Definition
Multi-touch attribution spreads conversion credit across multiple touchpoints (first, last, and middle touches).
How to use it
- MTA can improve visibility into upper-funnel touches versus last-click.
- It's still attribution, not causality; validate with experiments for big bets.
Common mistakes
- Assuming MTA is incrementality (it is still model-based attribution).
- Using complex models without validating against experiments.
Measured as
Measure Multi-touch Attribution (MTA) with a fixed attribution window, conversion event, and spend basis before comparing campaigns or creative tests.
Misused when
- Assuming MTA is incrementality (it is still model-based attribution).
- Using complex models without validating against experiments.
Operator takeaway
- MTA can improve visibility into upper-funnel touches versus last-click.
- It's still attribution, not causality; validate with experiments for big bets.
- Use Multi-touch Attribution (MTA) only inside a stable attribution rule, conversion definition, and time window so campaign comparisons stay honest.
- If performance changes, check whether the metric moved for a real business reason or because the measurement setup changed underneath you.
Next decision
- Read Attribution vs incrementality: what to trust, when, and how to test if the decision depends on interpretation, policy, or trade-offs beyond the raw formula.
- Decide which report owns Multi-touch Attribution (MTA) before comparing campaigns, channels, or creative tests.
Where to use this on MetricKit
Guides
- Attribution vs incrementality: what to trust, when, and how to test: A practical guide to attribution vs incrementality: common attribution models, window pitfalls, how MER/marginal ROAS fit in, and how to run holdout/geo tests.
- UTM + GA4 attribution: practical tracking for paid ads (without lying to yourself): A practical guide to UTMs and GA4: consistent source/medium/campaign tagging, conversion deduplication, and common attribution traps.