GlossaryAttribution & Bias

Attribution Modeling

Also known as: MTA, Multi-Touch Attribution

Attribution modeling is the rule-based process of assigning credit for a conversion to specific touchpoints. Common models include Last-Click, First-Click, Linear, and Time-Decay. While useful for tactical optimization, attribution models struggle to measure true causality compared to incrementality methods.

The Short Version

Deciding who gets the commission for the sale.

Often Confused With

The Credit War

Marketing channels fight for credit. Search claims it. Social claims it. Email claims it.

Attribution Picking is often political. 'Last Click' favors Search. 'View Through' favors Social. None of them represent the objective truth of what drove the growth.

How it works

1

Track user path: Ad A -> Ad B -> Ad C -> Purchase

2

Apply rule: 'Give 100% to Ad C' (Last Click) or 'Split evenly' (Linear)

3

Report revenue based on these assignments

Common Misconceptions

Believing the model is 'True' (It is just a representation)

Changing models to make numbers look better

Ignoring offline impact (Attribution usually requires a digital click)

In SpendSignal

SpendSignal ingests attribution data not to believe it, but to contrast it against Incrementality. We show you 'Attributed ROAS' vs 'Incremental ROAS' so you can see where the models are lying.

Frequently Asked Questions

QShould I delete my attribution tool?

No. Use attribution for day-to-day campaign management (e.g., which creative is working). Use SpendSignal for budget allocation and strategy.

QWhat is the best attribution model?

There isn't one. They all have biases. Data-Driven Attribution is slightly better, but still ignores incrementality.

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