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Attribution Models: First-Touch, Last-Touch, Linear, Time-Decay & Data-Driven Compared

Five attribution models, one table: how each assigns credit, what it fits, and what to watch out for.

The five models, compared

ModelHow credit is assignedBest fitWatch out for
First-touch100% to the first touch in the journeyUnderstanding what drives initial awarenessIgnores everything that closed the sale
Last-touch100% to the last touch before conversionShort sales cycles, single-channel journeysOvercredits bottom-funnel/branded channels
LinearEqual credit across every touchA simple, defensible multi-touch baselineTreats a footer-link click the same as a demo request
Time-decayMore credit to touches closer to conversionLonger sales cycles where recency mattersStill somewhat arbitrary about the decay rate
Data-drivenStatistical/ML weighting from your own conversion dataHigh-volume accounts wanting the most accurate splitNeeds real conversion volume; a black box to explain to stakeholders

Types of attribution models: the broader landscape

Beyond the five above, most platforms group models into two families: single-touch models (first-touch, last-touch) that assign all credit to one interaction, and multi-touch models (linear, time-decay, position-based, data-driven) that spread credit across the journey. See our dedicated multi-touch attribution guide for the multi-touch family specifically.

How to choose

hypothesis, from implementation experience rather than a controlled study: the model choice matters less than most teams assume, and identity resolution/event collection quality matters more. A sophisticated data-driven model fed by broken identity resolution will still produce numbers nobody trusts. Fix collection first (see the attribution pillar guide), then pick the simplest model that matches your sales cycle length.

Linear attribution model, in practice

The linear model is worth calling out separately because it is the most common starting point for teams moving off last-click: it requires no statistical modeling, it is easy to explain to stakeholders, and it corrects the worst distortion of last-click (ignoring the top of funnel entirely) without introducing a black box.

Frequently Asked Questions

What are the main types of attribution models?

The main types are first-touch, last-touch, linear, time-decay, and data-driven (algorithmic) attribution. Some platforms also offer position-based (U-shaped) models as a sixth variant.

What is a data-driven attribution model?

A data-driven attribution model uses statistical or machine-learning methods to assign credit based on actual conversion patterns in your data, rather than a fixed rule. It requires enough conversion volume to be statistically reliable - it is not a good fit for low-volume accounts.

Which attribution model does Google Analytics use by default?

Google Analytics 4 uses data-driven attribution by default where there is enough data; it falls back to a cross-channel last-click model when data-driven attribution cannot be calculated. Confirm the current default in your own property, since platform defaults change.

Should I use a single attribution model everywhere?

No - it is common and reasonable to use different models for different decisions: a simple model for day-to-day channel reporting, a more sophisticated model for budget reallocation decisions.

Not Sure Which Model Fits Your Sales Cycle?

We look at your actual conversion data and identity setup before recommending a model - not the other way around.

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