CONNECTIONS / IBM DB2 / IBM DB2 to Google EC for Leads
Db2 tables into Google Ads, built for Google Enhanced Conversions for Leads.
Connect IBM DB2 and point Signals at your Db2 tables; it sends down-funnel lead milestones matched to the originating Google click each time the read runs, hashed and consent-checked for Google Ads.
- ● ibm db2 → google.leads :: live
- > read lead_pipeline rows=66,157
- hash sha256(email,phone) consent=filtered
- route google deliver
- ✓ delivered · 48,956 matched
WHAT THIS ENABLES
IBM DB2 to Google EC for Leads
Google EC for Leads for IBM DB2: Signals sends down-funnel lead milestones matched to the originating Google click straight from your Db2 tables, hashed and consent-screened each time the read runs.
- Qualified-lead and pipeline signals from your Db2 tables activated for Google Ads, as Signals sends down-funnel lead milestones matched to the originating Google click.
- Lead-value bidding fed by the stages your pipeline actually reaches, drawn from your Db2 tables by enterprise data teams on IBM DB2.
WHAT FLOWS WHERE
IBM DB2 to EC for Leads, mapped.
Signals reads the qualified-lead and pipeline signals from your Db2 tables each time the read runs, hashes and screens each record, and posts the lead conversions to Google Ads' Enhanced Conversions API, keeping GCLID and hashed-email matching in view.
Signals reads the qualified-lead and pipeline signals from your Db2 tables each time the read runs, hashes and screens each record, and posts the lead conversions to Google Ads' Enhanced Conversions API, keeping GCLID and hashed-email matching in view.
Built for the teams that own the number.
Enterprise data teams on IBM DB2 activating Google Enhanced Conversions for Leads straight from Db2 tables.
From kickoff to verified events.
-
Connect
A read-only database user scoped to the Db2 tables you name to feed Google Ads' Enhanced Conversions API, sized for GCLID and hashed-email matching.
-
Map
A scheduled read pulls your Db2 tables, and its columns map to Google Ads' Enhanced Conversions API in the visual mapper, hashed and checked for GCLID and hashed-email matching.
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Deliver
On each run, Signals pulls your Db2 tables, sends down-funnel lead milestones matched to the originating Google click, and reads only the records changed since the last run, with GCLID and hashed-email matching in the debugger.
What ships with this use case.
Lead-value bidding fed by the stages your pipeline actually reaches on every run, as Signals reads your Db2 tables and reads only the records changed since the last run.
Lead-value signals matched to the paid click from your Db2 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 Google Ads' Enhanced Conversions API on GCLID and hashed-email matching, straight out of your Db2 tables.
What EC for Leads actually receives.
- ● signals :: event payload
- > POST /conversion_action source=ibm-db2.lead_pipeline
- gclid "Cj0KCQjw…" · conversion_action "sql_reached"
- conversion_value 6 · currency USD
- hashed_email sha256 "9c41af…"
- ✓ accepted match=gclid+hashed_email
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How often does the IBM DB2 Google EC for Leads sync run?
The pace follows your Db2 tables: Signals sends changes from IBM DB2 to Google Ads each time the read runs. Because it reads only the records changed since the last run, lead-value bidding fed by the stages your pipeline actually reaches stays current while enterprise data teams on IBM DB2 keep GCLID and hashed-email matching in view. Delivery needs no export and no manual upload.
What match rate should a IBM DB2-sourced Google EC for Leads batch expect?
Coverage of hashed identifiers across your Db2 tables decides it, and enterprise data teams on IBM DB2 own that inside IBM DB2. A live email or phone matches into Google Ads; neither, and it will not. First-run feedback flags GCLID and hashed-email matching, which enterprise data teams on IBM DB2 then raise inside your Db2 tables.
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