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    CONNECTIONS / Redshift / Redshift to Meta Custom Audience

    Customer segments in Redshift, activated for Meta lookalike and suppression seeds.

    Grant a scoped IAM role, name the table or materialized view, and Signals keeps Meta audiences synced as adds and removals so lists never drift with no UNLOAD to S3 and no file to hand off.

    Talk to our team Explore the setup

    redshift -> meta-custom-audience :: live

    1. ● redshift → meta.audience :: live
    2. > read marketing.high_value_customers rows=46,740
    3. hash sha256(email,phone) consent=filtered
    4. route meta deliver
    5. ✓ delivered · 38,327 matched

    WHAT THIS ENABLES

    Redshift to Meta Custom Audience

    Redshift to Meta Custom Audience: The Redshift Data API reads the customer segments in your Redshift tables, and Signals keeps Meta audiences synced as adds and removals so lists never drift, hashed and consent-checked as the materialized view refreshes.

    • Signals keeps Meta audiences synced as adds and removals so lists never drift, reading your Redshift tables as the materialized view refreshes.
    • Lookalike seeds and suppression lists that track your live customer base, fed by analytics teams maintaining Redshift tables and materialized views.

    WHAT FLOWS WHERE

    Redshift to Custom Audience, mapped.

    Signals pulls customer segments through the Redshift Data API, hashes and filters every row, and posts the match-ready audiences to Meta's Custom Audiences API, keeping audience refresh cadence in view.

    Signals pulls customer segments through the Redshift Data API, hashes and filters every row, and posts the match-ready audiences to Meta's Custom Audiences API, keeping audience refresh cadence in view.

    WHO THIS IS FOR

    Built for the teams that own the number.

    Performance teams running first-party suppression and lookalike seeds, with the numbers already modeled in Redshift tables and materialized views.

    Analytics teams maintaining Redshift tables and materialized views who need lookalike seeds and suppression lists that track your live customer base.

    HOW DATAHASH SETS IT UP

    From kickoff to verified events.

    1. Connect

      A scoped IAM role with SELECT on the schema you name to feed Meta's Custom Audiences API, sized for audience refresh cadence.

    2. Map

      The Redshift Data API reads your Redshift tables, and its columns map to Meta's Custom Audiences API in the visual mapper, hashed and checked for audience refresh cadence.

    3. Deliver

      As the materialized view refreshes, Signals keeps Meta audiences synced as adds and removals so lists never drift, touches only the rows changed since the last read, with audience refresh cadence watched in the debugger.

    WHAT YOU GET

    What ships with this use case.

    Lookalike seeds and suppression lists that track your live customer base on every run, since Signals touches only the rows changed since the last read.

    Always-current lookalike seeds and exclusions, delivered as the materialized view refreshes without RA3 load climbing.

    Each run returns a match report on audience refresh cadence from Meta's Custom Audiences API, read from your Redshift tables as the materialized view refreshes, at flat RA3 load.

    ON THE WIRE

    What Custom Audience actually receives.

    signals :: redshift.meta-custom-audience :: wire

    1. ● signals :: audience upload
    2. > POST /customaudiences source=redshift.marketing.high_value_customers
    3. schema ["EMAIL_SHA256","PHONE_SHA256"]
    4. num_received 46,740 · num_invalid_entries -143
    5. audience_id "1663913" · session "upsert"
    6. ✓ accepted match=82%
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    FAQ

    Asked on almost every call.

    How often does the Redshift Meta Custom Audience sync run?

    The refresh schedule drives it: when the materialized view rebuilds nightly, Meta gets a nightly feed, and an hourly refresh runs hourly. Each read touches only changed rows, so lookalike seeds and suppression lists that track your live customer base stays fresh for audience refresh cadence without RA3 load rising.

    What match rate should a Redshift-sourced Meta Custom Audience batch expect?

    The fill rate of the view matters more than Redshift itself. A clean hashed email or phone matches; a blank one never will. The first scheduled read reports quality from Meta's Custom Audiences API, the figure performance teams running first-party suppression and lookalike seeds weigh against audience refresh cadence.

    NEXT STEP

    Redshift to Meta Custom Audience, in production this week.

    Talk to our team All Redshift use cases