Brands are racing to deliver hyper-personalized experiences, using customer data to tailor every interaction—from emails and app notifications to in-store recommendations.
Algorithms analyze preferences, devices track behaviors, and AI agents predict next moves, all in the name of making the customer journey seamless.
However, PwC’s annual Customer Experience Survey reveals a critical tension.
Executives tend to assume more data equals more value, but while 53% of consumers say they’re willing to share personal information if it improves their experience, an overwhelming 93% will walk away from a brand that mishandles their data.
Nine out of 10 consumers are willing to share some type of personal data for more personalized service, the survey found, but their trust is contingent on what a company collects, how they use it, and whether the benefit of giving up the data feels tangible.
In other words, every personalization strategy comes with a tripwire. Cross it, and trust collapses.
“A lot of people don't feel comfortable giving more information out unless they're going to receive something, one, of value, and then two, anything beyond their email—which is what we saw consistently across the generations—where there was some comfort in giving that information, people were hesitant to provide other information, especially on the unauthenticated side,” George Korizis, Customer Strategy Partner at PwC, told CX Today in an interview.
“When it started to get into more [Personally Identifiable Information](PII), people really clamped down.”
Yes, the majority of consumers are willing to share some personal data. But that willingness drops off fast when the data gets more intimate.
Biometric scans, real-time location tracking, or behind-the-scenes profiling raise red flags. In a world where data breaches, algorithm overload, and digital overreach are constant risks, brands have to earn the right to personalize.
The growing use of large language models (LLMs) in collecting and handling customer data has added a new layer of complexity to the privacy conversation. As Korizis said:
With the advent of AI and these hidden rooms with the LLMs controlling further upstream in the funnel, this is where it becomes tricky when it comes to privacy and security.
Privacy Isn’t Compliance — It’s Strategy
On one hand, AI supercharges personalization—predicting customer needs, analyzing their behavior, and automating responses at scale. On the other, it can feel like a black box.
Customers often don’t understand how their data is being used, and many companies can’t fully explain it either. That opacity makes it harder to draw the line between helpful and invasive. When algorithms quietly stitch together insights from clicks, voice commands and even tone of voice, the creep factor rises.
There’s also a power shift quietly happening behind the scenes. As AI tools like ChatGPT increasingly handle customer interactions, search queries, and even drive purchases from their own embedded checkout, companies are handing over part of the customer experience to systems they don’t fully control.
These models decide what information to show, how to phrase it, and increasingly, how to nudge users toward certain products or actions.
“Even players who were progressive at the time are now going to be forced to move outside of their comfort zone in what they own from an experience standpoint, and have to rely on a third party to put their interests out there,” Korizis said.
So there's a privacy aspect and security for the end consumer, and then there is the IP protection, the positioning of the brand, and the brand equity that potentially may be lost for the companies that now rely on those LLMs to represent them, and they don't control how the LLMs do that.
“The entire cycle is shifting, and a lot of our clients—which is backed by the study—feel that a lot of what's happening is executives at companies are the ones that are pushing towards implementing AI, implementing technology for technology's sake,” Korizis said, because they need to be seen as keeping pace, rather than being led by what consumers want.
So how can companies use data to build trust rather than feed into concerns that would erode it? It’s about building anonymized profiles and making inferences based on how similar customers act, Korizis said:
“Companies that are at the forefront of creating insights use their first-party data, what they already know about the customer; then they will seek secondary and third-party data to augment what they have; and then they will go down the path of personalization… They have a lot of information before you even get asked to provide the additional information.”
“It's going to become an exchange of data for value, and the companies that [succeed] are able to show that they can provide that value securely, they can provide the value into a good or service that the consumer will benefit from truly.
“It's not just the company benefiting from getting the consumer's data. Those are the ones that are going to create lasting relationships, and we're going to see loyalty building.”
Leading brands are shifting toward intentional, privacy-first personalization—not because regulators demand it, but because customers reward it. This shift changes the question from “What data can we collect?” to “What data should we collect to deliver real value?”
Finding the Sweet Spot
The brands that get it right don’t overreach. Instead, they stick to less intrusive data that still has a high impact, such as preferences, purchase history and behavior.
They’re upfront about what they’re collecting and why, and they make sure customers see the benefits right away. The result? Experiences that make customers feel understood, not watched.