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    CONNECTIONS / Databricks / Databricks to Snap Leads CAPI

    Your Databricks lakehouse, wired to Snapchat qualified-lead reporting.

    Signals reads the Delta table through a Unity Catalog grant and sends qualified-lead events so Snapchat bids toward leads that convert offline, hashed on the way out and governed like any other lakehouse job.

    Talk to our team Explore the setup

    databricks -> snap-lead-gen-capi :: live

    1. ● databricks → snap.capi :: live
    2. > read main.crm.pipeline_stages rows=39,297
    3. hash sha256(email,phone) consent=filtered
    4. route snap deliver
    5. ✓ delivered · 31,045 matched

    WHAT THIS ENABLES

    Databricks to Snapchat Leads CAPI

    Databricks to Snapchat Leads CAPI: A notebook job reads the qualified-lead and pipeline signals in your Databricks Delta tables, and Signals sends qualified-lead events so Snapchat bids toward leads that convert offline, hashed and consent-checked each time the model rebuilds.

    • Signals sends qualified-lead events so Snapchat bids toward leads that convert offline, reading your Databricks Delta tables each time the model rebuilds.
    • Snapchat optimizing on qualified leads instead of raw submissions, fed by data engineers modeling in Databricks notebooks.

    WHAT FLOWS WHERE

    Databricks to Lead Gen CAPI, mapped.

    The notebook job streams qualified-lead and pipeline signals into Signals for hashing and consent screening, then Snapchat's Leads Conversions API records the lead conversions with qualified-lead signals accounted for.

    The notebook job streams qualified-lead and pipeline signals into Signals for hashing and consent screening, then Snapchat's Leads Conversions API records the lead conversions with qualified-lead signals accounted for.

    WHO THIS IS FOR

    Built for the teams that own the number.

    Snapchat lead-gen advertisers qualifying leads after the form, with the numbers already modeled in Databricks Delta tables governed by Unity Catalog.

    Data engineers modeling in Databricks notebooks who need Snapchat optimizing on qualified leads instead of raw submissions.

    HOW DATAHASH SETS IT UP

    From kickoff to verified events.

    1. Connect

      A Unity Catalog-scoped service principal on the single Delta table in play to feed Snapchat's Leads Conversions API, sized for qualified-lead signals.

    2. Map

      A notebook job reads your Databricks Delta tables, and its columns map to Snapchat's Leads Conversions API in the visual mapper, hashed and checked for qualified-lead signals.

    3. Deliver

      Each time the model rebuilds, Signals sends qualified-lead events so Snapchat bids toward leads that convert offline, reads only the rows the model rebuilt, with qualified-lead signals watched in the debugger.

    WHAT YOU GET

    What ships with this use case.

    Snapchat optimizing on qualified leads instead of raw submissions on every run, since Signals reads only the rows the model rebuilt.

    Spend steered toward leads that qualify, delivered each time the model rebuilds without job-cluster time climbing.

    Each run returns a match report on qualified-lead signals from Snapchat's Leads Conversions API, read from your Databricks Delta tables each time the model rebuilds, at flat job-cluster time.

    ON THE WIRE

    What Lead Gen CAPI actually receives.

    signals :: databricks.snap-lead-gen-capi :: wire

    1. ● signals :: event payload
    2. > POST /v2/conversion source=databricks.main.crm.pipeline_stages
    3. event_type "QUALIFIED_LEAD" · event_conversion_type "OFFLINE"
    4. hashed_email "4ac910…" · hashed_phone_number "7e30bc…"
    5. timestamp 1784403322
    6. ✓ accepted · match=true
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    FAQ

    Asked on almost every call.

    How often does the Databricks Snap Leads CAPI sync run?

    Cadence follows the job that rebuilds the table: a nightly model gives Snapchat a nightly feed, an hourly one an hourly feed. Because a run picks up only the rows the model rebuilt, Snapchat optimizing on qualified leads instead of raw submissions keeps pace on qualified-lead signals and job-cluster time stays modest.

    What match rate should a Databricks-sourced Snap Leads CAPI batch expect?

    Identifier quality in the Delta table drives it, not the cluster size. Rows carrying a live hashed email or phone land; rows with neither will not, and no rebuild changes that. The opening run's feedback from Snapchat's Leads Conversions API flags the gap for Snapchat lead-gen advertisers qualifying leads after the form tracking qualified-lead signals.

    NEXT STEP

    Databricks to Snap Leads CAPI, in production this week.

    Talk to our team All Databricks use cases