Bianca Guidry
Senior Director, Customer Strategy & Relationship Management
When I talk to retailers about identity resolution, I’ve noticed something interesting: most people think they already understand what it means. They’ll say, “That’s where we connect customer data and build a unified profile.” They’re not wrong. But that definition only applies to customers you already know.
Most identity solutions are designed to organize information about people who have already identified themselves through loyalty, logins, or other known identifiers. The harder challenge—and the one I think will define the next phase of identity resolution—is understanding the customers who never identify themselves at all.
The way I usually explain it is with a simple analogy. Most identity platforms operate like a hotel concierge. They’re incredibly helpful once someone has checked in. They know who they’re working with because the customer has already introduced themselves.
The problem we’ve focused on solving is different. It’s much closer to detective work. You’re starting with a transaction, a payment signal, or a pattern of behavior and trying to understand who that customer is without asking them to identify themselves every time.
That distinction matters. Because the next phase of identity resolution isn’t about creating better profiles for customers you already know—it’s about gaining visibility into the customers you don’t.
The Part of the Customer You’re Not Seeing
Most retailers are working with better data than they were even a few years ago. Systems are more connected. Reporting is cleaner. Loyalty programs, apps, and digital channels have made it easier to understand the customers who identify themselves.
But that’s still only part of the story.
On average, only about 25% of transactions are tied to customers who are actually known—loyalty members or identifiable users. The rest are anonymous. That doesn’t mean those customers are new. They may be regulars. They may be high-value shoppers. But without a way to connect transactions back to people, much of that behavior remains invisible.
You can see what happened. You can’t always see who drove it.
When the Data Looks Right—But the Conclusion Isn’t
When you’re only looking at known customers, the patterns in your data can look complete even when they’re not. A team might see loyalty engagement decline and assume customers are visiting less often. But some of those same customers may still be shopping regularly—they simply aren’t identifying themselves on every transaction. What looks like disengagement may actually be a visibility problem.
The same thing can happen with marketing performance, store trends, category behavior, or repeat visits. If you’re missing a large portion of customer activity, it’s easy to draw conclusions from a dataset that doesn’t reflect the full story. The data isn’t wrong. It’s just incomplete.
You might shift spend away from a campaign that is influencing more people than you can measure. You might overvalue a segment simply because it’s easier to see. You might misread whether a store is underperforming, whether a customer has lapsed, or whether a promotion is actually changing behavior.
The risk isn’t that retailers don’t have enough data. The risk is that the data they can see starts to stand in for the customers they can’t.
What Comes Next
A lot of the conversation in the industry has focused on creating a single source of truth. That’s important. Retailers need connected systems and reliable data. But organizing known-customer data doesn’t solve the harder problem: understanding the customers who never identify themselves.
This is why I think the phrase data without context resonates right now. Most retailers don’t have a data problem. They have a visibility problem. They have transactions. They have customer records. They have signals. What’s missing is the ability to connect more of those signals back to actual customer behavior. And that’s where identity resolution is headed.
The most interesting innovation happening in identity today isn’t helping retailers learn more about known customers. It’s helping them uncover the customers they didn’t know they could see at all. Because once you can see more of your customers, you can make better decisions for your business.
