If you’ve ever tried to stitch together a unified customer profile from a tangled mess of emails, devices, and nicknames, you know identity resolution is a beast. Now, Hightouch, a rising star in the data and AI-for-marketing space, says it has the answer.
Enter Adaptive Identity Resolution, launched today as part of Hightouch’s warehouse-native Customer Data Platform (CDP). The goal? Give businesses a way to reconcile disjointed customer data—cleanly, transparently, and directly in their data warehouse—while offering unprecedented flexibility between high-confidence precision and wide-reach guesses.
It’s a move that lands squarely at the intersection of two critical enterprise pain points: the need for accurate customer identities and the growing expectation of AI-powered personalization. Most tools force you to choose between rigid, exact-match identity logic or opaque machine learning models you can’t tweak. Hightouch says: why not both?
Deterministic Meets Probabilistic—No More Tradeoffs
Traditionally, deterministic identity resolution relies on exact matches (like email or phone number) to build a user profile. Great for accuracy. Terrible when you’ve got messy or incomplete data.
Probabilistic identity resolution, on the other hand, takes the AI route—using ML to infer connections across fuzzy data, like identifying that “Jon” and “Jonathan” on separate devices are probably the same person.
Hightouch’s Adaptive Identity Resolution lets you toggle between both approaches—“multi-zone matching,” as they call it—within the same environment. It’s like switching from a sniper rifle to a net, depending on what you’re trying to catch.
“We’ve built something entirely new,” said Tejas Manohar, Co-CEO of Hightouch. “Most identity resolution tools are either rigid or opaque. We’re giving users control, transparency, and flexibility. It’s a new way to think about identity.”
Built for the Modern Data Stack
Unlike traditional CDPs that require you to ship data into a third-party system—often a black box—Hightouch operates directly inside your existing data warehouse. That means no more duplicating data pipelines or compromising security and governance in the name of convenience.
Key features of the new release include:
- Multi-zone matching: Dial confidence up or down depending on use case.
- Warehouse-native architecture: Identity logic runs directly in Snowflake, BigQuery, Redshift, or Databricks—no offloading.
- Full transparency: See how the model makes decisions. Adjust logic without code.
- Real-time activation: Push clean profiles instantly to ads, email, CRM, and support tools.
This isn’t just another identity tool bolted onto a CDP. Hightouch flips the model—bringing identity logic to the warehouse rather than pulling data into the CDP. That’s a big deal for enterprises that are increasingly centralizing data infrastructure around modern platforms like Snowflake or Databricks.
Who This Impacts—and Why It Matters
Marketers, data engineers, and growth teams will likely be the biggest beneficiaries here. With Adaptive Identity Resolution, they can now tailor identity logic to fit the context—whether that’s ad targeting, personalized email, or customer service workflows.
The system doesn’t just clean up data for the sake of cleanliness. It’s about unlocking richer personalization, better measurement, and higher return on spend—without sacrificing privacy or transparency.
And it couldn’t come at a more relevant time. With the deprecation of third-party cookies and growing regulation around data governance, owning and resolving first-party data in-house is quickly becoming table stakes.
A Strategic Advantage, Not Just a Hygiene Fix
While competitors like Segment (Twilio), Amperity, or Adobe Experience Platform offer some level of identity resolution, they often obscure how it works or require vendors to do the heavy lifting. Hightouch’s new approach is more modular, more visible, and more adaptable.
This could give Hightouch an edge in a rapidly maturing CDP landscape, especially among enterprises looking to consolidate around the modern data stack. And with its AI models fully configurable and housed inside the warehouse, identity resolution is no longer a static feature—it becomes a living layer of your data strategy.
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