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- [00:00]
A
Nearly one in five consumers who used AI for customer support said that they received zero benefits from it, which was the highest failure rate of any AI application we looked at. Wow. This is particularly problematic because often customer service is the only time that customers know that they are engaging with AI. So it becomes a litmus test of whether brands can actually deliver on their AI promises, and they are failing that. So pretty clear that a lot of companies are using AI customer service to deflect costs, which is great for them. Efficiency metrics internally are up, but they're not actually resolving customer problems.
- [00:47]
B
It's the end of the year, and we're heading into 2026, which means it's one of my favorite seasons. I'm getting the flood of end of year research, trend reports, all those juicy stats that tell us where our customers are actually headed. And that's why I'm so excited for today's episode. I'm joined by Isabel Zanatny, the head of thought leadership at the Qualtrics XM Institute. Isabel and her team just released their brand new 2026 Experience Trends report, and it spotlights four major customer trends every business leader should have on their radar going into this new year. You're going to love her breakdowns. She makes the data feel really clear. Her energy's amazing. She gives some great actionable advice, and honestly, a few of these findings surprised me in the best of ways. You're listening to Experts of Experience. I'm your host, Lacy Pease, and if you enjoy this episode, hit that subscribe button. Drop a comment below letting me know which trend or stat stood out to you the most. I guarantee some of these insights will surprise you and some might even confirm the exact hunch you've been feeling with your customers all year long. So, without further ado, here's Isabelle Zidatny. Isabel, welcome to Experts of Experience.
- [01:50]
A
Thank you so much for having me. I'm delighted to be here.
- [01:52]
B
I am so excited you're here. And thanks for joining me on a Friday. I know it's like the end of the week for the both of us. So, like, you made it happen. You're here. We're on mic. Ron, Cam.
- [02:01]
A
It's a great note to end the week on.
- [02:03]
B
Yeah, absolutely. Absolutely. Well, we're gonna go through the Qualtrics report that you guys just released in the last. What was it like, month ago about.
- [02:10]
A
I mean, time goes so fast, but, yeah, about six weeks ago, at the beginning of October.
- [02:15]
B
So give me a rundown of this report because you guys have been doing it for a few years. It's designed to measure a few things around consumer experience. So what have you guys been tracking over the last four years and maybe how has it kind of evolved and like what survey data are you guys really pulling from?
- [02:28]
A
This is the fifth year we've conducted this global consumer study. So we started in 2021 and this year we surveyed just over 20,000 consumers from 14 different countries to really understand their experiences with and perceptions of those experiences with organizations across 18 different industries. So we have a whole host of questions in here about satisfaction and trust and likelihood to recommend. And then we dig into some of the deeper themes that we think are really influencing customers experiences today. So questions around AI and personalization and data usage, all of those top of mind trends.
- [03:10]
B
And have you been involved the last five years in this report?
- [03:13]
A
Yes. So my old boss used to lead out and I would be supporting. And then since he left, oh like two and a half, three years ago, I've been doing the last few.
- [03:24]
B
And what's been some of the like trends over time that you've been tracking that you've been most excited by?
- [03:28]
A
I would say the biggest one which we might get into in more detail is the continuous decline in customer feedback. We have found the percentage of customers who say that they send feedback to companies has gone down every single year. It's gone down about 7.5 percentage points since 2021. And I think that's really relevant for a lot of the companies I'm talking about are talking to where they ask, you know, why are my response rates dropping? And it's like this is a trend across the board that we're seeing, not just giving direct feedback, but actually things like sharing on social media or third party review sites that's dropped like 5 percentage points over the last few years. Fewer people are even telling their friends and family about their experiences, which is interesting. And I think the only response that has increased over that time is I did not tell anyone about this experience. So.
- [04:26]
B
Wow.
- [04:27]
A
Customers are just staying increasingly quiet about the experiences they're having with companies and that's been a real standout.
- [04:34]
B
Yeah, I want to dive so much deeper into that. Cause I know that's going to be one of the trends that we talk about today. But there were four key trends. Do you mind just highlighting those four trends you guys found in 2026?
- [04:43]
A
Is it worth setting the scene first of some really high level big picture before we get into the specifics?
- [04:49]
B
Absolutely, let's do that.
- [04:51]
A
Big picture as we head into 2026. This surprised me, honestly. We found that consumers are feeling good about their experiences. All four of the CX metrics that we track. So satisfaction, trust, likelihood to recommend, likelihood to repurchase. Those all improved by at least 3 percentage points over the last year, which is particularly impressive given the challenging environment that we're all operating in. Sure.
- [05:20]
B
I can't believe that, to be honest. Like, if you didn't have the numbers to pull out, I would be like, there's no way. There's no way that's true.
- [05:25]
A
So many people were like, are you sure? Like, check the numbers again. I do think, in fairness, that one of the things we've seen. I've been doing this before I worked at Qualtrics, I was at a small CX consulting firm called Temken Group that was actually acquired by Qualtrics in 2019. And we've been asking a lot of these questions since like 2011. So able to track over quite a long time period. And one of the quirks, I would say, of doing these types of temperature checks every year is that often numbers seem to be a lot lower in election years in the states. So it could also be that 2024 was a particularly low year and 2025 is more of a return to average. But I was also shocked by the increases across the board because I don't know a more professional way to say this, but like, those are not the vibes it seems like right now. Absolutely, yeah. So, yeah, so that was like big picture when you look a little deeper. Something that I actually thought was really surprising and interesting this year was how unevenly distributed those gains are actually. So we found this part isn't surprising. But in industries where it's really easy to switch between brands, so sectors like fast food, retail, airlines, hotels, those all saw much more substantial gains compared to industries with high barriers to switching, like utilities, health insurance, government agencies. And so what was interesting this year is we track what percentage of sales at risk organizations are putting so revenue loss based on delivering bad experiences to customers. We found Overall, globally, about $3 trillion of sales at risk in 2026.
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B
Wow.
- [07:18]
A
But normally the way we calculate that number is we look at what percentage of bad experiences do you deliver and then how do customers respond to that? So do they decrease or stop spending? And normally what happens is those hyper competitive markets deliver fewer bad experiences, but customers are much more likely to decrease or stop spending because they have so many more options.
- [07:45]
B
Makes total sense.
- [07:46]
A
Right. And in those harder to switch, more protected industries, they deliver more bad experiences. But because it's so hard to switch, they have a captive audience, customers can't really punish them for it. This year those harder to switch more protected industries are putting a higher percentage of their sales at risk, 6.1% versus those hyper competitive industries, 4% which I think is the first time we've seen that and I think speaks to the increasingly transactional nature of customers relationships with brands which will be a theme, one of the kind of sub themes I think weaving through the other specific themes. So with all that kind of throat clearing and big scene setting, the four specific themes this year were AI powered. Customer service is failing.
- [08:38]
B
So far.
- [08:39]
A
Survey fatigue leaves businesses guessing about the causes of customer churn. Value won't be enough to secure customer loyalty as we head into 2026. And my personal favorite, if we're allowed to have personal favorites, consumers demand transparency over personalization tactics.
- [08:59]
B
Awesome. Well thank you for that overview of like where we've been standing. I think it's really helpful context. So like trend one, if we want to dive there first. You said it's AI powered customer service is failing. Right. Which is interesting to hear because we've talked to so many people who have shared their like success stories with customer service. So then when I like read your guys report and was digging into it a little bit more, I was like okay, what's the angle here? Right. It's because we're talking to consumers. So from a business ROI standpoint, yes, we're seeing returns, we're seeing like less, you know, I'm spending less money on this, da da da da da. But the consumer is not necessarily receiving that same sort of impact. So could you talk like walk us through that trend a little bit?
- [09:41]
A
Yeah. There's a really interesting paradox I would say happening here. So overall consumer comfort with AI has actually rebounded from its low last year. So we found that about 73% of consumers, so nearly three in four have used AI for daily tasks, things like research and writing and language translation. A massive adoption increase. So these technologies are moving from a novelty to a habit for a huge percentage of the population. And something else, I'm just going to tell you all the stats that kind of surprised me. 50% of consumers now say that they believe AI will positively impact society, which is up 9 percentage points since we last asked this question in 2024. So big picture, like consumers are moving past their initial skepticism. They're actively engaging with AI across multiple use cases. The one blight on this otherwise rosy picture really is AI for customer service. So Nearly one in five consumers who used AI for customer support said that they received zero benefits from it, which was the highest failure rate of any AI application we looked at. It was nearly four times worse than the average. When we asked consumers to score different AI applications on qualities like convenience, time saving, usefulness.
- [11:11]
B
Right, yeah.
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A
All the things that chatbots, these AI agents, are supposed to be excelling at.
- [11:17]
B
That's the promise.
- [11:18]
A
Yeah, that's the promise. Organizations are like, this is what we're deploying them for. Customer support ranked the lowest of all of those applications. So again, it's falling behind other AI applications on the very metrics it's supposed to excel at. And I think this is particularly problematic because often customer service is the only time that customers know that they are engaging with AI, when they're having an AI mediated experience with a company. Right. So it becomes a litmus test of whether brands can actually deliver on their AI promises. And they are failing that, I would say, right now. And as a result, only 29% of consumers say that they trust organizations to deploy AI responsibly. So, you know, I think it's pretty clear that a lot of companies are using AI customer service to deflect costs, which is great for them. Efficiency metrics internally are up, but they're not actually resolving customer problems. They're using it as that gatekeeper to keep people away from expensive human agents rather than a tool to help customers solve their problems.
- [12:35]
B
I think a really key point that you made in that was around this, like the trust factor of AI tools. Right. If I, if my one experience that I know to be AI is through customer service and it's not a good one, or it slows me down, or I cannot get a person on the phone when I know my specific thing needs to be addressed by a person. It does make you skeptical of any AI tool moving forward. Right. So if you can't do this one thing, why would I trust you to be able to use AI to do all these other really cool applications in theory, but you can't even deliver on better customer service initially. So I think that's a really valid point.
- [13:12]
A
Or it makes it clear that you're delivering, you're using AI to help the business achieve its goals rather than help the customers achieve their goals, which again, undercuts trust in these new technologies, which.
- [13:27]
B
Kind of piles into some of the trends I know we're going to speak about around consumer trust. Right. Like if I can't trust you to do this one thing, then it's really going to lower the value that a business can get from a customer over time.
- [13:38]
A
Exactly. Right. As we move to that more transactional environment, trust becomes even more important because otherwise you don't have sticky interactions with your customers. Right. If you know, you're just. If they're just selecting you because of speed or convenience or you have the lower price, the second someone undercuts you by a few cents, the second a competitor comes along and is like, instead of three clicks to purchase this item, you can do it in two, those customers are going to be gone. And not only is the environment more transactional, but it's also, there's a lot more economic uncertainty and instability. And so customers are going to choose to interact with companies that they trust to have their interests at heart. Right. If price increase happens, it's not because they're trying to boost their profits, but like genuinely because supply chain issues or something goes wrong, that they will try to make it right. That's going to become a competitive differentiator, I think, as we move even deeper into this environment of uncertainty and complexity.
- [14:54]
B
Absolutely. Yeah, absolutely. With, with that. When you think about AI, that enhances human experience instead of just replaces it. Like, what do you think about? Are there any, I don't know, case studies or stories that you've heard of where this is done well, so people can learn from that?
- [15:09]
A
One of my favorites recently was from one of our clients, which is a healthcare technology provider, and they used to have a claims process. This is a pretty common use case, but they used to have a claims process that took about two days to complete. Customers often don't know the right way to fill out the forms. What's actually eligible? Then you need a claims processing agent on the other side to review it. Go back to the customer with questions. So they used AI, first of all, they use computer vision to help analyze customer receipts so customers could just take a picture of their full receipt with some things that are eligible, some things that are not eligible. It was able to determine these items are eligible for reimbursement and automatically fill out the form for customers. And then they also deployed an AI chatbot along with that, where customers could ask questions and get answers very quickly. So the ones that I'm seeing working well are asking, what are the goals that customers are trying to achieve and what are the right tools that we can deploy to help them reach those goals more quickly and painlessly. And sometimes that's going to be AI, Sometimes you're going to want human connection, you're going to want a human on the other side of it, sometimes there's other tools that you should be deploying that are not AI. So rather than just like, oh, here's a shiny object, it's like, how do we help people do what they want to do better and more smoothly?
- [16:40]
B
I like that question. Reframe way more than how do I save money? How do I cut, you know, save things at the bottom line instead of, instead of that, how can I actually improve my customers experience with these tools? Or maybe that's not even the right tool to choose. There has definitely been shiny object syndrome with AI where it's like, we can fix everything. With AI, it's like, no, there's actually some great tools that have existed for a really long time or just human interaction that would be, you know, super fitting in this particular moment, in this customer journey and to just ignore that and try to replace everything with AI. I do feel like a lot of companies have made that misstep, unfortunately. And I've been on the receiving end of that as a consumer, you know, trying to get a hold of a company. You know, I think we all have had that experience this year.
- [17:23]
A
Yeah, absolutely. One of the other things I think companies are doing is they are using these AI tools to accelerate their existing ways of working. How can you do what you already do more quickly and more efficiently? So like, okay, we already do customer support. How do we do that faster and more cheaply? And that's great. I don't think they should be ignoring the efficiency use cases, but these technologies are so transformative that I think companies also need to be looking at what are we able to deliver to customers now? How can we create and deliver value to customers in new ways that were never possible before? What is our unique brand able to deliver to customers at scale that we've never been able to do before? I think they're getting very spun up in these like efficiency metrics, productivity gains, and are really failing to imagine more interesting and differentiating ways of delivering better experiences to customers.
- [18:35]
B
Oh, that is such, such a good point in the imagination piece, like actually taking time and saying like if, if we didn't do anything at all, if I was going to build this business today from scratch, how would I want to deliver this? Rather than getting caught up in how we've been doing it for a decade or 50 years, like can we just completely wipe that from our mind and think about what would I do next year for my customer if I was starting this business completely from scratch?
- [18:57]
A
That's exactly. And I mean it's probably not only a little cliche now, but I'm pretty sure it's also apocryphal. But I always think of that old Henry Ford line. If I would have asked the people what they wanted, they would have said faster horses.
- [19:10]
B
Yeah.
- [19:11]
A
So how are we not just doing those simple AI adoption use cases, but also like you're saying, if we started from scratch doing those blank slate exercises, how are we creating safe spaces for dangerous ideas and giving them different budgets and KPIs and timelines to go run and explore what are like radical innovations we could be doing with this AI? I suspect companies that are going to succeed and thrive in this new era are the ones that do that.
- [19:41]
B
Isabelle, the second trend you highlighted is that customers aren't giving feedback anymore. And we already talked about this a little bit, but I want to dive even deeper. Give me all the juicy stats that you found in this report this year.
- [19:51]
A
The key finding here is that for every 10 poor customer experiences, five result in spending cuts, while only three generate direct feedback from customers. So those companies that still rely solely on traditional surveys to understand customers experiences, they are losing both their consumers and their revenue, often without knowing why. And we talked a little bit before about some of the stats here about how dramatically feedback has declined across all channels, from direct feedback to social sharing. But yeah, it's it hit an all time low this year at 29% of consumers who share direct feedback with companies following a poor experience.
- [20:37]
B
You know, it is something that I think about with my own, you know, life like how I recommend products. I do not recommend things as much as I used to. I mean, years ago I would be like, oh my God, this thing blew my mind away. Like you guys have to try this. I love it. I don't feel that way about many things anymore. If I have a great experience in the store or something that's super memorable, even like online, that might be something I share, but like a product itself, I'm not, I'm not sharing, I'm curious, like are you having the same thing in your like life and family?
- [21:10]
A
I think overall another of those kind of through lines that we've seen doing the trends for so many years is that customer expectations are rising. So I think what used to blow us away a few years ago just becomes kind of baseline and table stakes. So yeah, creating those standout experiences I think is just a lot harder. Wowing your jaded customer base is a lot harder than it even was a few years ago.
- [21:39]
B
Yeah, for sure. And I think most of the experiences I do share are ones where, like, something maybe went wrong and the person fixed it, the company fixed it. That interaction of, like, something went wrong with it immediately was resolved. It feels so rare now that. That I feel compelled to share.
- [21:53]
A
Absolutely. And I think that goes back to, like, the trust point. Right. Of we're almost surprised when companies demonstrate, like, reliability and dependability and making things right like that integrity as a company. I do think that rather than bells and whistles and shiny features, that it is that type of, like, trust, integrity, benevolence that really strikes people and differentiates companies today.
- [22:22]
B
Absolutely. So with surveys, why do you think customers are opting out of doing them? Is it just people, like, get so much spam now that they're not going to look at it in their email or what's causing that?
- [22:31]
A
I do think some of it, probably a large portion of it, is survey fatigue combined with a why bother factor. When companies don't visibly act on feedback, which very few of them do, customers just stop participating. Right. It's not worth their time to go scream into a void. We have a lot of other things on our plate that we could be working on. And I also think that this does reflect some of that, again, increasingly transactional nature of customer relationships where there's no point, again, taking your precious time to share feedback with one company when you can just easily and quietly just go switch to one of their competitors. And I think there's a lot of bad survey practices out there. I will not name any names, but earlier today I did hear one who has 15 questions on a single survey. And so not only are customers getting a lot of feedback requests, they're not seeing the benefit of it. But when they do take surveys, they're long, they're asking irrelevant questions. They're just exhausted by the end of taking those surveys. And that trains them not to take future surveys.
- [23:42]
B
No, I mean, I feel that 100%. Do you see any patterns in people who are still filling out the surveys, though? Like, of the three of 10 that are filling these out, are they people that are really, really happy or really upset, or is there some sort of trend there?
- [23:55]
A
That's a good question. We're not able to dig into that in this, like, granularity, level of granularity in this research. Generally speaking, working with a lot of companies, I do think you're getting the two extremes, especially people who are more upset and screaming into the void might not get them a response, but it does feel cathartic. And then you might also get those Types of standout experiences, especially like if an employee went above and beyond to solve an issue. But I think you're really seeing a hollowing out of the middle, which is going to be a vast majority of your consumers. And so you are getting quite unrepresentative feedback when customers are responding.
- [24:36]
B
Yeah. Oh, for sure. I mean, and I think about that in my own experience. Anytime I've left feedback recently, it's usually been because there was just something terrible. And it's usually not even because I think the business is going to do anything about it. It's because I want other customers to see that review, to know, hey, look out for this. Don't, you know, don't invest here. Yeah, so what I know when we were chatting last time, you had a really cool way that people are. A few companies have been doing surveys and feedback differently with AI tools. I would love to hear you share more about that.
- [25:07]
A
I would say just overall, right before getting into the details. The organizations that we're seeing do this well are really diversifying their listening portfolio. So combining the sparse survey feedback that they do receive with rich unsolicited data from sources like support conversations and that operational data and behavioral patterns, and then synthesizing all of those different signals into predictive early warning signal systems that can actually prevent problems rather than just reactively documenting them. And one of my favorite examples of this recently comes from one of the large financial institutions that we work with. One of the things that they found is that on their relationship study every year where they're looking at Net promoter score was their core relationship metric, they only had an 8% response rate on that survey, which meant that historically they've been blind to 92% of their customer base. What they did recently was they took that 8% and they used it to build this predictive model where they created rich profiles for the customers who did respond to that survey. And this included not just their CX scores, but also behavioral and operational signals like call frequency, usage, pattern support, interaction, demographic information. And then they used machine learning to find the patterns that correlated with different net promoter scores. And then once they had that model, they could then apply it to the other 92% of customers who never responded to the survey. So they generated a synthetic net promoter score for every single customer based on their behavioral and demographic patterns. And then they not only kind of came up with a synthetic way to track it, they actually use those scores to act on those predictions, so triggering proactive outreach to customers that the models flagged as detractors. Even though again, those customers had never filled out a single survey.
- [27:13]
B
And what was the response like when they did this?
- [27:16]
A
Yeah, so far so good. I don't have. This was pretty recent, so I don't have a whole ton of ROI metrics, but I think so far has been a really effective program.
- [27:25]
B
I think it's a really imaginative way to think about taking what you do have and making the most of it. Because you could look at that and say, oh, only 8% of people responded. What are we going to do about the 92? But to actually think, okay, what can we take from that data? Translate it out. And it may not be entirely accurate given that it's just a sample size, but we're going to try this out and see what we can get. There was another thing that I had heard recently about using a chatbot essentially to get survey feedback. Instead of just sending out five questions and having someone answer it. It was like, I get to have a conversation almost. And then the questions are geared as the person responds. Is that something you guys are seeing as well?
- [28:03]
A
Absolutely. Yeah. So this is exactly to your point of like, when you have fewer signals, how are you making the most out of the information that you do have? We offer conversational surveys. So I've seen a number of customers deploy these. My personal favorite example comes from fiserv, which is a financial services technology company. And they deployed these conversational surveys on their attrition survey because they figured it was low risk. These people are already leaving us. What's the worst that could happen, right?
- [28:36]
B
It's smart. It's so smart.
- [28:38]
A
Yeah. And so their head of vocal, she knew that on these surveys there were always two complaints people were leaving either because of cost or because of customer support. In the past, they just ignored those two responses because they're not really actionable and would look kind of down further the list of complaints. But when they started using conversational AI on their attrition surveys, they got this like completely different story. So my favorite is within 24 hours they deployed this and a customer had an open ended comment that was like terrible service. I keep getting transferred. Instead of just being like, oh, that's bad, let's go share that with the customer support department. The AI followed up and was like, oh no, I'm so sorry, tell us about a time you were transferred and probed even deeper into that. I think it asks, it's set up to ask just two follow up questions, but it comes up with them itself and they're very effective.
- [29:40]
B
That's great.
- [29:41]
A
And so based on this follow up they found that there is like this critical issue leading to churn that fiserv had not been aware of, which is sometimes like the local government or the IRS would require a hold on clients financial accounts as they were investigating an issue. But Fiserv isn't legally allowed to tell their customers that. And so customers would have funds withheld or frozen, they'd call into customer support and then they were very reasonably infuriated when they felt like they were being given the runaround or lied to or transferred to different departments. But that's not the service agent's fault. They're actually following proper procedures. But unsurprisingly, customers experience a sustained terrible service, get very frustrated and leave the company. And so it looked like a service problem they could then identify is actually a communication and an expectation setting problem. And as soon as they recognize this again this was all within like 24 hours. Fiserv was able to change how they set expectations upfront around those legally restricted processes so that customers at least understood, you know, why certain information couldn't be shared rather than just feeling like they were given the runaround. And also interestingly on these, we don't see a drop in response rates, which is crazy. Everyone thinks that there's going to be a drop in response rates.
- [31:05]
B
Yeah.
- [31:06]
A
But instead customers feel like the company's actually listening to them rather than these cookie cutter questions and really trying to understand their issue. And so yeah, they're actually willing to supply more information we found.
- [31:21]
B
And is this just chat? Like I just would text response to that.
- [31:24]
A
So it's within a survey and it's like off the back of open ended questions. So instead of, you know, you get a low NPS score and saying like tell us more about why you gave this score. It's able to ask much more targeted and specific questions based on their answers. But it's within the survey.
- [31:42]
B
That's so smart. That's amazing. And it would be interesting too to have that as I don't know if you guys have tried this yet for phones. Like if I could do a phone survey where it's the same type of deal and I can just. Because then I really would speak my mind if I don't even have to type it.
- [31:55]
A
I haven't seen that yet, but that's a great point. That would also be probably more cathartic and it's faster. Right. Often for people to explain things. We do see a rise in video feedback where customers can show their screens and talk about the problem. Rather than again responding to these static generic surveys. So I don't think surveys are going away, but I do think surveys need to evolve as we move ahead. They're just not effective mechanisms anymore for getting a comprehensive understanding of customers experiences. They're reactive. You have data lags, you have limited response rates. So they should be one tool in your toolkit rather than the whole of your customer listening program.
- [32:40]
B
And the beauty of what AI can offer now too is we can change how we think about getting customer feedback because we can take all this unstructured data like sentiments, how the person's voice was, you know, the way that the words that they used, how long they responded, all this stuff can then be digested by AI and like you can come up with more thorough conclusions. So we're definitely at a pivotal point where I think next year we're gonna have a completely different way people are looking at how we get customer data and customer feedback.
- [33:05]
A
Yeah, it's so interesting. The AI makes it so much cheaper and easier to access and combine vast data sets. Right. Like that data that kind of has always been produced as an output of transactional or operational systems. Like we can now capture that and combine it with customer sentiment. Exactly as you were saying, unstructured conversations from the call center or chat conversations to get really granular understanding at both an individual level and at that segment.
- [33:38]
B
Level with the video feedback. Is that people being like, hey, this is my problem that I ran into and like you guys can't solve it, or is it literally someone just being like, here's my problems and speaking into the camera about all the things that they don't like?
- [33:51]
A
Yeah, it can be either. A few of the most common use cases are things like on digital. So being able to screen share and then talk over if you've had a bad digital experience and like physically show this is the issue I'm running into has been huge. And then another one is for market research where you can capture people like almost like real time observability labs of like, here are my thoughts and feelings as I'm going through this experience has also been a really effective use case for again getting a much more comprehensive view of customers perceptions and attitudes as they go through an experience.
- [34:30]
B
All right. This third trend I feel like is actually a pretty big one. It's around price sensitivity and value. But that not being quite as important as one might think in this economy as trust, in which we've been talking about this whole time and how important trust is. So tell me about how people are Defining or redefining what's important to them, like how consumers are redefining what's important to them when it comes to brands that they're loyal to.
- [34:55]
A
You asked at the beginning what are common set of questions, this was a new question set this year, which I love. This was my favorite addition to the survey. And we found that again, the trend here is value won't be enough to secure customer loyalty in 2026. So given our current economic climate, it is unsurprising that when we ask consumers, why did you choose to do business with a company, value for money was the number one driver of consumer choice. Like 46% of people selected that. However, while value will get people in the door, we found that it's those high quality services that will keep them coming back again over the long term. So 92% of consumers who choose companies based on their customer service say that they feel satisfied as opposed to just 87% for value. So notably higher. And then the trust gap between that was even bigger. So 89% of consumers who choose companies based on their customer service trust that company versus just 83% when it comes to value. And then we also saw that a number of the negative drivers. So if customers say I had no other options or it's too difficult to switch, their satisfaction scores are so much lower, they're usually in the 60s. So those are customers that are just waiting for an easy alternative to show up. And I think as we head into 2026, why this really matters is that while price is clearly important in tough economic times, a race to the bottom isn't sustainable. It's going to erode your margins. It's going to leave you vulnerable again when a competitor offers even a slightly better deal. And so instead what we recommend organizations do is combine operational excellence, a lot of what we've already been talking about around how do you apply technology for those efficiency gains? Right? Save some money there and then that will allow you to compete on price, but also give you the wiggle room to deliver those high quality experiences that ultimately we see end up creating lasting customer relationships even as those business conditions continue to switch.
- [37:20]
B
I think all of us as consumers have had this experience now too of like getting something because it's cheaper. And we just, we're all feeling very price sensitive right now, but then almost regretting it because, oh, I had a problem with it and I can't get ahold of your customer service. And yeah, it's like 100%. I think we've all been trained now to like, not just think about what's the price of the product or service that I'm purchasing, but what's the longevity of that. You know, I think of classic examples like vacuums. I feel like vacuums used to last forever and now they just break like every six months. And so I'm like, looking for the vacuum that will actually, actually last as long as I need it to last. And, and that's just a small example of something they have in your household. But when you're talking about like big enterprise purchases, like what we do for our business whenever we buy, you know, something that's like a subscription service or something, I'm not so much looking at the price tag. Sure, it's something I consider, but if I know that they're going to be responsive and helpful and their customer service is going to be great, I will spend an extra $100 a month if I need to to make sure that I have access to that.
- [38:19]
A
Absolutely. One of the other really interesting findings, again, just peek behind the scenes. So as part of this survey, we also ask what we call our well being index, which is made up of three elements. So customers, we ask customers, like, are you happy, Are you healthy, and are you financially secure? One of the things we found is that customers who say that they're financially insecure give much lower CX scores across the board, like about 7 percentage points lower than average for trust satisfaction, likelihood to recommend, and likelihood to repurchase. So something that I think organizations need to be keeping their eye on as again, we move into more economic uncertainty, is how do those price pressures change customers perceptions of their experiences? You know, it's going to be harder to hold on to those customers who are incredibly price sensitive if they're shopping around.
- [39:23]
B
Yeah. So if I'm thinking about this from a business perspective of like, things are getting tighter, like, I don't have a lot of money to spend on making this great experience and making sure customer service is perfect and also trying to like, lower the cost of my product or service to be competitive. It is, it is such a tough position to be in. So how are you thinking about that? Like, what are you seeing businesses do who are successful with sort of balancing the fact that like, yes, we've got to cut costs in some fronts, but there's other things we're still going to be investing in and really making the argument for that investment, because I do see, like, it's hard to go to like the CFO and say, no, this is worthwhile for the long term when in the short term, the budgets are tight.
- [40:02]
A
Yeah. And I think this is actually where the customer silence piece gets really dangerous in this environment and frankly in all environments. Right. None of us are working with infinite resources. But when budgets are tight, you need to be able to identify what specific moments, what products, what interactions are driving the business outcome that your company cares about the most. And when you're missing those customer signals. Right. That these perceptions you can then say lead to these behaviors down the line, like renewal churn, calling into the contact center, it becomes a lot harder to make those investment decisions because you're working from incomplete information. So I think companies need to get better at understanding what are those moments across customers journeys that have the most outsized impact on people's perceptions and behaviors and then by extension on the business outcomes that the company cares about the most. And then how are you prioritizing investment in those particular areas so you're not just listening to the loudest customers? Maybe a lot of customers are complaining about a broken link, but actually that doesn't drive their purchasing behaviors. So as you're trying to prioritize, what should we be investing in? Maybe that one goes further down the list as opposed to another area that fewer customers are complaining about but actually affects those business outcomes that the company is looking for. So I think that to start, organizations need a much stronger sense of what is happening across people's experiences. And then how do those variables affect their downstream behavior to allow them to prioritize their investments and make those trade off decisions that are inevitably going to be required in a climate like this?
- [42:04]
B
Oh, that's great. That's great. That's really good advice. And I think looking at all the different pieces of the customer journey and really stack ranking them would it's so helpful because it's really easy to be like we need to make everything great.
- [42:14]
A
Yes. And if you go to a stakeholder, like everyone thinks that their own hobby horse is the most important thing for sure. Yeah. And so if you don't have regression analysis or you don't have customer validation to give you objective information about where you need to focus to get the most bang for your buck, it's really hard to make those again, objective trade off decisions that you need to make when you are trying to maximize your investments.
- [42:43]
B
Absolutely. So I want to get to the trend for the one that you said that you are most excited about. So what exactly. As it's stated in the Qualtrics report, what is this trend around personalization? And then I have my own like Opinions on it. So I'm curious to see what you're excited about with it.
- [42:59]
A
Yeah. So this is, consumers demand transparency over personalization tactics. And I think what I find so interesting here is that for years, companies have just assumed that customers would gladly trade their privacy for personalization, and that is just not true. So what we found is that while demand for personalization is growing, so 64% of consumers today say that they want tailored experiences, only 39% of customers trust companies to use their data responsibly.
- [43:33]
B
This is another one of those paradoxes that we're seeing.
- [43:36]
A
Yes, and this is, this is one, the personalization privacy paradox, like, is called a paradox for a reason. We also asked, you know, do you think that the personalization benefits you receive are worth the privacy trade offs? And only 41% of consumers said that they were. And then this is the part that, again, I think because I live in the CX world, really shocked me. When we asked customers about specific personalization methods, we saw like, just remarkably low comfort levels across the board. So the highest is 30% of consumers say that they are comfortable with basic things. Like companies remembering their purchase behavior or seeing their website behavior. Right. Like, things that I guess I take for granted. Like, of course companies know what I.
- [44:30]
B
Know I know before.
- [44:32]
A
And then, unsurprisingly, right. The more invasive or opaque the method becomes, the last, last comfortable customers feel. So only 16% say that they're okay with companies listening to or watching them through their devices. Again, completely unsurprising. But the largest group was 32% who said that they are uncomfortable with every single method of personalization. So I think, what? Wow. Yeah, but they.
- [44:59]
B
But then 64% want personalization, but they.
- [45:02]
A
Want personalization, but they don't trust companies to do it responsibly. So I think the issue here is not data collection again, it's trust. You know, I see most companies today getting this personalization equation backwards. So they are stockpiling information about who their customers are, right? Like their demographics and their purchasing behavior and browsing patterns. But they're missing out on what customers actually need in any given moment. So instead of just amassing more and more data, I think companies should instead here really be focusing on understanding their customer's current context and intent. What journey are they on with you? Have they already called your contact center three times before? Is this a product that they purchase frequently and then using that information to again, help them achieve their goals more quickly and efficiently? Because I think customers at this point are recognizing that personalization is really just fancy sales tactics. Right. It's clear what's in it for the company. They're getting more sales, they're pushing more product, but it's not necessarily clear what's in it for the customers.
- [46:22]
B
Which sort of ties back to what we're talking about with AI. Right. I can see how your business is going to save money if you invest in this, but what do I get out of it? Right.
- [46:30]
A
Social media has also taught us if we get something for free on the Internet, we're the product and, uh, they're selling our data. So I think there's just very low trust across the board in that. Except the place where we see trust is the highest is in Europe where they have GDP laws and regulation about how consumer data can be used.
- [46:50]
B
Oh, that is interesting because you did say this report was across 14 different countries. So did you see that difference in the response with them?
- [46:56]
A
Okay, yeah. Europeans are much more like, yeah, we trust them because legally they're being forced to do this.
- [47:04]
B
Like, okay, now I get it.
- [47:05]
A
Yeah.
- [47:06]
B
There. I think there was a stat in that, this trend as well around if a consumer trusted the company already, then they were way more okay. With personalization, it's like, how do you get to that bridge, how do you bridge this gap of like most. I don't trust most companies, but of the ones that I do that I'm like, okay. With personalization. It's. It's very complicated to kind of figure out how we bridge this.
- [47:26]
A
Yeah. And I. Exactly as you're saying, when customers say that they do trust a company with their personal data, that bumps up all comfort levels with personal personalization methods, about 10 percentage points. So we found customers want transparency about what's collected, they want control over how their data is being used, and they want the ability to easily delete their data. And I would say these are not complex demands. These are just the basics. And if companies don't do them, consumers are going to remain wary of sharing their personal data, even if it might genuinely lead to better experiences. And exactly like you're saying, this is going to have major downstream consequences because customers are not going to share their information for AI models. They're not going to try new experiences that the company is offering. Right. When you undermine the trust like this, it makes your life a lot harder down the line when you're trying to get customers to shift their behaviors in ways that are going to help your business.
- [48:27]
B
Yeah, I really feel like if we were to like summarize all these four trends into One, it's just this big. Like, how do we get our customers to trust US More like 2026 is the year of trust. Customer trust. Let's get it back.
- [48:40]
A
So we do. At Ex IM Institute, we do a year of every year. This year is like the year of connection. But we did year of trust last year. And I'm like, but this year is the year of trust, and next year is also the year of trust. And every year is the year of trust. We have a lot of data showing that when customers say that they trust a company, they do all of these business positive behaviors like recommending and repurchasing and forgiving the company if it makes a mistake and trying a new offering. So I completely agree. It is foundational to everything else that we've been discussing.
- [49:16]
B
I don't know if you guys measured this in your report, but did you see any difference in company size? Because, like, when I think about a small business that I work with, if they're personalizing things for me, I feel like, very receptive to it. I don't think it's weird at all because it's a. You have 20 people in your business. Like, I anticipate that you would know who I am. And my law needs cut this specific way. Oh, you have an upgrade for blah, blah, blah. Sure, I'm all about it. But then, of course, this, like, degrades as I get into a larger company where I'm like, oh, you are recommending this thing now suddenly I'm super skeptical of you.
- [49:46]
A
Yeah.
- [49:46]
B
So was there any differences in business size that played a role in this?
- [49:50]
A
So we don't look at it. So for our global consumer study, because it is global, we don't ask at a brand level. We ask an industry level. Like, have you interacted with a bank in the last, you know, 90 days? We have a U.S. consumer study where we do ask about specific brands. However, in order to get the sample size that we need, we only ask about the top. I think it's like 418 companies to ensure that we can get responses. So we haven't. But my intuition would completely align with what you're saying, that the larger the company is, the less you inherently trust them to take care of your needs and deploy AI responsibly and use your personal data responsibly, they start becoming more of kind of a faceless corporation.
- [50:39]
B
Yeah. Yeah. And it's funny, the companies that stand out, at least for me, like, I think of Costco like it's a huge company, but I. They have such good brand trust and I trust their pretty much everything that they do. So it is interesting the companies that do stand out, that are still large organizations but still somehow still give that like, mom and pop enough vibe that I trust you to do these things.
- [51:00]
A
And I'll say, you know, Costco has been at the top of our, again, that US consumer ranking for 15 years. Not the very tippy top, but I would say like, you know, in the top 10 consistently, we see a lot of other, other brands that I think would surprise people versus, you know, the more like sexy brands like Apple or Tesla. The ones that we actually see at the top are the ones that have very clear value propositions for customers and then deliver on them consistently every single time. So they're not promising super fancy, you know, bells and whistles, but they're like, here's what you can expect. And then we deliver on it in every single interaction, regardless of which store you're in, regardless of which product you're using, whether you're getting tires from us or ordering a vacation. Again, back to the trust. Like, we are going to reliably deliver on our brand promises. Those are the companies we see perform really well in our kind of brand tracking study.
- [52:13]
B
So from this report, we've gone through four, you know, really comprehensive trends. Some things I think are probably surprising to anyone listening, some things are not surprising. They all align with like, what we've experienced as consumers or seen in our own businesses. But from this, if you wanted our leaders listening today to like, walk away with a few core actions to take going into the next year, what would those be?
- [52:36]
A
The one that immediately comes to mind is, I would say, pick, you know, one to three of your high priority customer journeys and really try to understand them for a few reasons. Number one, I think that's going to give you a sense of which part of those journeys you can automate with AI or use AI to help people do more efficiently. Which parts of that journey are really important for maintaining human connection and differentiating yourself. That's also going to help you instrument your listening strategy. People tend to get very overwhelmed, given the entire world of customer signals and market signals out there, of figuring out how do we move from a few surveys to this more holistic listening program? And if you look across a journey, you can find what are those key moments that matter that we really need to make sure we're capturing feedback or behavioral signals, what some existing operational or behavioral data that we already exists with other teams that we can bring in to help understand this journey. And so I think that's a good place to start. And it's going to give you an outside in perspective of how customers are perceiving those core experiences rather than just an inside out. Here's how our company thinks customers are working through it. So I think that that will answer a lot of the trends that we're seeing.
- [54:07]
B
All right, I got one last fun question for you. What do you think is going to surprise us the most if we have this conversation in a year about 20, 26?
- [54:16]
A
I could go two ways. I could say that we would either be surprised at how little progress got made. And my argument for that would be everyone's talking about agentic now. But if you actually look inside companies, many of their processes are undocumented, they're messy, they're made up of workarounds and handoffs. And so when add AI and AI agents on top of that mess, you're not fixing it, you are amplifying the dysfunction. And so I could see that rolling out, you know, effective enterprise wide AI systems is actually a lot harder than people think and we're not going to move as fast as we think we will. So on the one hand I could see it being like, wow, we've really not made as much progress as I would have anticipated. On the other hand, I can see us being like, holy cow, we came five years in a single year. And I think a lot of that is going to depend on how these capabilities advance to some degree. Like Gemini 3 just came out and has moved the ball forward across a number of different fronts. But I also think it's going to be organizations figuring out some of those internal structures and change management issues that have been holding them up so far. So we found in our research that a lot of organizations are stuck in what I'd call pilot purgatory, the state of kind of fragmented experimentation that really fails to scale and capture AI's full potential. MIT Nanda just released a report that 90% of generative AI initiatives, enterprise wide gen AI initiatives have failed to see scale beyond pilots and reach full production with P and L impact despite tens of billion dollars of investment. So I think companies have really been bumping up against that barrier recently. And if companies by and large made a few changes, I think they could rapidly accelerate and start seeing some really incredible wins. There's a few large organizations I've seen do some really incredible things with AI and we could start seeing that on a broader scale.
- [56:29]
B
I think it's going to be both. Truthfully, I think half the companies, or maybe Even more, maybe 75% are going to be in the first bucket that you described of like, why are we itching along? Because they're going to start to feel these pain points. I mean, the pain points are becoming obvious as we look inside how these companies are rolling out enterprise AI. But unfortunately, when you're inside the company, it's really hard to like, you get stuck in bureaucracy and things don't move. But there's going to be the like 10% of companies over here that do just accelerate way beyond the what was possible imagine and there's going to be this divide. So I actually think your prediction is completely on point.
- [57:02]
A
Well, and one of the things I've just been doing this tour of executive dinners on the topic of AI, and one of the things that struck me is just the unbelievable range. You have some, like large, complex companies that are truly transforming their business and you have others who are like my executives still don't know what AI stands for. So there's such a range. And I would say the ones that are just like accelerating their success are the ones that invested a few years ago in things like data warehouse and data hygiene. And so they're working from a much richer, cleaner, more easily accessible and querier. That's not a word. But data set that can again accelerate their efforts very quickly. The ones I'm seeing really lagging behind have messy silo data. And that is just such an impediment for AI models.
- [57:57]
B
And what's unfortunate about that is it's not the sexy thing. Right. Like, the sexy thing is let's do AI now. Let's do agentic AI. Right. But like, oh, sorry, no, you need to do the thing that, you know, some of these companies were doing five years ago and clean up your data and spend all the time and investment it's going to take to do that. Luckily it's a little bit faster than it was a couple years ago. Because of AI, Right, Yep.
- [58:18]
A
Are helping with some of those. So you could leapfrog, right, where companies kind of had to do this the hard manual way a few years ago. But yeah, you're right, it is not the sexy glorified work.
- [58:30]
B
No, no, it's like if I'm the CEO of the company and I'm like, wait, we're spending all this money and time on data?
- [58:35]
A
Yes.
- [58:36]
B
And not AI. That's, that's the hard part.
- [58:39]
A
They're investing in the like flashy, sexy use cases that are giving these like high productivity and efficiency gains that look really good to the board. And they're not investing in the actual foundational work, like cleaning their data that doesn't have clear ROI at the moment, but is so important over the long run. So I think that's also a hurdle, is they're measuring the things that are less important rather than just focusing on the. On those foundational pillars.
- [59:14]
B
100%. I totally agree. Well, this has been fantastic. Thank you so much for running us through the entire report and sharing your, you know, trends and takeaways, especially on a late afternoon. I really appreciate the time. Yeah. And if any of our listeners are interested and they actually want to go read this report themselves, where should they go?
- [59:31]
A
Yep. If you look at Qualtrics, I mean, at this point, you can just Google Consumer Experience, Trends, 2026, Qualtrics, and that will get you there.
- [59:39]
B
Awesome. We'll also drop the link in the show notes if people have easy access to download it. But, yeah, that's great. And Isabel, where can people find you if they're like, I want to stay, you know, in connection with this woman who has so many good insights?
- [59:51]
A
Absolutely. Well, one of the good, good things about having an unpronounceable last name is that I'm very easy to find online. So feel free to connect with me on LinkedIn. Send me a note. Isabel Zidatny. So ZD ATNY. Hopefully I'm easy to track down and I love these topics. I love talking to the people who are actually in the trenches doing this work. So always happy to connect with and talk more about these ideas.
- [60:15]
B
Awesome. Well, thank you so much for joining us.
- [60:17]
A
Of course. This was great. I really appreciate it.