CONNECTIONS / GCS / GCS to Google Customer Match
Your GCS objects, wired to Google Customer Match.
Connect GCS and point Signals at your GCS objects; it projects your segments into Google Ads as Customer Match lists each time a new file lands, hashed and consent-checked for Google Ads.
- ● gcs → google.match :: live
- > read segments rows=11,234
- hash sha256(email,phone) consent=filtered
- route google deliver
- ✓ delivered · 9,437 matched
WHAT THIS ENABLES
GCS to Google Customer Match
GCS to Google Customer Match: your GCS objects, hashed and consent-checked, feed Google Ads as Signals projects your segments into Google Ads as Customer Match lists each time a new file lands.
- Customer segments from your GCS objects activated for Google Ads, as Signals projects your segments into Google Ads as Customer Match lists.
- Customer Match lists that add joiners and drop lapsed members each sync, drawn from your GCS objects by data teams landing exports in GCS.
WHAT FLOWS WHERE
GCS to Customer Match, mapped.
Each sync hands the customer segments from your GCS objects to Signals, which hashes and filters every record, then Google Ads' Customer Match API logs the match-ready audiences for the serving-size threshold.
Each sync hands the customer segments from your GCS objects to Signals, which hashes and filters every record, then Google Ads' Customer Match API logs the match-ready audiences for the serving-size threshold.
Built for the teams that own the number.
Data teams landing exports in GCS activating Google Customer Match straight from GCS objects.
From kickoff to verified events.
-
Connect
A read-only service account scoped to the one GCS bucket you name to feed Google Ads' Customer Match API, sized for the serving-size threshold.
-
Map
Signals picks up your GCS objects, and its columns map to Google Ads' Customer Match API in the visual mapper, hashed and checked for the serving-size threshold.
-
Deliver
On each run, Signals pulls your GCS objects, projects your segments into Google Ads as Customer Match lists, and processes only the newly dropped file, with the serving-size threshold in the debugger.
What ships with this use case.
Customer Match lists that add joiners and drop lapsed members each sync on every run, as Signals reads your GCS objects and processes only the newly dropped file.
Lists that self-maintain across syncs from your GCS objects, with transfer overhead steady because Signals processes only the newly dropped file.
A per-run match report from Google Ads' Customer Match API on the serving-size threshold, straight out of your GCS objects.
What Customer Match actually receives.
- ● signals :: audience upload
- > POST /user_list_operations source=google-cloud-storage.segments
- operation ADD · user_list "segment_57519"
- hashed_email sha256 "b02cf1…" · hashed_phone sha256 "3ad990…"
- members_uploaded 11,234 · members_matched 9,437
- ✓ accepted match=84%
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How often does the GCS Google Customer Match sync run?
The pace follows your GCS objects: Signals sends changes from GCS to Google Ads each time a new file lands. Because it processes only the newly dropped file, Customer Match lists that add joiners and drop lapsed members each sync stays current while data teams landing exports in GCS keep the serving-size threshold in view. Delivery needs no export and no manual upload.
What match rate should a GCS-sourced Google Customer Match batch expect?
Coverage of hashed identifiers across your GCS objects decides it, and data teams landing exports in GCS own that inside GCS. A live email or phone matches into Google Ads; neither, and it will not. First-run feedback flags the serving-size threshold, which data teams landing exports in GCS then raise inside your GCS objects.
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