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    CONNECTIONS / MySQL / MySQL to LinkedIn Offline CAPI

    From MySQL tables to LinkedIn account-revenue reporting.

    Signals reads your MySQL tables through a read-only database user scoped to the MySQL tables you name, then reports closed B2B deals so LinkedIn optimizes on account revenue so LinkedIn sees offline conversions without an export.

    Talk to our team Explore the setup

    mysql -> linkedin-offline-capi :: live

    1. ● mysql → linkedin.capi :: live
    2. > read closed_deals rows=35,607
    3. hash sha256(email,phone) consent=filtered
    4. route linkedin deliver
    5. ✓ delivered · 29,910 matched

    WHAT THIS ENABLES

    MySQL to LinkedIn Offline CAPI

    MySQL to LinkedIn Offline CAPI: Signals reads your MySQL tables and reports closed B2B deals so LinkedIn optimizes on account revenue, hashed and consent-checked each time the read runs.

    • Signals reports closed B2B deals so LinkedIn optimizes on account revenue, reading your MySQL tables each time the read runs.
    • Account revenue attached to the sourcing campaign, with no export step out of your MySQL tables.
    WHAT FLOWS WHERE

    The click, the conversion, and the credit.

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

    LinkedIn credits the campaign that sourced the conversion conversion happens off-platform Ad click on LinkedIn Scheduled read sync recorded in MySQL S Signals hash · dedupe Conversions API delivered · credited
    WHO THIS IS FOR

    Built for the teams that own the number.

    B2B teams whose deals close long after the impression, working out of MySQL tables and views.

    Application teams on MySQL who need pipeline revenue tied to the LinkedIn campaigns that sourced it out of MySQL tables.

    HOW DATAHASH SETS IT UP

    From kickoff to verified events.

    1. Connect

      A read-only database user scoped to the MySQL tables you name, mapped to LinkedIn's Conversions API and tuned for long B2B attribution windows.

    2. Map

      Columns from your MySQL tables align to LinkedIn's Conversions API in the visual mapper, hashed as the read runs and checked for long B2B attribution windows.

    3. Deliver

      Each time the read runs, Signals reads your MySQL tables and reports closed B2B deals so LinkedIn optimizes on account revenue, reads only the records changed since the last run, with long B2B attribution windows 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 Offline CAPI 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 MySQL records the event.
    ON THE WIRE

    What Offline CAPI actually receives.

    signals :: mysql.linkedin-offline-capi :: wire

    1. ● signals :: event payload
    2. > POST /conversionEvents source=mysql.closed_deals
    3. conversion "urn:lla:llaPartnerConversion:79222"
    4. conversionHappenedAt 1784224222000
    5. user.userIds [{ idType: "SHA256_EMAIL", idValue: "9c41af…" }]
    6. ✓ accepted · conversionValue 21327 USD
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    FAQ

    Asked on almost every call.

    How often does the MySQL LinkedIn Offline CAPI sync run?

    Delivery tracks MySQL, run by application teams on MySQL: a near-real-time or scheduled sync of your MySQL tables feeds LinkedIn on that cadence. Each run reads only the records changed since the last run, so account revenue attached to the sourcing campaign holds up on long B2B attribution windows. The live debugger confirms every delivery inline.

    What match rate should a MySQL-sourced LinkedIn Offline CAPI batch expect?

    Coverage of hashed identifiers across your MySQL tables decides it, and application teams on MySQL own that inside MySQL. A live email or phone matches into LinkedIn; neither, and it will not. First-run feedback flags long B2B attribution windows, which application teams on MySQL then raise inside your MySQL tables.

    NEXT STEP

    MySQL to LinkedIn Offline CAPI, in production this week.

    Talk to our team All MySQL use cases