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    CONNECTIONS / MariaDB / MariaDB to LinkedIn Offline CAPI

    MariaDB tables into LinkedIn, built for LinkedIn account-revenue reporting.

    Signals reads your MariaDB tables through a read-only database user scoped to the MariaDB 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

    mariadb -> linkedin-offline-capi :: live

    1. ● mariadb → linkedin.capi :: live
    2. > read closed_deals rows=45,735
    3. hash sha256(email,phone) consent=filtered
    4. route linkedin deliver
    5. ✓ delivered · 35,673 matched

    WHAT THIS ENABLES

    MariaDB to LinkedIn Offline CAPI

    LinkedIn Offline CAPI for MariaDB: Signals reports closed B2B deals so LinkedIn optimizes on account revenue straight from your MariaDB tables, hashed and consent-screened each time the read runs.

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

    The click, the conversion, and the credit.

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

    LinkedIn credits the campaign that sourced the conversion conversion happens off-platform Ad click on LinkedIn Scheduled read sync recorded in MariaDB 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 MariaDB tables and views.

    Engineering teams running MariaDB who need pipeline revenue tied to the LinkedIn campaigns that sourced it out of MariaDB tables.

    HOW DATAHASH SETS IT UP

    From kickoff to verified events.

    1. Connect

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

    2. Map

      Columns from your MariaDB 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 MariaDB 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 MariaDB records the event.
    ON THE WIRE

    What Offline CAPI actually receives.

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

    1. ● signals :: event payload
    2. > POST /conversionEvents source=mariadb.closed_deals
    3. conversion "urn:lla:llaPartnerConversion:70960"
    4. conversionHappenedAt 1784713960000
    5. user.userIds [{ idType: "SHA256_EMAIL", idValue: "9c41af…" }]
    6. ✓ accepted · conversionValue 40033 USD
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    FAQ

    Asked on almost every call.

    How often does the MariaDB LinkedIn Offline CAPI sync run?

    You set the cadence, from near-real-time to a nightly MariaDB sync of your MariaDB tables into LinkedIn. Since Signals reads only the records changed since the last run, pipeline revenue tied to the LinkedIn campaigns that sourced it keeps pace and engineering teams running MariaDB watch long B2B attribution windows. One scoped connection sets it up, cadence adjustable later.

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

    Match rate follows identifier coverage in your MariaDB tables, which engineering teams running MariaDB control, not MariaDB itself. A record with a current hashed email or phone matches for LinkedIn; one missing both cannot. First-run feedback from Conversions API pinpoints long B2B attribution windows, the number engineering teams running MariaDB tune against.

    NEXT STEP

    MariaDB to LinkedIn Offline CAPI, in production this week.

    Talk to our team All MariaDB use cases