Services

Revenue Data Foundation

The data governance framework that makes everything else work — because every dashboard, AI tool, and automation is only as good as the data underneath it.

The Problem

Your CRM has 47,000 accounts but nobody knows which ones are real customers. Marketing reports different pipeline numbers than Sales. Your AI tools produce garbage recommendations because they’re trained on garbage data.

The problem isn’t your tools — it’s that nobody ever designed the data layer they all depend on. Without a Revenue Data Foundation, every system you build, every report you run, and every AI model you deploy is built on sand.

75% of RevOps professionals cite data inconsistencies as their biggest challenge. Fix the foundation, or nothing built on top of it will work.

Our Approach

  1. 1

    Audit your current data landscape — every system, every object, every field that touches revenue data.

  2. 2

    Design your Customer Master: the single authoritative record for every account, contact, and relationship across your entire stack.

  3. 3

    Build deduplication logic that handles the messy reality of B2B data — subsidiaries, acquisitions, name variations, and multi-entity relationships.

  4. 4

    Implement cross-system integrity rules so that changes in one system propagate correctly to every other system.

  5. 5

    Create the semantic layer — standardized definitions, calculated fields, and data models — so that “ARR” means the same thing in Salesforce, your data warehouse, and your board deck.

What You Get

Customer Master Design

Architecture for a golden record system that maintains a single authoritative version of every account, contact, and relationship across your GTM stack.

Data Governance Framework

Policies, ownership assignments, and processes for data entry, validation, enrichment, and lifecycle management.

Deduplication Strategy

Matching logic and merge rules designed for B2B complexity — handling subsidiaries, acquisitions, name variations, and multi-entity hierarchies.

Cross-System Integrity Audit

Analysis of how data flows between systems with rules to ensure changes propagate correctly and records stay in sync.

Data Quality Scorecard

Ongoing measurement framework for completeness, accuracy, consistency, and timeliness of your revenue data.

Who This Is For

  • Companies where Sales and Marketing report different pipeline numbers
  • Teams with CRM databases full of duplicates, outdated records, and inconsistent data
  • Organizations investing in AI or advanced analytics that need clean data to get value
  • Revenue leaders who want forecasting they can actually trust

Ready to get started?

Schedule a complimentary 30-minute assessment and we'll help you determine if revenue data foundation is the right fit for your team.

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