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    CONNECTIONS / PostgreSQL / PostgreSQL to LinkedIn Leads CAPI

    Your PostgreSQL tables, wired to LinkedIn lead-stage optimization.

    Signals reads your PostgreSQL tables through a read-only database user scoped to the PostgreSQL tables you name, then reports deal-stage progress so LinkedIn favors opportunities that advance so LinkedIn sees lead conversions without an export.

    Talk to our team Explore the setup

    postgresql -> linkedin-leads-capi :: live

    1. ● postgresql → linkedin.capi :: live
    2. > read lead_pipeline rows=31,557
    3. hash sha256(email,phone) consent=filtered
    4. route linkedin deliver
    5. ✓ delivered · 23,037 matched

    WHAT THIS ENABLES

    PostgreSQL to LinkedIn Leads CAPI

    LinkedIn Leads CAPI for PostgreSQL: Signals reports deal-stage progress so LinkedIn favors opportunities that advance straight from your PostgreSQL tables, hashed and consent-screened each time the read runs.

    • Signals reports deal-stage progress so LinkedIn favors opportunities that advance, reading your PostgreSQL tables each time the read runs.
    • Campaign focus on the deals that advance, with no export step out of your PostgreSQL tables.

    WHAT FLOWS WHERE

    PostgreSQL to Leads CAPI, mapped.

    Signals reads the qualified-lead and pipeline signals from your PostgreSQL tables each time the read runs, hashes and screens each record, and posts the lead conversions to LinkedIn's Leads Conversions API, keeping opportunity-stage weighting in view.

    Signals reads the qualified-lead and pipeline signals from your PostgreSQL tables each time the read runs, hashes and screens each record, and posts the lead conversions to LinkedIn's Leads Conversions API, keeping opportunity-stage weighting in view.

    WHO THIS IS FOR

    Built for the teams that own the number.

    B2B advertisers whose LinkedIn forms fill faster than they qualify, working out of PostgreSQL tables, views, and materialized views.

    Engineering teams running PostgreSQL who need LinkedIn focus on the deals that actually advance out of PostgreSQL tables.

    HOW DATAHASH SETS IT UP

    From kickoff to verified events.

    1. Connect

      A read-only database user scoped to the PostgreSQL tables you name, mapped to LinkedIn's Leads Conversions API and tuned for opportunity-stage weighting.

    2. Map

      Columns from your PostgreSQL tables align to LinkedIn's Leads Conversions API in the visual mapper, hashed as the read runs and checked for opportunity-stage weighting.

    3. Deliver

      Each time the read runs, Signals reads your PostgreSQL tables and reports deal-stage progress so LinkedIn favors opportunities that advance, reads only the records changed since the last run, with opportunity-stage weighting watched in the debugger.

    WHAT YOU GET

    What ships with this use case.

    LinkedIn focus on the deals that actually advance from your PostgreSQL tables, delivered each time the read runs.

    Campaign focus on the deals that advance out of your PostgreSQL tables, delivered each time the read runs without read load on the database climbing.

    Match feedback on opportunity-stage weighting from LinkedIn's Leads Conversions API each run, tied back to your PostgreSQL tables.

    ON THE WIRE

    What Leads CAPI actually receives.

    signals :: postgresql.linkedin-leads-capi :: wire

    1. ● signals :: event payload
    2. > POST /conversionEvents source=postgresql.lead_pipeline
    3. conversion "urn:lla:llaPartnerConversion:85004"
    4. conversionHappenedAt 1784013004000
    5. user.userIds [{ idType: "SHA256_EMAIL", idValue: "b19e04…" }]
    6. ✓ accepted · conversionValue 2913 USD
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    FAQ

    Asked on almost every call.

    How often does the PostgreSQL LinkedIn Leads CAPI sync run?

    Delivery tracks PostgreSQL, run by engineering teams running PostgreSQL: a near-real-time or scheduled sync of your PostgreSQL tables feeds LinkedIn on that cadence. Each run reads only the records changed since the last run, so campaign focus on the deals that advance holds up on opportunity-stage weighting. The live debugger confirms every delivery inline.

    What match rate should a PostgreSQL-sourced LinkedIn Leads CAPI batch expect?

    Coverage of hashed identifiers across your PostgreSQL tables decides it, and engineering teams running PostgreSQL own that inside PostgreSQL. A live email or phone matches into LinkedIn; neither, and it will not. First-run feedback flags opportunity-stage weighting, which engineering teams running PostgreSQL then raise inside your PostgreSQL tables.

    NEXT STEP

    PostgreSQL to LinkedIn Leads CAPI, in production this week.

    Talk to our team All PostgreSQL use cases