In short
Match rate is the percentage of records you send to an ad platform that the platform successfully matches to a known user. It applies to conversion uploads, where it measures how many offline sales matched a user, and to audience uploads, where it measures how many CRM contacts became targetable. The number is driven almost entirely by identifier coverage and quality: hashed email and phone captured at purchase or login match best, while formatting errors such as unnormalized phone numbers or casing applied before hashing silently destroy matches. Benchmarks vary by platform and identifier mix, so a single target figure is misleading. The honest way to raise a match rate is a baseline audit: send a representative sample, read the platform’s own match feedback, then fix the largest identifier gap first before chasing smaller ones. Match rate is the clearest proxy for whether your data is reaching the platform intact.
What drives your match rate?
Identifier coverage and quality. Hashed email and phone captured at purchase or login match best. Formatting errors (unnormalized phone numbers, casing before hashing) silently destroy match rates.
What is a good match rate?
Vary by platform and identifier mix. The honest answer is a baseline audit: send a sample, read the platform’s match feedback, fix the biggest identifier gap first.
What makes a match rate rise or fall?
A brand uploads a customer list and sees a low match rate. The cause is phone numbers stored without country codes; normalizing them to E.164 before hashing recovers a large share of the list, with no new data collected, only cleaner formatting.