, again, there's no point when you can just kind of quiet switch to one of the competitors just as easily. But I would say again to echo what Amy just said, customer signals haven't disappeared. They've scattered, right? So they're in chat transcripts and call recordings and support tickets and behavioral patterns and operational data. And so the companies we're seeing succeed here are bringing together their sparse survey data with all of these other signals to understand what customers are doing, not just what they're saying. And I would also say here that AI is really helping on this front in a few different ways. We've actually been very fortuitous that just as customer feedback is in decline, AI actually helps us fill in the gaps a little bit. So first of all, we can now do these conversational adaptive surveys where they can adjust questions in real time based on customer responses. And that allows you to get much deeper into issues and root causes without exhausting your customers with those long questionnaires. Second, again, with natural language processing, we can analyze all of that unstructured feedback in those different spaces in social media posts and call and chat transcripts and call recordings, all those spots to identify patterns and themes that, just take months for humans to do manually. And then third, we're increasingly seeing AI help build up predictive models. So instead of waiting for customers to tell you they're unhappy, AI is able to spot those early warning indicators, customer who's call frequency spikes or usage pattern shift, writer whose language gets really infused with frustration during calls and then help predict churn and do proactive outreach before it happens. So one of my favorite examples here is one of our clients is able to build synthetic customer experience scores so not promoter scores. They only have an 8% response rate to their relationship survey, but based on that, they're able to build customer profiles and then predict the not promoter score of 92% of their other consumers who never fill out a survey. And then use that to proactively reach out and try to mend relationships, even if those customers have never filled out a survey. So there's some good news buried in there. 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