Attribution Model
An attribution model defines how credit for a conversion is shared among the marketing touchpoints a customer interacted with before converting.
What is an attribution model?
Customers rarely convert after a single interaction. A B2B buyer might first see a LinkedIn ad, later find a blog post through search, return via a Google Ads click and finally fill in a form after typing in the URL. An attribution model defines how the credit for that conversion is shared among these touchpoints.
Common models:
- Last click: all credit goes to the final click. Simple, but it undervalues channels that create demand early on.
- First click: all credit goes to the first interaction.
- Rule-based models such as linear, time decay or position-based split credit according to fixed rules.
- Data-driven attribution: credit is assigned with machine learning, based on how touchpoints actually contribute to conversions in your account.
In Google Analytics 4 and Google Ads, data-driven attribution is now the default, and Google has retired most rule-based models; last click remains available for comparison.
Attribution has clear limits: it only sees tracked, consented interactions (Consent Mode), struggles with cross-device journeys and offline touchpoints such as sales calls or trade fairs, and each platform tends to claim credit for itself. That is why many companies complement it with CRM data, incrementality tests or marketing mix modelling.
For international reporting, compare markets with the same model and settings: journey lengths and channel roles often differ by country, and inconsistent attribution leads to wrong budget decisions – for example cutting channels that drive awareness in a new market.