Attribution and measurement benchmarks explain how e-commerce teams assign credit to marketing and how measurement shifts when tracking changes.
This silo groups practical benchmark structures for attribution models, incrementality testing, and common measurement signals.
Back to the hub:
E-commerce Statistics.
If you only publish two pages first, start with
attribution model usage
and incrementality test adoption.
Featured (start here)
The most useful building blocks for measurement narratives and analytics reporting.
Attribution model usage share
Benchmark structures for how often teams use last-click, data-driven, or multi-touch models.
Incrementality test adoption
Benchmark structures for how often teams run incrementality experiments and how they report results.
Attribution becomes more meaningful when paired with funnel outcomes:
Conversion funnel benchmarks.
Pages in this silo
Prepared links so you won’t need to edit this silo later as pages go live.
How to use attribution benchmarks
A checklist for keeping measurement comparisons valid.
- Label the model. Last-click, data-driven, and multi-touch are not comparable without context.
- State the lookback window. Lookback windows can change ROAS and conversion attribution dramatically.
- Separate measurement from performance. Changes in tracking can shift reported results even without true performance change.
- Prefer incrementality for “truth checks”. Use incrementality to validate channel lift when tracking is noisy.
Reference pages:
Methodology •
Glossary •
Sources