CONNECTIONS / Snowflake / Snowflake to LinkedIn Leads CAPI
Snowflake's deal-stage table, past the LinkedIn form fill.
A form fill on LinkedIn means little until your warehouse shows the deal moving forward. Signals reads the stage table your data team already maintains and streams the changes to LinkedIn's Leads Conversions API, hashed throughout.
- ● snowflake → linkedin.leads_capi :: live
- > sync table DEAL_STAGE_TABLE rows=6,280
- hash sha256(business_email)
- route linkedin.leads_capi conversion=stage_mapped
- ✓ delivered · stage recorded
WHAT THIS ENABLES
Snowflake to LinkedIn Leads Conversions API
Snowflake to LinkedIn Leads Conversions API reads a warehouse table tracking deal-stage history and posts the changes to LinkedIn server-side, so B2B campaigns optimize toward qualified pipeline and closed-won revenue rather than raw form-fill volume.
- Deal-stage history in Snowflake reported to LinkedIn as distinct conversion events.
- Deal value carried alongside the stage change, so LinkedIn's bidding can weight toward the pipeline that actually matters.
- B2B optimization that reflects the same stage table your revenue reporting already trusts.
WHAT FLOWS WHERE
Snowflake to Leads CAPI, mapped.
A scheduled Snowflake read picks up stage changes from the deal table, Signals hashes the business email on each row, and posts the result to LinkedIn's Leads Conversions API as a stage-mapped conversion.
A scheduled Snowflake read picks up stage changes from the deal table, Signals hashes the business email on each row, and posts the result to LinkedIn's Leads Conversions API as a stage-mapped conversion.
Built for the teams that own the number.
Teams whose stage table already feeds Meta, Google, or TikTok and want LinkedIn added without a second integration.
From kickoff to verified events.
-
Connect
A read-only Snowflake role scoped to the table carrying deal stage and business email columns.
-
Map
Whatever stage labels the table already carries, most often a qualified flag and a closed-won marker, matched to LinkedIn's conversion definitions once during setup.
-
Deliver
Server-side stage delivery on a scheduled read, diagnosable per event.
What ships with this use case.
LinkedIn bidding informed by the same stage table your revenue team already reports from.
A closed deal's revenue traced back through LinkedIn reporting to the stage change that first flagged it.
A stage feed that runs on the schedule your warehouse task already keeps.
What Leads CAPI actually receives.
- ● signals :: event payload
- > POST /conversionEvents source=snowflake.DEAL_STAGE_TABLE
- conversion "urn:lla:llaPartnerConversion:588327"
- conversionHappenedAt 1784391600000
- user.userIds [{ idType: "SHA256_EMAIL", idValue: "9c41af…" }]
- ✓ accepted · conversionValue 46500 USD
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Which columns in our Snowflake stage table should feed LinkedIn Leads Conversions API?
Most teams map the stages that predict revenue, commonly a qualified flag, an opportunity flag, and a closed-won date, each becoming its own conversion event. The initial mapping happens during onboarding against your actual schema, and it can be revised later without a new integration project.
How fast do changes in the Snowflake table reach LinkedIn Leads Conversions API?
Stage changes stream to LinkedIn in near real time once the scheduled read picks them up, and most teams run that read on a schedule tight enough to keep the delay small. Slower warehouse tasks still work, since LinkedIn accepts conversions within its own attribution lookback window.
Does LinkedIn Leads Conversions API need a formal table, or can it read a view?
Either. Signals reads whatever object your team already uses to surface deal-stage history, a base table or a view built on top of a dbt model, so there is no requirement to build a new object just to support this sync.
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