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    CONNECTIONS / PostgreSQL / PostgreSQL to Meta Custom Audience

    Your PostgreSQL tables, wired to Meta lookalike and suppression seeds.

    Signals reads your PostgreSQL tables through a read-only database user scoped to the PostgreSQL tables you name, then keeps Meta audiences synced as adds and removals so lists never drift so Meta sees match-ready audiences without an export.

    Talk to our team Explore the setup

    postgresql -> meta-custom-audience :: live

    1. ● postgresql → meta.audience :: live
    2. > read segments rows=26,301
    3. hash sha256(email,phone) consent=filtered
    4. route meta deliver
    5. ✓ delivered · 19,200 matched

    WHAT THIS ENABLES

    PostgreSQL to Meta Custom Audience

    Meta Custom Audience for PostgreSQL: Signals keeps Meta audiences synced as adds and removals so lists never drift straight from your PostgreSQL tables, hashed and consent-screened each time the read runs.

    • Signals keeps Meta audiences synced as adds and removals so lists never drift, reading your PostgreSQL tables each time the read runs.
    • Always-current lookalike seeds and exclusions, with no export step out of your PostgreSQL tables.

    WHAT FLOWS WHERE

    PostgreSQL to Custom Audience, mapped.

    Signals reads the customer segments from your PostgreSQL tables each time the read runs, hashes and screens each record, and posts the match-ready audiences to Meta's Custom Audiences API, keeping audience refresh cadence in view.

    Signals reads the customer segments from your PostgreSQL tables each time the read runs, hashes and screens each record, and posts the match-ready audiences to Meta's Custom Audiences API, keeping audience refresh cadence in view.

    WHO THIS IS FOR

    Built for the teams that own the number.

    Performance teams running first-party suppression and lookalike seeds, working out of PostgreSQL tables, views, and materialized views.

    Engineering teams running PostgreSQL who need lookalike seeds and suppression lists that track your live customer base out of PostgreSQL tables.

    HOW DATAHASH SETS IT UP

    From kickoff to verified events.

    1. Connect

      A read-only database user scoped to the PostgreSQL tables you name, mapped to Meta's Custom Audiences API and tuned for audience refresh cadence.

    2. Map

      Columns from your PostgreSQL tables align to Meta's Custom Audiences API in the visual mapper, hashed as the read runs and checked for audience refresh cadence.

    3. Deliver

      Each time the read runs, Signals reads your PostgreSQL tables and keeps Meta audiences synced as adds and removals so lists never drift, reads only the records changed since the last run, with audience refresh cadence watched in the debugger.

    WHAT YOU GET

    What ships with this use case.

    Lookalike seeds and suppression lists that track your live customer base from your PostgreSQL tables, delivered each time the read runs.

    Always-current lookalike seeds and exclusions out of your PostgreSQL tables, delivered each time the read runs without read load on the database climbing.

    Match feedback on audience refresh cadence from Meta's Custom Audiences API each run, tied back to your PostgreSQL tables.

    ON THE WIRE

    What Custom Audience actually receives.

    signals :: postgresql.meta-custom-audience :: wire

    1. ● signals :: audience upload
    2. > POST /customaudiences source=postgresql.segments
    3. schema ["EMAIL_SHA256","PHONE_SHA256"]
    4. num_received 26,301 · num_invalid_entries -180
    5. audience_id "1649068" · session "upsert"
    6. ✓ accepted match=73%
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    FAQ

    Asked on almost every call.

    How often does the PostgreSQL Meta Custom Audience sync run?

    Delivery tracks PostgreSQL, run by engineering teams running PostgreSQL: a near-real-time or scheduled sync of your PostgreSQL tables feeds Meta on that cadence. Each run reads only the records changed since the last run, so always-current lookalike seeds and exclusions holds up on audience refresh cadence. The live debugger confirms every delivery inline.

    What match rate should a PostgreSQL-sourced Meta Custom Audience batch expect?

    Coverage of hashed identifiers across your PostgreSQL tables decides it, and engineering teams running PostgreSQL own that inside PostgreSQL. A live email or phone matches into Meta; neither, and it will not. First-run feedback flags audience refresh cadence, which engineering teams running PostgreSQL then raise inside your PostgreSQL tables.

    NEXT STEP

    PostgreSQL to Meta Custom Audience, in production this week.

    Talk to our team All PostgreSQL use cases