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Measurement and attribution

What is Multi-touch attribution (MTA)?

Multi-touch attribution distributes credit for a conversion across the marketing touchpoints that preceded it, using a rule (first touch, last touch, linear, time decay) or a data-driven model. It describes observed sequence; it does not establish that any touchpoint caused the outcome.

Definition

Definition

Also written: MTA, attribution modelling

Multi-touch attribution distributes credit for a conversion across the marketing touchpoints that preceded it, using a rule (first touch, last touch, linear, time decay) or a data-driven model. It describes observed sequence; it does not establish that any touchpoint caused the outcome.

Coverage is the structural weakness. Consent refusals, cross-device journeys, dark social, offline conversations and privacy restrictions all remove touchpoints from the record, and the model redistributes credit among whatever remains.

That makes MTA useful for operational questions — which campaigns appear in winning journeys — and unreliable as the sole basis for budget reallocation.

The usual error

Where this goes wrong in practice

Reading a model output as causal. Channels that are easy to observe accumulate credit from channels that are not.