2 min lesson
Attribution honesty
Name the key items in "Attribution honesty", then explain why each one matters.
Step 1 of 3
Attribution is where GTM data is most tempting to lie. Every model is a simplification with a built-in bias and a developer-led motion makes the lie easier because product usage muddies every marketing claim.
Truth-seeking, the value screened throughout this loop, shows up most sharply here. The honest answer to "did the startup program drive that revenue?" is usually "partly and here's how confident I am," not a clean number that makes a slide look good.
- Model
- First-touch
- How it assigns credit
- All credit to the first interaction
- Built-in bias
- Over-credits awareness; ignores what closed
- Model
- Last-touch
- How it assigns credit
- All credit to the final interaction
- Built-in bias
- Over-credits closing; ignores what created demand
- Model
- Linear multi-touch
- How it assigns credit
- Equal credit across all touches
- Built-in bias
- Flatters minor touches; assumes every touch mattered equally
- Model
- Time-decay
- How it assigns credit
- More credit to touches near the close
- Built-in bias
- Defensible but still a guess at causality
| Model | How it assigns credit | Built-in bias |
|---|---|---|
| First-touch | All credit to the first interaction | Over-credits awareness; ignores what closed |
| Last-touch | All credit to the final interaction | Over-credits closing; ignores what created demand |
| Linear multi-touch | Equal credit across all touches | Flatters minor touches; assumes every touch mattered equally |
| Time-decay | More credit to touches near the close | Defensible but still a guess at causality |
No model measures cause; each one redistributes correlation under a different assumption.