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    CONNECTIONS / IBM DB2 / IBM DB2 to Meta Custom Audience

    Db2 tables into Meta, built for Meta lookalike and suppression seeds.

    Connect IBM DB2 and point Signals at your Db2 tables; it keeps Meta audiences synced as adds and removals so lists never drift each time the read runs, hashed and consent-checked for Meta.

    Talk to our team Explore the setup

    ibm-db2 -> meta-custom-audience :: live

    1. ● ibm db2 → meta.audience :: live
    2. > read segments rows=13,034
    3. hash sha256(email,phone) consent=filtered
    4. route meta deliver
    5. ✓ delivered · 10,949 matched

    WHAT THIS ENABLES

    IBM DB2 to Meta Custom Audience

    Meta Custom Audience for IBM DB2: Signals keeps Meta audiences synced as adds and removals so lists never drift straight from your Db2 tables, hashed and consent-screened each time the read runs.

    • Customer segments from your Db2 tables activated for Meta, as Signals keeps Meta audiences synced as adds and removals so lists never drift.
    • Lookalike seeds and suppression lists that track your live customer base, drawn from your Db2 tables by enterprise data teams on IBM DB2.

    WHAT FLOWS WHERE

    IBM DB2 to Custom Audience, mapped.

    Signals reads the customer segments from your Db2 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 Db2 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, with the records already in Db2 tables and views.

    Enterprise data teams on IBM DB2 activating Meta lookalike and suppression seeds straight from Db2 tables.

    HOW DATAHASH SETS IT UP

    From kickoff to verified events.

    1. Connect

      A read-only database user scoped to the Db2 tables you name to feed Meta's Custom Audiences API, sized for audience refresh cadence.

    2. Map

      A scheduled read pulls your Db2 tables, and its columns map to Meta's Custom Audiences API in the visual mapper, hashed and checked for audience refresh cadence.

    3. Deliver

      On each run, Signals pulls your Db2 tables, keeps Meta audiences synced as adds and removals so lists never drift, and reads only the records changed since the last run, with audience refresh cadence in the debugger.

    WHAT YOU GET

    What ships with this use case.

    Lookalike seeds and suppression lists that track your live customer base on every run, as Signals reads your Db2 tables and reads only the records changed since the last run.

    Always-current lookalike seeds and exclusions from your Db2 tables, with read load on the database steady because Signals reads only the records changed since the last run.

    A per-run match report from Meta's Custom Audiences API on audience refresh cadence, straight out of your Db2 tables.

    ON THE WIRE

    What Custom Audience actually receives.

    signals :: ibm-db2.meta-custom-audience :: wire

    1. ● signals :: audience upload
    2. > POST /customaudiences source=ibm-db2.segments
    3. schema ["EMAIL_SHA256","PHONE_SHA256"]
    4. num_received 13,034 · num_invalid_entries -299
    5. audience_id "1641809" · session "upsert"
    6. ✓ accepted match=84%
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    FAQ

    Asked on almost every call.

    How often does the IBM DB2 Meta Custom Audience sync run?

    The pace follows your Db2 tables: Signals sends changes from IBM DB2 to Meta each time the read runs. Because it reads only the records changed since the last run, lookalike seeds and suppression lists that track your live customer base stays current while enterprise data teams on IBM DB2 keep audience refresh cadence in view. Delivery needs no export and no manual upload.

    What match rate should a IBM DB2-sourced Meta Custom Audience batch expect?

    Coverage of hashed identifiers across your Db2 tables decides it, and enterprise data teams on IBM DB2 own that inside IBM DB2. A live email or phone matches into Meta; neither, and it will not. First-run feedback flags audience refresh cadence, which enterprise data teams on IBM DB2 then raise inside your Db2 tables.

    NEXT STEP

    IBM DB2 to Meta Custom Audience, in production this week.

    Talk to our team All IBM DB2 use cases