The Loyalty Blueprint: How to Balance Consumer Privacy & Personalization

Consumers are creating a growing “personalization paradox” when it comes to AI in 2026. They want personalized experiences more than ever, but they’re equally anxious about how brands use their data. CapTech’s proprietary consumer research reveals that while AI-driven personalization can strongly influence purchase decisions, trust and transparency remain the biggest barriers.

CapTech Principal and CX Growth Lead, Bree Basham, and Research Lead, Lea Moon, discuss what to expect with AI in 2026, what we are seeing that drives loyalty, and how brands can thoughtfully balance value and privacy.

Listen in to learn more:

• High‑value, in‑the‑moment personalization increases willingness to share data.
• AI comfort is rising but opt-out options and human fallback remain essential.
• Trust improves when brands use plain language and transparency in data use.
• Consumer adoption varies by mindset – not age or demographic.

Read the full research here: https://www.captechconsulting.com/articles/2025-consumer-survey-solving-the-personalization-paradox

Transcript

Bree Basham:

Hello everyone and welcome back to the CapTech Trends Podcast. I'm your host for today, Bree Basham. I'm a partner at CapTech and lead a lot of our customer experience work as well as work in our marketing and go to market spaces. And joining me, I have Lea Moon. Lea is one of our senior researchers on our customer experience team and she led this last round of consumer research that we're going to dive in today. So welcome, Lea.

Lea Moon:

I'm excited to talk about it.

Bree Basham:

We're excited to get into it. So let's dig again. This is actually the fifth year we've done the consumer research, which is hard to believe, but I was double checking this morning and realized it had been five years. This year we are researching all about what consumers are expecting in 2026 and spoiler alert, there is a bit of a focus on AI.

Lea Moon:

Yep.

Bree Basham:

Can you tell us just a little bit of the mechanics of how the survey was conducted?

Lea Moon:

Sure. So we went out to about 450 consumers nationwide. We asked a series of questions ranging from personal use on AI to preferences for personalization and what really drives brand loyalty. The focus being on really understanding how people see AI fitting into their lives and what the plans are for the future.

Bree Basham:

And understanding, I feel like a big part of this is always understanding consumer sentiment and preferences and sort of what's driving their choices.

Lea Moon:

Yes, exactly.

Bree Basham:

Awesome. So we titled this article and this set of insights, The Personalization Paradox. And I love the name, but break down a little bit for us sort of what the meaning behind that is and how that ties to the outcomes.

Lea Moon:

Sure. So we saw that 100% of our respondents listed privacy and security as a top concern when it comes to things like AI and personalization. And yet we found only 52%, so just above half, are willing to provide the data that is necessary to drive a personalized experience. And that is very, very telling of the sort of battle that we're going to see brands facing in the coming year, this importance. And four times as likely, those who highly value personalization are four times as likely to purchase. And yet I don't want to give you the data that's necessary for you to give me that experience that I'm telling you is so valuable. And that's The Personalization Paradox.

Bree Basham:

Yeah. I saw that stat, that 100%. And we've done a lot of these research studies, you and I over the years, and 100% doesn't come up often.

Lea Moon:

Very rarely. As a researcher, you never see 100%.

Bree Basham:

I feel like this actually might be the first I've seen, but I saw that and it was tied to data and privacy being very important. And I always think about how we can win. How do we make the experience worthwhile and what are people getting in exchange for giving something up? And I really think the key to moving consumers from distrust to this space of brand loyalty is that transparent value exchange. They have to feel that it's worth it.

Lea Moon:

Correct. And so 94% say that personalization is going to influence their brand choices. 44% of our respondents rating it very important. And one of the really interesting things that we saw was this incredible concern over security and privacy. And yet when a person could perceive a very high value in personalization, there became a willingness to provide data that originally they wouldn't be able to do. So it was sort of like, "I'm willing to give you this if you can tell me exactly what it is you're using it for and what the value is." Or, "Exactly what you're using it for, and then show me and let me feel that it is truly valuable to my experience."

Bree Basham:

That makes sense. What they're giving, why it matters, and what they're getting in return.

Lea Moon:

Exactly.

Bree Basham:

Okay. Let's talk about sort of the fact that you mentioned personalization is driving intent.

Lea Moon:

Yes.

Bree Basham:

And not only that, frankly, it's driving purchases, which is even more valuable.

Lea Moon:

Yes.

Bree Basham:

But we often talk about in these types of conversations, the rates for brand loyalty, understanding what will convert a consumer. AI has now added this hyper, real time predictive edge to personalization that we have not seen before. It's taking it to this new level. In the survey, what types of personalization were you hearing that were hitting the mark and driving that intent?

Lea Moon:

Yeah. So personalization when it is contextual, so when it is in the moment naturally fits in, so it's not something that feels, it needs to feel sort of effortless. It needs to feel very relevant. So we saw things like making an experience tailored to me is highly valuable to somebody, even more so in some cases than being able to provide a targeted offer, but being able to show that you know me. So making things relevant, making things feel helpful. So very small things, but in the moment. So rather than just looking at what people are clicking on, looking at their data to truly understand what they need. In a situation where, think of I've already bought the boots, so stop trying to sell me the boots and use that understanding to drive another sense of personalization that shows that you get me.

Bree Basham:

Yeah. Add the skirt to that that seems to make a good outfit.

Lea Moon:

Exactly, exactly.

Bree Basham:

I always think of it as like, I think of personalization as almost, when done right, removing roadblocks throughout an experience. Pick that up, that's more of an open road for the consumer. Pick up the next step and they just can sail through and the AI is anticipating and anticipating their next move and interpreting how it should respond.

Lea Moon:

Yes. And what's interesting is we saw 61% said that in the past year, they have seen an increase in their AI usage. People are accepting of AI. 82% recognize when AI is being used in an experience. They're gaining comfort with it, but it needs to be valuable. It needs to be contextual in the moment, relevant to what I'm doing right now, effortless. And then the other key to that was really allowing them to opt out if necessary, getting them to a human as quickly as possible if they either don't want to participate in the AI experience or it's not quite going the direction they're hoping it will. Those were all key in driving a positive experience.

Bree Basham:

Awesome. One of the things that came out on the executive side of the research that we did, which was the companion piece to this one, and that one, while this focused on hearing from consumers, that piece focused on hearing from executives and trying to marry the executive reality with the consumer perspective. So on the executive side, executives understood that consumers were looking for personalized experiences, but I saw the biggest gap between almost everything we learned in this space because many companies are lacking the data infrastructure that needs to be in place to produce this real time effective personalization. And when the data is fragmented, as we know, it's very difficult to unify those customer insights across channels. So any thoughts on that barrier to accelerating this personalization? It feels like the technology is there in theory, but companies are having a hard time sort of putting that into action because of those data barriers.

Lea Moon:

Yep. And I think the large message there is there is a tremendous value in putting the money and effort into a data infrastructure that is going to support AI and personalization because people have said that that is so critical to them. It's so important. I think the keys to it go back to that moment in time, areas where we saw people really valuing AI and what the data can do in search and learning, in personal time saving. So while your data structures may be fragmented, how can you take a piece of it, even and drive a really small but highly valuable personalized experience that's going to be a quick win and get people to sort of dip the toe in and test-

Bree Basham:

Build upon it.

Lea Moon:

Yeah. And once you can do that, the other smaller things will come with it.

Bree Basham:

Yeah. I think we've talked about starting small, expanding strategically. It makes me think of that. Completely agree. You can show a lot of value in incremental ways and still still end up in a win. Okay. Well, we talked about why personalization is valuable. Let's go to the flip side of the paradox, which is the building trust part. For brands, I think they see that there's this clear desire for personalization. We have the 94% of people saying personalization influences their brand choices. They find it highly valuable. However, as we saw with the 100%, they care even more about the privacy risk. So what would you say brands need to do to earn that trust?

Lea Moon:

Yeah. And to add to that a little bit, the research showed us 65% are concerned about privacy breaches. Six in 10 are worried about things like behavioral tracking and a lack of regulation. And to put on top of that, two out of three of the people who responded to our survey had no clue how their data fits into AI. And so there's a huge hurdle that we're trying to get over when it comes to trust, because we're starting with like this basic foundation of zero trust, but it's incredibly important. Ways that you can get past that, make transparency tangible. So using plain language, explain why I'm taking your data and this is exactly how AI is going to use it.

Lea Moon:

Making it very easy to give the control to the consumers to say, I had an experience with, I can't remember which AI tool it was where I typed in some information and it said, "This is not private. You're about to share a name." That's huge to stop somebody in the moment and say, "This is how we're about to use your data. Are you sure you want to do that?" And those sorts of things are going to go a long way in driving that trust. And that is where we get to this idea of privacy by design. So building privacy into the design of what you're doing. Compliance can't be a checkbox. They need to be a partner at the table and it needs to be very clear in the experience that compliance was part of that.

Bree Basham:

Yeah, makes sense. And you talked a lot about the communication sort of side of that, having the privacy and security measures in place, but that makes me think of ethical AI practices.

Lea Moon:

Yes.

Bree Basham:

And so all the things you said I feel like are helpful and are necessary to a large degree to thrive in today's environment, but still not quite enough. What else do we need to be thinking about?

Lea Moon:

So ethical AI is a competitive advantage. So practices like mitigating algorithmic bias are not just going to protect reputation, but they are going to help the users feel much more secure in what they're doing because they are definitely things that are driving high concern. So when you can demonstrate the fairness and the accountability in how AI is going to make decisions, it signals that personalization isn't happening at the expense of trust.

Bree Basham:

Let's shift into sort of the third area I want to talk about today is around the consumers and the segments that we uncovered and their mindset. So I know a key piece of this research that we all found pretty fascinating was around the behavioral segments and what we identified was not necessarily what we expected. Can you share a little bit more both about the segments we uncovered and maybe what the surprise was there?

Lea Moon:

Yeah. So we identified four segments, what we call our committed adopters. These are the people who are bought in, roughly 8% of our population were committed to adopters. We found a group, this was the largest group called curious explorers. So these are people who are using AI maybe monthly for things like learning and research. They're intrigued, but there's some question and some insecurity. The next group being our engaged skeptics. So these are people who are participating in AI, sometimes reluctantly, really neutral in how they're feeling about AI and what it can do. Usage is a little less frequent than others. And then our cautious observers, which was about 12%. So these are the people who were like, I think one of the quotes was, "I just don't have a use for AI and I don't see a need for it. " So the really interesting thing about these segments was when we looked at them, there was zero correlation between age, gender, or even like technical savviness or experience.

Lea Moon:

So instead, these segmentations were driven by all of that stuff we just talked about, the mindset around trust and personalization and understanding of how data is being used and the ethical elements that come with an AI experience. So to think of it this way, then you can have a Gen Z consumer who is completely uninfluenced by AI. They're untrusting, they're going to avoid it. And at that flip side, you've got a boomer who is using it daily, who has seen the value that it's driving in their life. And what this means then is success is not going to be one size fits all, and it's not going to be driven by typical age and demographics. It's really going to have to look at the mindset.

Bree Basham:

Yeah. I found that really interesting as well. And I noticed, especially with that curious explorers group, that was the second group you mentioned, they are using AI. I mean, it was 56%, so it's the majority of the segments by far. Now everywhere I go when I look around the room, I think, "That's probably a curious explorer next to me." Because it's most of us. But one of the things that I found interesting, you mentioned they're still not fully trusting. When I dug into that, I noticed that a lot of what they weren't trusting were the companies that were behind the technology. And so again, this goes back to the paradox, but I think with all of these groups, the fact that all of them have that room to mature, we're very early in this process still.

Bree Basham:

The fact that it is hitting all ages and demos the same way, or sort of in the same ways, I guess I should say, signals that this is... I mean, that's the power of AI. We've never seen anything come in with quite this amount of force and hit so quickly and it's hitting everywhere, but the fact that we still have people at all these different levels, I think there's a lot of optimism for progressing people along the path and increasing their usage, trying to get more people into these committed adopters.

Lea Moon:

Yeah. And one of the things we saw in the two middle segments, the cautious or the curious explorers and the engaged skeptics was a high level of neutral sentiment in their responses. And when you see neutral sentiment that's very factual, "AI exists. AI is presented to me. AI is something I'm going to have to learn how to use." But at that point, as an executive or as a brand, your goal is to move them from neutral to either positive or negative. And so when you look at the mindset then, and what we can understand about these, we can tailor experiences and rollouts and adoption to address the concerns that each of them have, to make sure that you are moving them from that neutral sentiment into positive rather than negative, because really, they're yours to lose.

Bree Basham:

That's right, yep.

Lea Moon:

And one of the things that you can do is those committed adopters, while it's only 8%, these are the people who are gung ho AI, use them. A key factor we saw in our middle area was this, "I still need a human." Use the committed adopter as the human-

Bree Basham:

As influencers, yeah.

Lea Moon:

That's going to influence it as the backup to say, "Hey, let me help you dip your toe in the water and try this and I'm going to be here to support you." Test your experiences with those committed adopters. Conversely, when you're looking at your cautious observers, that 12% may... Just make sure you're building positive non-AI experiences to keep them happy.

Bree Basham:

Optionality into those experiences, 100%. You mentioned usage a moment ago, and it got me thinking about how we use these segments overall. So we've gone to the trouble of taking the data, slicing and dicing it, coming up with these four segments. How can organizations use these or should they think about using these in their day-to-day?

Lea Moon:

Yeah. So one of the important things to think about with these segments is that you carry your personal mindset into a business environment, into your work environment. And so thinking about the segmentation, it applies to both an employee audience or to a consumer audience. So as you're thinking about rolling something out to your consumers, understanding that you are going to have a mindset that makes up 54%, how do you account for their concerns and build experiences that address those and offset maybe what they're thinking about. On that same side, as you think about rolling out AI for the purpose of employee efficiency or workplace efficiencies, you're going to meet that same breakdown of audiences. You're still going to have your committed adopters and your cautious observers and-

Bree Basham:

And a big group in the middle.

Lea Moon:

And a big group in the middle. And how do you use them? It's going to be the same tactics and approaches and mindsets that you see on the consumer side.

Bree Basham:

Yeah, makes perfect sense. Know who your customers are.

Lea Moon:

Exactly.

Bree Basham:

All right. So as we near the end here, I want to come back to The Personalization Paradox.

Lea Moon:

Yes.

Bree Basham:

The research shows that brands need to strive for these intuitive, but purposeful personalization experiences. We need to prioritize transparent data and privacy practices. And now we've also given a lot of things to think about with these new audiences to help inform brand approaches. Other than all of that, what would you say sticks in your mind as a takeaway that people can move forward with from this?

Lea Moon:

I think taking all of this together, personalization, privacy, trust are not three separate things. They're very interconnected. They are one conversation and purposeful personalization is going to work best and be more highly valued when people feel confident that their data is being handled responsibly.

Bree Basham:

I thought about that as well and what stuck out to me is that we can resolve The Personalization Paradox with those genuine human relationships that you're building with customers. Building trust is building a relationship. And so it's ironic, but I think that's, at the end of the day, what's going to help make all the technology work is still having that human element into how it is experienced and consumed. And that's ultimately, I think, what's going to allow people to feel a little bit more comfortable.

Lea Moon:

Exactly. The personalization delivers when it delivers high value and clear benefits is going to build trust and loyalty. That trust and loyalty will be seen by a willingness to engage with AI, which in turn will get you more data, which gets you more personalized experiences.

Bree Basham:

Better experiences. Well, Lea, thank you for joining me today.

Lea Moon:

Thank you.

Bree Basham:

And thanks to the team that you worked with that helped to bring this to life. For everyone listening, you can access the full research report that we discussed today. We just touched on really lots more in the report. You can visit us at captechconsulting.com to find that. The full article is there. It is called The Personalization Paradox, and you can find that in our insights section. And while folks are there, I mentioned we also did a second piece of research with C-suite executives. That heavily focuses on the return of investment around AI. So a lot of good stuff in there. Look out for that companion piece too. Thanks for tuning in.

Lea Moon:

Thank you.

Speaker 3:

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