Attribution Model Comparison

Upload conversion-path data in simple CSV format and compare five attribution models side by side. See how much credit each channel earns under last-click vs linear vs time-decay vs position-based. Nothing leaves your browser.

Measurement Intelligence

The attribution model you pick decides where next quarter's budget goes.

Last-click rewards whichever channel closed the sale, usually paid search and direct. First-click rewards whatever introduced the prospect, usually SEO and display. Linear, time-decay, and position-based split credit across the whole path. The gap between these models for the same data is often 30-60% of a channel's apparent value. This tool makes that gap visible.

1. Paste or upload conversion paths

CSV format: path, conversions, revenue

Separate touchpoints with " > ". Each path can be first touch to conversion. Channels can be any string.

Comparison across models

Credit assigned per channel (revenue)

Each column is a different attribution model

Channel	Last-Click	First-Click	Linear	Time-Decay	Position-Based	Range

Visual comparison

Share of revenue credit by model

Bars show relative credit; look for channels where one model gives much more than another

Model definitions and when to use each

Last-Click

100% credit to the final touchpoint before conversion. GA4's default until 2023. Simple, but systematically underweights awareness channels (SEO, display, social).

Best for: short sales cycles, bottom-of-funnel optimisation, direct-response.

First-Click

100% credit to the first touchpoint in the path. Rewards awareness channels. Systematically underweights closing channels.

Best for: brand-building budgets, measuring top-of-funnel programs.

Linear

Equal credit to every touchpoint. Simple to explain. Can over-reward low-cost channels that happen to touch many paths.

Best for: B2B with long consideration cycles where every touch matters.

Time-Decay

More credit to touches closer to conversion. Half-life typically 7 days. Compromise between last-click and linear.

Best for: mid-funnel programs, retargeting evaluation.

Position-Based (U-shaped, 40/20/40)

40% credit to first touch, 40% to last touch, 20% split across the middle. Rewards both discovery and closing.

Best for: balanced marketing programs where awareness and conversion are both tracked.

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Frequently asked questions

What is an attribution model?

A rule for distributing credit for a conversion across the touchpoints that led to it. Different models give different channels different credit.

What are the common models?

Last click, first click, linear, time-decay, position-based, data-driven. The tool compares all of them side by side.

Which model should I use?

Data-driven is the modern standard in GA4. It uses conversion probability modelling. For sanity-checking use linear or time-decay as a backup view.

Why does last-click overweight some channels?

Last-click gives 100% credit to the last touch. Direct and brand search tend to be last clicks, so they look bigger than they are. Google Ads brand is a classic case.

Why is first-click interesting?

Shows which channels discover customers. Great for brand marketing attribution.

What is position-based attribution?

40% first touch, 40% last touch, 20% distributed across middle touches. Reflects the awareness + conversion dual-importance view.

What is time-decay?

Later touches get more credit than earlier ones. Half-life of 7 days by default. Useful for short consideration cycles.

How does data-driven attribution differ?

Uses machine learning on your actual conversion paths. Each channel's credit reflects how much it contributes vs an identical path without it.

Can one page see different results across models?

Yes dramatically. The whole point of model comparison. If results agree across models the channel is unambiguously valuable.

Does the tool need my GA4 export?

Yes. Export conversion paths. The tool runs each model and reports per-channel credit.

What is incrementality vs attribution?

Attribution distributes credit for conversions that happened. Incrementality asks whether spend caused the conversion in the first place. See the Incrementality Test tool.

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