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    CONNECTIONS / PostgreSQL / PostgreSQL to TikTok Custom Audience

    Your PostgreSQL tables, wired to TikTok audience targeting.

    Signals reads your PostgreSQL tables through a read-only database user scoped to the PostgreSQL tables you name, then delivers first-party segments to TikTok as match-ready custom audiences so TikTok sees match-ready audiences without an export.

    Talk to our team Explore the setup

    postgresql -> tiktok-custom-audience :: live

    1. ● postgresql → tiktok.audience :: live
    2. > read segments rows=15,636
    3. hash sha256(email,phone) consent=filtered
    4. route tiktok deliver
    5. ✓ delivered · 12,822 matched

    WHAT THIS ENABLES

    PostgreSQL to TikTok Custom Audience

    TikTok Custom Audience for PostgreSQL: Signals delivers first-party segments to TikTok as match-ready custom audiences straight from your PostgreSQL tables, hashed and consent-screened each time the read runs.

    • Signals delivers first-party segments to TikTok as match-ready custom audiences, reading your PostgreSQL tables each time the read runs.
    • Targeting that mirrors your live segment, 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 TikTok's Custom Audience API, keeping match quality on TikTok 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 TikTok's Custom Audience API, keeping match quality on TikTok in view.

    WHO THIS IS FOR

    Built for the teams that own the number.

    TikTok advertisers seeding lookalikes and suppressing existing customers, working out of PostgreSQL tables, views, and materialized views.

    Engineering teams running PostgreSQL who need TikTok custom audiences mirroring the segment your data team publishes 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 TikTok's Custom Audience API and tuned for match quality on TikTok.

    2. Map

      Columns from your PostgreSQL tables align to TikTok's Custom Audience API in the visual mapper, hashed as the read runs and checked for match quality on TikTok.

    3. Deliver

      Each time the read runs, Signals reads your PostgreSQL tables and delivers first-party segments to TikTok as match-ready custom audiences, reads only the records changed since the last run, with match quality on TikTok watched in the debugger.

    WHAT YOU GET

    What ships with this use case.

    TikTok custom audiences mirroring the segment your data team publishes from your PostgreSQL tables, delivered each time the read runs.

    Targeting that mirrors your live segment out of your PostgreSQL tables, delivered each time the read runs without read load on the database climbing.

    Match feedback on match quality on TikTok from TikTok's Custom Audience API each run, tied back to your PostgreSQL tables.

    ON THE WIRE

    What Custom Audience actually receives.

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

    1. ● signals :: audience upload
    2. > POST /dmp/custom_audience source=postgresql.segments
    3. id_schema ["EMAIL_SHA256","PHONE_SHA256"]
    4. action "add" · audience_id "aud_68515"
    5. id_list_size 15,636 · matched 12,822
    6. ✓ accepted match=82%
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    FAQ

    Asked on almost every call.

    How often does the PostgreSQL TikTok 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 TikTok on that cadence. Each run reads only the records changed since the last run, so targeting that mirrors your live segment holds up on match quality on TikTok. The live debugger confirms every delivery inline.

    What match rate should a PostgreSQL-sourced TikTok 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 TikTok; neither, and it will not. First-run feedback flags match quality on TikTok, which engineering teams running PostgreSQL then raise inside your PostgreSQL tables.

    NEXT STEP

    PostgreSQL to TikTok Custom Audience, in production this week.

    Talk to our team All PostgreSQL use cases