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    CONNECTIONS / Oracle / Oracle to Google Customer Match

    From Oracle tables to Google Customer Match.

    Signals reads your Oracle tables through a read-only database user scoped to the Oracle tables you name, then projects your segments into Google Ads as Customer Match lists so Google Ads sees match-ready audiences without an export.

    Talk to our team Explore the setup

    oracle -> google-customer-match :: live

    1. ● oracle → google.match :: live
    2. > read segments rows=28,687
    3. hash sha256(email,phone) consent=filtered
    4. route google deliver
    5. ✓ delivered · 23,810 matched

    WHAT THIS ENABLES

    Oracle to Google Customer Match

    Google Customer Match for Oracle: Signals projects your segments into Google Ads as Customer Match lists straight from your Oracle tables, hashed and consent-screened each time the read runs.

    • Signals projects your segments into Google Ads as Customer Match lists, reading your Oracle tables each time the read runs.
    • Lists that self-maintain across syncs, with no export step out of your Oracle tables.

    WHAT FLOWS WHERE

    Oracle to Customer Match, mapped.

    Signals reads the customer segments from your Oracle tables each time the read runs, hashes and screens each record, and posts the match-ready audiences to Google Ads' Customer Match API, keeping the serving-size threshold in view.

    Signals reads the customer segments from your Oracle tables each time the read runs, hashes and screens each record, and posts the match-ready audiences to Google Ads' Customer Match API, keeping the serving-size threshold in view.

    WHO THIS IS FOR

    Built for the teams that own the number.

    Growth teams feeding Google audiences from governed first-party data, working out of Oracle tables, views, and PL/SQL results.

    Enterprise data teams on Oracle who need Customer Match lists that add joiners and drop lapsed members each sync out of Oracle tables.

    HOW DATAHASH SETS IT UP

    From kickoff to verified events.

    1. Connect

      A read-only database user scoped to the Oracle tables you name, mapped to Google Ads' Customer Match API and tuned for the serving-size threshold.

    2. Map

      Columns from your Oracle tables align to Google Ads' Customer Match API in the visual mapper, hashed as the read runs and checked for the serving-size threshold.

    3. Deliver

      Each time the read runs, Signals reads your Oracle tables and projects your segments into Google Ads as Customer Match lists, reads only the records changed since the last run, with the serving-size threshold watched in the debugger.

    WHAT YOU GET

    What ships with this use case.

    Customer Match lists that add joiners and drop lapsed members each sync from your Oracle tables, delivered each time the read runs.

    Lists that self-maintain across syncs out of your Oracle tables, delivered each time the read runs without read load on the database climbing.

    Match feedback on the serving-size threshold from Google Ads' Customer Match API each run, tied back to your Oracle tables.

    ON THE WIRE

    What Customer Match actually receives.

    signals :: oracle.google-customer-match :: wire

    1. ● signals :: audience upload
    2. > POST /user_list_operations source=oracle.segments
    3. operation ADD · user_list "segment_82330"
    4. hashed_email sha256 "b02cf1…" · hashed_phone sha256 "3ad990…"
    5. members_uploaded 28,687 · members_matched 23,810
    6. ✓ accepted match=83%
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    FAQ

    Asked on almost every call.

    How often does the Oracle Google Customer Match sync run?

    You set the cadence, from near-real-time to a nightly Oracle sync of your Oracle tables into Google Ads. Since Signals reads only the records changed since the last run, Customer Match lists that add joiners and drop lapsed members each sync keeps pace and enterprise data teams on Oracle watch the serving-size threshold. One scoped connection sets it up, cadence adjustable later.

    What match rate should a Oracle-sourced Google Customer Match batch expect?

    Match rate follows identifier coverage in your Oracle tables, which enterprise data teams on Oracle control, not Oracle itself. A record with a current hashed email or phone matches for Google Ads; one missing both cannot. First-run feedback from Customer Match API pinpoints the serving-size threshold, the number enterprise data teams on Oracle tune against.

    NEXT STEP

    Oracle to Google Customer Match, in production this week.

    Talk to our team All Oracle use cases