Multi-Touch Attribution
In one line
Multi-touch attribution (MTA) distributes credit for a conversion across every marketing touchpoint a user encountered, rather than handing it all to the last click.
Going deeper
Multi-touch attribution exists because last-click hands all the credit to the final ad. If a user saw a Facebook ad, read a blog post and clicked a search ad a week later before buying, MTA spreads the credit across all three.
Models vary widely — Linear (equal weight), U-Shape (weight first and last), Time Decay (later touchpoints earn more), Data-Driven (weights learned from your data). Switching the model alone can reshuffle channel performance, which is why model choice is often half political.
Honestly, post-iOS 14 tracking limits and cookie deprecation have eroded MTA's precision. Most teams now pair it with media-mix modelling and incrementality experiments rather than treating MTA as the single source of truth.
Related terms
Attribution Model
An attribution model is a framework for deciding how credit for a conversion is split across the different touchpoints a customer interacted with on the way there.
MarketingFirst-Party Data
First-party data is information you collect directly from your own customers and channels — the most reliable marketing asset in the post-cookie era.
MarketingGA4
Google Analytics 4 (GA4) is Google's current analytics platform for web and app, built on an event-based data model rather than the session-centric model that defined Universal Analytics.
MarketingROAS
Return on ad spend (ROAS) is revenue divided by ad spend — the headline efficiency metric for performance campaigns where revenue can be tracked back to the channel.
MarketingPaid Media
Paid media is any channel where you pay to be seen — search ads, display, social ads, video and OTT all fall under this umbrella.
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