Identity resolution

Identity resolution is the process of matching records from different sources, an email signup, a mobile app login, an in-store loyalty card, to a single underlying person or household, even when no single shared ID connects them directly. It typically combines deterministic matching, exact matches on email or phone, with probabilistic matching, statistical confidence based on overlapping signals like device, location, and behavior patterns.

The term overlaps heavily with identity stitching and record linkage, and is used somewhat interchangeably with both in practice; identity resolution is more common in the marketing and customer-data context, while record linkage is the broader statistical term used across research and public-sector data matching. The output feeds a unified customer 360 profile and is typically stored and managed inside a customer data platform.

Identity resolution matters because most organizations' data about a single customer is fragmented across systems that were never designed to talk to each other, and without resolving that fragmentation, analytics and personalization treat one person as several unrelated ones. Match confidence is the central tradeoff: aggressive probabilistic matching increases coverage but also the rate of incorrectly merging two different people into one profile, while strict matching misses real connections. Resolution built on personal identifiers also needs to account for pseudonymization and consent requirements governing how those identifiers can be used.