Which attribution model is best?

There is no single best model. Position-based is a good default for e-commerce because it values both discovery and closing. Data-driven attribution (DDA) is the most sophisticated approach, using machine learning to weight touchpoints based on their actual contribution.

Why does attribution matter for budget?

If last-click shows email drives 40% of revenue and social drives 5%, you might cut social budget. But first-click might show social drives 25% of initial discovery. Without comparing models, you might cut the channel that feeds your entire funnel.

What is time-decay attribution?

Time-decay gives more credit to touchpoints closer to the conversion. A touchpoint 7 days before purchase gets roughly half the credit of one 1 day before. It assumes recent interactions have more influence on the final decision.

How do I implement multi-touch attribution?

GA4 offers data-driven attribution by default. For custom implementation, you need customer journey data (all touchpoints per user) stored in a data warehouse, then apply the model logic. Tools like Rockerbox, Triple Whale, and Northbeam specialize in e-commerce attribution.

Does iOS privacy affect attribution?

Yes. iOS 14.5+ App Tracking Transparency reduced cross-app tracking, making it harder to attribute social media conversions. Server-side tracking, Conversions API, and probabilistic matching help recover some accuracy.

What is the difference between attribution and incrementality?

Attribution distributes credit for observed conversions. Incrementality measures whether a channel caused conversions that would not have happened otherwise (using holdout tests). Incrementality is more accurate but harder and more expensive to measure.

Attribution Model Comparison Calculator

Compare first-click, last-click, linear, time-decay, and position-based attribution models. See how each model distributes credit across marketing channels.

Conversion Value (Revenue)

Number of Touchpoints

First-Click

TP1: $200.00

100% to first touchpoint

Last-Click

TP4: $200.00

100% to last touchpoint

Linear

$50.00 each

Equal split across 4 touchpoints

Position-Based

TP1: $80.00

40% first + 40% last + 20% middle

Credit Distribution by Model

Touchpoint	First	Last	Linear	Time-Decay	Position
TP 1	$200.00	$0.00	$50.00	$13.33	$80.00
TP 2	$0.00	$0.00	$50.00	$26.67	$20.00
TP 3	$0.00	$0.00	$50.00	$53.33	$20.00
TP 4	$0.00	$200.00	$50.00	$106.67	$80.00

Planning notes, formulas, and examples

About the Attribution Model Comparison Calculator

Attribution models determine how credit for a conversion is distributed across the marketing touchpoints in a customer's journey. Different models can dramatically change which channels appear most valuable, directly affecting where you allocate budget.

This calculator lets you enter a customer journey with multiple touchpoints and see how revenue credit shifts between first-click (gives all credit to first interaction), last-click (gives all to the last), linear (equal credit to all), time-decay (more credit to recent touchpoints), and position-based (40% first, 40% last, 20% middle).

Understanding attribution is critical because no single model is "correct." Each illuminates a different aspect of channel performance. Comparing them side by side reveals which channels are over- or under-valued by your default model.

When This Page Helps

Most analytics platforms default to last-click attribution, which undervalues awareness channels and overvalues closers. This page shows the discrepancy so you can make more balanced budget decisions.

How to Use the Inputs

Enter the total conversion value (revenue from the order).
Enter the number of touchpoints in the customer journey.
The calculator distributes credit across touchpoints under each model.
Compare how each model values early, middle, and late touchpoints.
Use the comparison to inform your marketing budget allocation.

Formula used

First-Click: 100% to touchpoint 1
Last-Click: 100% to last touchpoint
Linear: 100% / N to each touchpoint
Time-Decay: Weighted by recency (half-life decay)
Position-Based: 40% first + 40% last + 20% split among middle

Example Calculation

Result: First: $200/$0/$0/$0 | Last: $0/$0/$0/$200 | Linear: $50 each

A $200 order with 4 touchpoints: First-click gives all $200 to the first channel. Last-click gives all $200 to the last. Linear gives $50 to each. Position-based gives $80/$20/$20/$80. Time-decay gives roughly $25/$35/$55/$85 depending on decay rate.

Tips & Best Practices

No single attribution model is correct — use multiple models to triangulate the truth.
Last-click attribution undervalues brand awareness channels; first-click undervalues closing channels.
Position-based (40/20/40) is a good compromise for most e-commerce businesses.
Run attribution comparison quarterly to catch shifts in channel performance.
Consider data-driven attribution (available in GA4) which uses machine learning instead of rules.
Always compare attributed revenue against actual ad spend for each channel to find misallocations.

The Attribution Problem in E-commerce

Modern customer journeys involve an average of 6–8 touchpoints across multiple channels before a purchase. A customer might see a Facebook ad, click an Instagram story, read a blog post via Google, and finally convert from an email. Which channel "caused" the sale? Attribution models attempt to answer this question.

Model Comparison at a Glance

First-click favors awareness channels (social, display). Last-click favors conversion channels (email, branded search). Linear treats all equally. Time-decay favors recency. Position-based balances discovery and closing. Comparing all five reveals which channels your default model over- or under-credits.

Moving Beyond Rules-Based Models

Data-driven attribution (DDA) uses machine learning to analyze thousands of customer journeys and determine the actual contribution of each touchpoint. It is more accurate than any rules-based model but requires sufficient data volume (typically 3,000+ conversions per month) to produce reliable results.

Sources & Methodology

Last updated: February 8, 2026

Frequently Asked Questions

There is no single best model. Position-based is a good default for e-commerce because it values both discovery and closing. Data-driven attribution (DDA) is the most sophisticated approach, using machine learning to weight touchpoints based on their actual contribution.