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    CONNECTIONS / Oracle / Oracle to Google Store Sales

    From Oracle tables to Google Store Sales matching.

    Signals reads your Oracle tables through a read-only database user scoped to the Oracle tables you name, then matches in-person transactions to Google accounts as store-sales conversions so Google Ads sees offline conversions without an export.

    Talk to our team Explore the setup

    oracle -> google-store-sales :: live

    1. ● oracle → google.sales :: live
    2. > read closed_deals rows=27,812
    3. hash sha256(email,phone) consent=filtered
    4. route google deliver
    5. ✓ delivered · 22,250 matched

    WHAT THIS ENABLES

    Oracle to Google Store Sales

    Google Store Sales for Oracle: Signals matches in-person transactions to Google accounts as store-sales conversions straight from your Oracle tables, hashed and consent-screened each time the read runs.

    • Signals matches in-person transactions to Google accounts as store-sales conversions, reading your Oracle tables each time the read runs.
    • Store visits reconciled to campaign spend, with no export step out of your Oracle tables.
    WHAT FLOWS WHERE

    The click, the conversion, and the credit.

    The conversion happens off Google, away from any pixel. Here is how Oracle closes the loop.

    Google credits the campaign that sourced the conversion conversion happens off-platform Ad click on Google Scheduled read sync recorded in Oracle S Signals hash · dedupe Store Sales Direct API delivered · credited
    WHO THIS IS FOR

    Built for the teams that own the number.

    Omnichannel retailers reconciling point-of-sale against Google spend, working out of Oracle tables, views, and PL/SQL results.

    Enterprise data teams on Oracle who need counter and showroom revenue inside the same ROAS view as online orders 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' Store Sales Direct API and tuned for the store-sales match rate.

    2. Map

      Columns from your Oracle tables align to Google Ads' Store Sales Direct API in the visual mapper, hashed as the read runs and checked for the store-sales match rate.

    3. Deliver

      Each time the read runs, Signals reads your Oracle tables and matches in-person transactions to Google accounts as store-sales conversions, reads only the records changed since the last run, with the store-sales match rate watched in the debugger.

    WHAT YOU GET

    What changes when the CSV goes away.

    Capability Manual CSV upload Datahash
    Reporting Offline sales sit in a separate export, reconciled by hand. Revenue counted in the same Store Sales reporting as web conversions.
    Deduplication A re-uploaded file risks counting the same conversion twice. Deduped delivery, so a resent record never counts as a second conversion.
    Match visibility Match quality is a guess until the numbers look off. Match rate reported per upload, tied to the source event set that produced it.
    Effort and latency An analyst exports and uploads on a manual cadence. Server-side and automatic the moment Oracle records the event.
    ON THE WIRE

    What Store Sales actually receives.

    signals :: oracle.google-store-sales :: wire

    1. ● signals :: store sales upload
    2. > POST /offline_user_data_jobs source=oracle.closed_deals
    3. transaction_time 2026-07-21T05:19:30 · transaction_amount_micros 37896000000
    4. currency_code GBP
    5. hashed_email sha256 "6d2e91…" · hashed_last_name sha256 "cc410a…"
    6. ✓ accepted match=80%
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    FAQ

    Asked on almost every call.

    How often does the Oracle Google Store Sales 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, counter and showroom revenue inside the same ROAS view as online orders keeps pace and enterprise data teams on Oracle watch the store-sales match rate. One scoped connection sets it up, cadence adjustable later.

    What match rate should a Oracle-sourced Google Store Sales 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 Store Sales Direct API pinpoints the store-sales match rate, the number enterprise data teams on Oracle tune against.

    NEXT STEP

    Oracle to Google Store Sales, in production this week.

    Talk to our team All Oracle use cases