A rule or algorithm that assigns conversion credit across the marketing touchpoints that influenced a customer's decision — 'how do we credit a signup that saw a Facebook ad, then clicked a Google ad, then opened an email?'
Attribution Models reconcile that customers rarely convert from one touchpoint — they encounter your brand many times. Common models: last-touch (all credit to the final touchpoint), first-touch (credit to the discovery touchpoint), linear (equal credit across all touchpoints), time-decay (more credit to recent touchpoints), position-based / U-shaped (40% first, 40% last, 20% middle). Data-driven attribution uses ML to learn credit weights from your specific funnel — more accurate but requires significant conversion volume.
Switching from last-touch to data-driven attribution and discovering that organic search content was driving 35% of conversions previously credited entirely to retargeting ads.
Attribution model choice directly drives budget allocation — last-touch over-credits retargeting; first-touch over-credits awareness; the right model depends on your funnel shape and decision horizon.
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