
Multi-touch attribution is an approach to measuring marketing performance that assigns conversion credit to multiple touchpoints in the customer journey, rather than a single one.
In ecommerce, customers rarely buy after just one interaction. They may discover a product via social media, read reviews on your blog, click a retargeting ad, and finally purchase after an email reminder. Multi-touch attribution recognizes all these steps, giving a more accurate picture of which channels work together to drive sales. This is essential for understanding the synergy between upper-funnel and lower-funnel marketing efforts.
Multi-touch models can be rule-based (linear, time-decay, position-based) or algorithmic (data-driven). Rule-based models use fixed formulas to split credit; data-driven models use machine learning to evaluate each touchpoint’s actual impact. For ecommerce, multi-touch tracking often requires integrating analytics tools with your ecommerce platform and ad accounts to capture the full path.
A skincare brand running influencer campaigns, paid social ads, and email finds that last-click attribution undervalues influencer partnerships. With multi-touch attribution, they see influencers often start the journey, even if the final click comes from a discount email, leading them to increase influencer investment.
Multi-touch attribution is not the same as omnichannel tracking, which focuses on following the same customer across platforms. Multi-touch is about distributing credit across those touchpoints.
Position-Based Attribution
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