GTM data and decisions
GTM data your analysts and AI agents can both rely on
For B2B companies, prepblend audits and rebuilds the go-to-market data and decision layer, then uses it to set ICP, judge pipeline health and build the forecast.
Two layers, one practice
Data layer
Foundat10n
A spec of ten pass or fail requirements for the GTM warehouse. The audit scores your stack and gives you the fix list in order.
Decision layer
Cohorticulture
Cohort methods for the sales calls you make every quarter: ICP, pipeline health and forecasting, on the history Foundat10n keeps.
How an engagement runs
Audit
Score your CRM, billing and warehouse against the ten requirements. You get the scorecard and a ranked fix list.
Build
Daily snapshot history, a medallion warehouse and one set of revenue definitions, in your own Snowflake or Databricks account.
Hand off
Your team owns the dbt project, the pipelines and the docs.
Ten requirements, each pass or fail
Four of the ten, scored with sample data. The audit scores all ten against your stack.
- All GTM stack data lands in the warehousePass
- Raw layers persist every source columnPass
- The warehouse is the single source of truthFail
- Every non-audit table gets SCD2, plus a "newest" viewFail
Selected work
Cracks in the foundation inevitably result in unnecessary re-work and missed opportunities.
No pipeline history
Problem
Opportunities only carried their latest values, so there was no record of how pipeline changed.
Fix
Added SCD2 snapshots with a current-state view and trailing-window models for period-over-period comparisons.
Metrics with trust issues
Problem
Internal AI agents read an incorrect field as ARR with a mangled currency conversion and presented it as gospel.
Fix
Rebuilt the metric from source as one certified definition, so agents stopped driftmaxxing.
Unversioned territories
Problem
Accounts were reassigned by hand with no record of the change.
Fix
Versioned territory assignments to streamline as-is, as-was, and as-will-be reporting.
Start with the audit
A fixed-scope audit scores your stack against the ten requirements and gives you a ranked fix list. The first step is a call.