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Attribution models

U-shaped attribution (position-based 40/20/40)

U-shaped attribution is the position-based model in its classic form: the first interaction and the conversion-driving interaction each receive a large fixed share (commonly 40% each), and the remaining credit is split among the middle touches. It is a rules-based heuristic that values discovery and closing equally, and it is the lens many tools mean when they say 'position-based'.

Verified against primary sources

What this means

U-shaped (also called position-based) attribution applies fixed weights based on where a touch sits in the path. In the widely used form, the first touch gets 40%, the last/converting touch gets 40%, and the middle 20% is divided evenly among any interactions between them. With only two touches, each typically takes 50%.

It is a compromise between first-click and last-click: rather than crediting one end, it credits both ends generously and treats the middle as supporting cast.

When it fits and when it does not

U-shaped suits funnels where introduction and closing are the decisive moments — for example, a first paid-search discovery and a final branded-search return. It is weak when the middle does the real persuading (long consideration journeys) because the rule caps the middle at a small fixed share regardless of how much work those touches did.

Because the weights are arbitrary constants, U-shaped tells you about path shape and your chosen heuristic, not about measured causal contribution.

How it appears in analytics and logs

Credit concentrated at the two ends of a path means the model is U-shaped; mid-funnel channels will always look smaller here than they would under a linear model, by design rather than by performance.

Diagnostic use case

Use U-shaped attribution when you want to reward both the channel that introduced the user and the channel that closed the deal, without ignoring the assisting middle entirely.

What WebmasterID can help detect

WebmasterID records first-party touchpoints with source and medium, so you can reconstruct first/middle/last positions and reason about how a U-shaped split would assign credit across your own paths.

Common mistakes

Privacy and accuracy notes

U-shaped attribution distributes credit across recorded touchpoints; it needs path data, not identity. The weighting is a fixed rule, so it makes no probabilistic guesses about people.

Related pages

Sources and verification notes

Last reviewed 2026-06-24. Facts are checked against primary/official sources where available; uncertain specifics are marked “Data not yet verified” rather than guessed.