Attribution

Attribution Payback Matrix

Meta says 45-day payback. CRM says 90 days. Both are correct. One will break your business.

The Problem

Only 52% of marketers use any attribution reporting at all. The other 48% fly blind on platform dashboards.

Here’s the pattern: Teams scale based on Attributed Payback (platform data) without ever calculating True Payback. They spend $5M acquiring customers at what they think is a 45-day payback. Then board meeting questions force them to look at CRM data. True Payback: 90 days. By then, they’ve acquired customers at 2x the target CAC. And they’re already committed.

Why Platform Attribution Lies

1.Organic misattribution — 15-40% of 'attributed' revenue was happening anyway

2.Multi-touch bias — Last-click gets credit for multi-touch journeys

3.Hidden acquisition costs — Platform data doesn't include sales ops, onboarding, or support

4.Modeled conversions — Probabilistic models optimized to show you good numbers

5.Expansion invisibility — Stops at first purchase — misses expansion revenue that changes economics

The Three Types of Payback

There are three different payback numbers. Most teams use the wrong one.

Type 1

Attributed Payback (What Platforms Tell You)

$100K spend → platform reports $320K attributed revenue → 28-day payback. Fast to calculate. Looks great in decks.

Use for: A/B testing directional accuracy. Not for scaling decisions.

Type 2

True Payback (What Your Data Shows)

Fully-loaded CAC ÷ actual revenue from CRM. Same $100K ad spend + $20K sales ops + $15K onboarding = $135K fully-loaded CAC against $180K actual revenue.

True Payback = Fully-loaded CAC ÷ monthly revenue per customer

Type 3

Strategic Payback (What Actually Matters)

Includes expansion revenue, referrals, and downstream value. This is the payback that predicts long-term business health — but requires the most sophisticated data infrastructure to calculate.

The First-Party Data Advantage

The solution to the attribution gap isn’t better attribution tools — it’s building a first-party data moat. Teams that own their data can calculate True Payback directly instead of relying on platform estimates.

The Data Independence Scorecard

Score each dimension from 1 (Dependent) to 3 (Independent):

•Identity — Do you own your user identity graph?

•Consent — Are you collecting first-party consent?

•Attribution — Can you measure without platform data?

•Activation — Can you target using owned signals?

•Measurement — Can you validate results independently?

Score out of 15

5-7: Heavily dependent. High risk.

8-10: Transitioning. Focus on gaps.

11-13: Building independence. Keep investing.

14-15: Data moat established. Defend and optimize.

The Tools

Attribution Payback Matrix

Calculate Attributed vs. True vs. Strategic Payback and see where platform data diverges from reality.

Try Free →

Data Independence Scorecard

Assess your first-party data maturity across 5 dimensions and get a prioritized action plan.

Try Free →

Related Issues

Issue #47

The Attribution Payback Matrix

The full framework for measuring real payback periods

Issue #48

The First-Party Data Moat

Building data independence and the Data Independence Scorecard

Get the next framework first

Join 2,000+ mobile marketers getting one original framework every Saturday. No fluff, no repurposed threads — just sharp thinking you can use Monday morning.

Subscribe to Diversified UA