Glossary
What is Attribution Model?
An attribution model is the rule set a business uses to assign credit for a conversion across the multiple marketing touchpoints — ads, emails, organic search results — a customer engaged with beforehand.
Most customers touch several marketing channels before converting — they might click a Google ad, leave, later see a retargeting ad on Instagram, then find the site again through an organic search a week later and finally buy. An attribution model decides which of those touchpoints gets credit for the sale, and that choice changes which channels look effective and which look wasteful.
Last-click attribution, still a common default, gives 100% of the credit to the final touchpoint before conversion — simple to calculate, but it systematically undervalues awareness and consideration-stage channels that start the journey but rarely close it directly. First-click does the opposite. Linear and time-decay models split credit across all touchpoints using different weighting rules, and data-driven attribution (now the default model in GA4) uses machine learning to assign credit based on patterns across all converting and non-converting paths in the account's own data, rather than a fixed rule.
The practical stakes are budget decisions: a channel that looks weak under last-click attribution might be doing real work earlier in the funnel, and cutting it based on a single-touch model can quietly remove the thing that was generating demand for every other channel to close.