CONNECTIONS / BigQuery / BigQuery to Google Customer Match
From BigQuery datasets to Google Customer Match.
Point Signals at the dataset behind a read-only service account, and it projects your segments into Google Ads as Customer Match lists on the cadence your scheduled query already keeps.
- ● bigquery → google.match :: live
- > read audiences.segment_members rows=43,832
- hash sha256(email,phone) consent=filtered
- route google deliver
- ✓ delivered · 38,134 matched
WHAT THIS ENABLES
BigQuery to Google Customer Match
BigQuery to Google Customer Match: A scheduled query reads the customer segments in your BigQuery tables, and Signals projects your segments into Google Ads as Customer Match lists, hashed and consent-checked whenever the scheduled query reruns.
- Signals projects your segments into Google Ads as Customer Match lists, reading your BigQuery tables whenever the scheduled query reruns.
- Customer Match lists that add joiners and drop lapsed members each sync, fed by analytics engineers running BigQuery scheduled queries.
WHAT FLOWS WHERE
BigQuery to Customer Match, mapped.
A scheduled query hands the customer segments to Signals, which hashes and consent-filters each row before Google Ads' Customer Match API logs the match-ready audiences for the serving-size threshold.
A scheduled query hands the customer segments to Signals, which hashes and consent-filters each row before Google Ads' Customer Match API logs the match-ready audiences for the serving-size threshold.
Built for the teams that own the number.
Analytics engineers running BigQuery scheduled queries who need Customer Match lists that add joiners and drop lapsed members each sync.
From kickoff to verified events.
-
Connect
A read-only service account with dataViewer on the one dataset you nominate to feed Google Ads' Customer Match API, sized for the serving-size threshold.
-
Map
A scheduled query reads your BigQuery tables, and its columns map to Google Ads' Customer Match API in the visual mapper, hashed and checked for the serving-size threshold.
-
Deliver
Whenever the scheduled query reruns, Signals projects your segments into Google Ads as Customer Match lists, scans only the rows the query changed, with the serving-size threshold watched in the debugger.
What ships with this use case.
Customer Match lists that add joiners and drop lapsed members each sync on every run, since Signals scans only the rows the query changed.
Lists that self-maintain across syncs, delivered whenever the scheduled query reruns without BigQuery slot cost climbing.
Each run returns a match report on the serving-size threshold from Google Ads' Customer Match API, read from your BigQuery tables whenever the scheduled query reruns, at flat BigQuery slot cost.
What Customer Match actually receives.
- ● signals :: audience upload
- > POST /user_list_operations source=bigquery.audiences.segment_members
- operation ADD · user_list "segment_91746"
- hashed_email sha256 "b02cf1…" · hashed_phone sha256 "3ad990…"
- members_uploaded 43,832 · members_matched 38,134
- ✓ accepted match=87%
Adjacent moves on the same stack.
from BigQuery
BigQuery to Meta Custom Audience
BigQuery to Meta Custom Audience: A scheduled query reads the customer segments in your…
Learn more
from BigQuery
BigQuery to TikTok Custom Audience
BigQuery to TikTok Custom Audience: A scheduled query reads the customer segments in your…
Learn more
same use case
ActiveCampaign to Google Customer Match
ActiveCampaign to Google Customer Match: Signals reads your ActiveCampaign contacts and…
Learn moregeneric
Google Customer Match
Datahash builds and refreshes Google Customer Match audiences from your CRM, warehouse, or…
Learn moreAsked on almost every call.
How often does the BigQuery Google Customer Match sync run?
The scheduled query sets the pace: rebuild the customer segments nightly and delivery to Google Ads is nightly, or refresh hourly for an hourly feed. Each run only reads the rows the query changed, so Customer Match lists that add joiners and drop lapsed members each sync stays current for the serving-size threshold while BigQuery slot cost barely moves.
What match rate should a BigQuery-sourced Google Customer Match batch expect?
Coverage in your BigQuery tables decides the rate, not BigQuery. A row with a current hashed email or phone matches; one missing both cannot, however the query is tuned. The first run's report from Google Ads' Customer Match API sets a baseline, the number growth teams feeding Google audiences from governed first-party data weigh against the serving-size threshold.
NEXT STEP