In short
Customer Match is Google’s first-party audience product. You upload hashed identifiers, and Google matches them to signed-in users across Search, YouTube, Gmail, Shopping, and Display, then uses the audience for targeting, exclusion, lookalike seeding, and as a Smart Bidding signal. Its value is that it runs on data you own rather than third-party cookies, so it keeps working as cookie-based audiences decay. The operational catch is that lists themselves decay. A Customer Match audience is only as fresh as its last update, and a one-off CSV upload starts going stale the day it lands, as customers churn, change contact details, and new ones arrive. The fix is to sync from your CRM or warehouse on a schedule so the audience reflects current reality, and to send clean, normalized identifiers so match rates stay high. Datahash syncs Customer Match audiences from source on a cadence instead of relying on manual uploads, so the list stays current.
Operational reality
Lists decay. A Customer Match audience is only as good as its refresh cadence, which is why Datahash syncs from your CRM or warehouse on a schedule instead of one-off CSV uploads.
Why do Customer Match lists need refreshing?
A brand uploads a loyalty list once and reuses it for months. Over that time the audience drifts out of date as members lapse and details change. A scheduled CRM sync keeps the same audience current, so targeting and exclusions act on who the customers are now.
Reference: Google Ads Help, about Customer Match