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Linear Attribution
A multi-touch model that distributes credit equally across all touchpoints.
On this page (5 sections)
A multi-touch model that distributes credit equally across all touchpoints.
Why It Matters
Linear attribution democratizes credit across your marketing mix, preventing the over/undervaluation inherent in single-touch models. It's the simplest MTA model to implement and understand, making it an excellent starting point for brands moving beyond last-touch.
Practical Example
Scenario
A customer journey includes 4 touchpoints: Facebook ad, influencer post, email newsletter, and Google search. Each receives 25% of the $80 AOV credit.
Calculation
Facebook: $20 | Influencer: $20 | Email: $20 | Google: $20Result
This reveals that all four channels contribute to the sale, rather than Google getting 100% credit as in last-touch.
Pro Tips
- 1Linear is great for initial MTA exploration—patterns you discover may inform which weighted model to use later
- 2Compare linear results to last-touch to identify channels you've been undervaluing
- 3Use linear to justify brand awareness spend that shows minimal ROI in last-touch models
Common Mistakes to Avoid
Frequently asked questions
Put it to work
Related Terms
Previous
Last-Touch Attribution
Next
Lookalike Audience (LAL)
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7.7x blended return at scale — seven figures attributed, across five straight quarters · Modern Prairie · Apr 2025–Jun 2026 Read the Modern Prairie case study