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    CONNECTIONS / Microsoft SQL Server / SQL Server to Snap Custom Audience

    Your SQL Server tables, wired to Snapchat audience matching.

    Connect SQL Server and point Signals at your SQL Server tables; it matches your segments into Snapchat for targeting and customer suppression each time the read runs, hashed and consent-checked for Snapchat.

    Talk to our team Explore the setup

    microsoft-sql-server -> snap-custom-audience :: live

    1. ● sql server → snap.audience :: live
    2. > read segments rows=11,208
    3. hash sha256(email,phone) consent=filtered
    4. route snap deliver
    5. ✓ delivered · 9,527 matched

    WHAT THIS ENABLES

    SQL Server to Snapchat Custom Audience

    SQL Server to Snapchat Custom Audience: Signals reads your SQL Server tables and matches your segments into Snapchat for targeting and customer suppression, hashed and consent-checked each time the read runs.

    • Customer segments from your SQL Server tables activated for Snapchat, as Signals matches your segments into Snapchat for targeting and customer suppression.
    • Snapchat audiences that stay in step as the segment rebuilds, drawn from your SQL Server tables by data teams running SQL Server.

    WHAT FLOWS WHERE

    Microsoft SQL Server to Custom Audience, mapped.

    Signals reads the customer segments from your SQL Server tables each time the read runs, hashes and screens each record, and posts the match-ready audiences to Snapchat's Custom Audiences API, keeping list sizing on Snapchat in view.

    Signals reads the customer segments from your SQL Server tables each time the read runs, hashes and screens each record, and posts the match-ready audiences to Snapchat's Custom Audiences API, keeping list sizing on Snapchat in view.

    WHO THIS IS FOR

    Built for the teams that own the number.

    Snapchat advertisers building lookalikes and excluding current buyers, with the records already in SQL Server tables, views, and indexed views.

    Data teams running SQL Server activating Snapchat audience matching straight from SQL Server tables.

    HOW DATAHASH SETS IT UP

    From kickoff to verified events.

    1. Connect

      A read-only database user scoped to the SQL Server tables you name to feed Snapchat's Custom Audiences API, sized for list sizing on Snapchat.

    2. Map

      A scheduled read pulls your SQL Server tables, and its columns map to Snapchat's Custom Audiences API in the visual mapper, hashed and checked for list sizing on Snapchat.

    3. Deliver

      On each run, Signals pulls your SQL Server tables, matches your segments into Snapchat for targeting and customer suppression, and reads only the records changed since the last run, with list sizing on Snapchat in the debugger.

    WHAT YOU GET

    What ships with this use case.

    Snapchat audiences that stay in step as the segment rebuilds on every run, as Signals reads your SQL Server tables and reads only the records changed since the last run.

    Audiences that rebuild as the segment does from your SQL Server tables, with read load on the database steady because Signals reads only the records changed since the last run.

    A per-run match report from Snapchat's Custom Audiences API on list sizing on Snapchat, straight out of your SQL Server tables.

    ON THE WIRE

    What Custom Audience actually receives.

    signals :: microsoft-sql-server.snap-custom-audience :: wire

    1. ● signals :: audience upload
    2. > POST /audience_match source=microsoft-sql-server.segments
    3. schema ["EMAIL_SHA256","PHONE_SHA256"]
    4. external_audience_id "aud_58846"
    5. id_list_size 11,208 · matched 9,527
    6. ✓ accepted match=85%
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    FAQ

    Asked on almost every call.

    How often does the SQL Server Snap Custom Audience sync run?

    Delivery tracks SQL Server, run by data teams running SQL Server: a near-real-time or scheduled sync of your SQL Server tables feeds Snapchat on that cadence. Each run reads only the records changed since the last run, so audiences that rebuild as the segment does holds up on list sizing on Snapchat. The live debugger confirms every delivery inline.

    What match rate should a SQL Server-sourced Snap Custom Audience batch expect?

    Match rate follows identifier coverage in your SQL Server tables, which data teams running SQL Server control, not SQL Server itself. A record with a current hashed email or phone matches for Snapchat; one missing both cannot. First-run feedback from Custom Audiences API pinpoints list sizing on Snapchat, the number data teams running SQL Server tune against.

    NEXT STEP

    SQL Server to Snap Custom Audience, in production this week.

    Talk to our team All Microsoft SQL Server use cases