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    CONNECTIONS / BigQuery / BigQuery to Google EC for Leads

    From BigQuery datasets to Google Enhanced Conversions for Leads.

    Point Signals at the dataset behind a read-only service account, and it sends down-funnel lead milestones matched to the originating Google click on the cadence your scheduled query already keeps.

    Talk to our team Explore the setup

    bigquery -> google-ec-leads :: live

    1. ● bigquery → google.leads :: live
    2. > read crm.lead_stage_history rows=57,819
    3. hash sha256(email,phone) consent=filtered
    4. route google deliver
    5. ✓ delivered · 49,146 matched

    WHAT THIS ENABLES

    BigQuery to Google EC for Leads

    BigQuery to Google EC for Leads: A scheduled query reads the qualified-lead and pipeline signals in your BigQuery tables, and Signals sends down-funnel lead milestones matched to the originating Google click, hashed and consent-checked whenever the scheduled query reruns.

    • Signals sends down-funnel lead milestones matched to the originating Google click, reading your BigQuery tables whenever the scheduled query reruns.
    • Lead-value bidding fed by the stages your pipeline actually reaches, fed by analytics engineers running BigQuery scheduled queries.

    WHAT FLOWS WHERE

    BigQuery to EC for Leads, mapped.

    A scheduled query hands the qualified-lead and pipeline signals to Signals, which hashes and consent-filters each row before Google Ads' Enhanced Conversions API logs the lead conversions for GCLID and hashed-email matching.

    A scheduled query hands the qualified-lead and pipeline signals to Signals, which hashes and consent-filters each row before Google Ads' Enhanced Conversions API logs the lead conversions for GCLID and hashed-email matching.

    WHO THIS IS FOR

    Built for the teams that own the number.

    Google lead-gen advertisers bidding past the first form submit, with the numbers already modeled in BigQuery tables and GA4 exports.

    Analytics engineers running BigQuery scheduled queries who need lead-value bidding fed by the stages your pipeline actually reaches.

    HOW DATAHASH SETS IT UP

    From kickoff to verified events.

    1. Connect

      A read-only service account with dataViewer on the one dataset you nominate to feed Google Ads' Enhanced Conversions API, sized for GCLID and hashed-email matching.

    2. Map

      A scheduled query reads your BigQuery tables, and its columns map to Google Ads' Enhanced Conversions API in the visual mapper, hashed and checked for GCLID and hashed-email matching.

    3. Deliver

      Whenever the scheduled query reruns, Signals sends down-funnel lead milestones matched to the originating Google click, scans only the rows the query changed, with GCLID and hashed-email matching watched in the debugger.

    WHAT YOU GET

    What ships with this use case.

    Lead-value bidding fed by the stages your pipeline actually reaches on every run, since Signals scans only the rows the query changed.

    Lead-value signals matched to the paid click, delivered whenever the scheduled query reruns without BigQuery slot cost climbing.

    Each run returns a match report on GCLID and hashed-email matching from Google Ads' Enhanced Conversions API, read from your BigQuery tables whenever the scheduled query reruns, at flat BigQuery slot cost.

    ON THE WIRE

    What EC for Leads actually receives.

    signals :: bigquery.google-ec-leads :: wire

    1. ● signals :: event payload
    2. > POST /conversion_action source=bigquery.crm.lead_stage_history
    3. gclid "Cj0KCQjw…" · conversion_action "sql_reached"
    4. conversion_value 3 · currency GBP
    5. hashed_email sha256 "9c41af…"
    6. ✓ accepted match=gclid+hashed_email
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    FAQ

    Asked on almost every call.

    How often does the BigQuery Google EC for Leads sync run?

    The scheduled query sets the pace: rebuild the qualified-lead and pipeline signals nightly and delivery to Google Ads is nightly, or refresh hourly for an hourly feed. Each run only reads the rows the query changed, so lead-value bidding fed by the stages your pipeline actually reaches stays current for GCLID and hashed-email matching while BigQuery slot cost barely moves.

    What match rate should a BigQuery-sourced Google EC for Leads batch expect?

    Coverage in your BigQuery tables decides the rate, not BigQuery. A row with a current hashed email or phone matches; one missing both cannot, however the query is tuned. The first run's report from Google Ads' Enhanced Conversions API sets a baseline, the number Google lead-gen advertisers bidding past the first form submit weigh against GCLID and hashed-email matching.

    NEXT STEP

    BigQuery to Google EC for Leads, in production this week.

    Talk to our team All BigQuery use cases