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Marketing Single Source of Truth

End the data chaos and build a foundation everyone can trust

When every system tells a different story, no one trusts the numbers anymore. This is not a dashboard problem—it's a data trust and definition problem. We help you build a unified data foundation that powers reliable dashboards, meaningful attribution, and safe AI usage.

01 — The Problem

Marketing Data Silos & Disunity

Your data is everywhere, but the truth is nowhere. The symptoms are painfully familiar:

  • Conflicting metrics across GA, CRM, ad platforms, and internal reports
  • Heavy reliance on spreadsheets and manual reconciliation
  • Ongoing debates about 'which number is right'
  • Leadership losing confidence in dashboards and forecasts
02 — Our Approach

How Darwin Solves It

We perform comprehensive infrastructure work that eliminates marketing bloat and chaos, creating what we call the Marketing Single Source of Truth.

01

Deep Dive

Understand what systems exist and what each should be trusted for

02

Normalize

Document and standardize data definitions across all platforms

03

Create Foundation

Build a single, queryable foundation for reporting, analytics, and AI

04

Enable Trust

Establish reliable dashboards, meaningful attribution, and safe AI usage on top of trusted data

The Outcome

A unified data foundation that everyone trusts—from daily operational decisions to strategic planning and AI initiatives.

03 — Who It's For

Marketing operations leaders, data teams, and CMOs who are tired of conflicting metrics and want to establish a reliable data foundation that supports confident decision-making and enables safe AI adoption.

04 — Value

What You Get

Marketing Operations

  • Single source of truth across all marketing platforms
  • Automated data synchronization eliminating manual reconciliation
  • Clear data definitions that end metric debates
  • Foundation ready for AI and advanced analytics

Leadership

  • Reliable dashboards you can trust for decision-making
  • Meaningful attribution that shows true marketing impact
  • Faster, more confident operational and strategic decisions
  • Safe foundation for AI initiatives
05 — Results

Case Studies

Audi

Organization-Wide Data Foundation

The Challenge

Audi operated across multiple factories, logistics systems, and reporting layers, each producing large volumes of data. While data availability wasn't the issue, trust and usability were.

The Solution

  • Defining which data sources could be trusted for which decisions
  • Creating consistent, up-to-date reporting for employees and leadership
  • Designing the logic behind dealer incentive programs and performance tracking
  • Supporting both real-time and historical data analysis across operations

The Outcome

  • Daily operational and financial reports delivered automatically
  • Reliable, up-to-date data available across factories, logistics, and dealer networks
  • Clear performance and incentive tracking for dealers
  • Faster, more confident decision-making across teams
Potomac Floral

Optimized Operations & Decision-Making

The Challenge

As Potomac Floral scaled, its internal reporting became slow, fragmented, and increasingly difficult to trust. Different departments relied on separate reports and manual updates, creating delays and uncertainty.

The Solution

  • Consolidating reporting outputs into a single, trusted source
  • Automating data synchronization to ensure consistency and freshness
  • Defining clear, role-specific views for leadership, accounting, and purchasing

The Outcome

  • Report load times reduced from 10+ minutes to under 20 seconds
  • Critical data synchronized in near real time
  • Teams aligned around the same definitions and metrics
  • Faster, more confident operational and financial decisions
06 — Process

How We Work

We build a comprehensive data foundation that unifies your marketing data ecosystem. The process is thorough but designed to deliver quick wins along the way.

01

Systems Audit & Mapping

~2 weeks

Document all data sources, understand what each system should be trusted for, and identify conflicts and gaps in your current data architecture.

02

Definition & Normalization

~2 weeks

Establish standardized data definitions, resolve metric conflicts, and create a unified data model that serves all stakeholders.

03

Foundation Build

~3-4 weeks

Implement the technical infrastructure: data pipelines, synchronization, and a queryable foundation for reporting and AI.

04

Dashboard & Enablement

~2 weeks

Build reliable dashboards, establish reporting workflows, and train teams on the new data foundation.

Ready to get started?

Let's discuss how Marketing Single Source of Truth can help transform your marketing operations.