CONNECTIONS / Snowflake / Snowflake to Meta Custom Audience
Snowflake segments, live inside Meta Ads Manager.
Signals reads the Snowflake table you designate, hashes each identifier, and holds the corresponding Meta Custom Audience to the same membership.
- ● snowflake → meta.custom_audience :: live
- > sync table CHURN_RISK_SEGMENT rows=36,920
- hash sha256(email,phone)
- route meta.custom_audience upsert
- ✓ audience refreshed · 30,215 matched
WHAT THIS ENABLES
Snowflake to Meta Custom Audience
Snowflake to Meta Custom Audience keeps Meta's Custom Audiences built from whichever table or view in Snowflake defines your best customers, hashing identifiers at read and refreshing adds and removals on your chosen cadence, so lookalike and suppression audiences never drift out of date.
- Warehouse tables acting as the control surface for Meta audiences.
- Churn-risk and LTV segments flowing into paid social the moment tasks rebuild them.
- Audience membership auditable with the same SQL you use for reporting.
WHAT FLOWS WHERE
Snowflake to Custom Audience, mapped.
Segment rows sync out of Snowflake on schedule, get hashed by Signals, and Meta's Custom Audiences API brings the audience to matching state.
Segment rows sync out of Snowflake on schedule, get hashed by Signals, and Meta's Custom Audiences API brings the audience to matching state.
Built for the teams that own the number.
Media buyers waiting on data teams for every audience refresh.
Enterprises consolidating activation onto governed warehouse data.
From kickoff to verified events.
-
Connect
A read-only Snowflake role granted on the segment schema alone.
-
Map
Table columns hashed to Meta's audience key format at query time.
-
Deliver
Scheduled upserts through the Custom Audiences API with size feedback.
What ships with this use case.
Paid social audiences that sit directly downstream of your dbt models.
Adds and removals applied together, so audiences never bloat with lapsed members.
Warehouse-side control over exactly which columns ever reach the pipeline.
What Custom Audience actually receives.
- ● signals :: audience upload
- > POST /customaudiences source=snowflake.CHURN_RISK_SEGMENT
- schema ["EMAIL_SHA256","PHONE_SHA256"]
- num_received 36,920 · num_invalid_entries 288
- audience_id "1622…" · session "upsert"
- ✓ accepted match=82%
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What refresh cadence keeps a warehouse-sourced Meta audience from going stale?
Daily is the common default, though the schedule can run anywhere from hourly to weekly depending on how often the underlying warehouse task rebuilds the segment table. Each refresh sends only the members added or dropped since the previous run, not a full re-upload, so a tighter schedule does not add meaningful load to your Snowflake compute.
What match rate is realistic when the audience comes straight from a warehouse table?
It depends on which identifiers the underlying table or dbt model carries. Rows with a current, hashed-ready email and phone typically match well; rows missing both will not match regardless of segment size. The accepted audience size is reported after every sync, so match quality is visible rather than assumed.
Can the same Snowflake segment feed more than one Meta ad account?
Yes. One table or view defined once in Snowflake can push to several ad accounts under the same Business Manager, each with its own refresh schedule and accepted-size reporting, so a single dbt model supports every team running Meta campaigns off the same customer base.
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