Linear Attribution
Linear attribution is a multi-touch model that splits conversion credit equally among every touchpoint in the buyer's journey.
In depth
Linear attribution treats each interaction as equally important, so a journey with five touchpoints assigns 20% of the conversion to each one regardless of timing or role. It works by counting the qualifying touchpoints on a path and dividing the credit evenly, which makes it the simplest multi-touch model to calculate and the easiest to defend as unbiased. Teams reach for it when they want to acknowledge the whole journey without arguing about which step mattered most.
The common pitfall is that equal weighting is rarely realistic: a throwaway display impression gets the same credit as the demo that closed the deal, which can flatter low-value channels. In a quiz-funnel and lead-qualification workflow, linear attribution gives your top-of-funnel ad, your landing page, and your scorecard quiz each a visible share of the conversion, which is useful for proving that early stages contribute, but you should switch to time-decay or position-based when you need to weight the steps that actually move people forward.
Example in practice
Frequently asked questions
How does linear attribution calculate credit?
It counts the qualifying touchpoints in a conversion path and divides the credit equally among them. A four-touch journey gives each touchpoint 25%, no matter when it happened.
When is linear attribution a good choice?
It suits longer, multi-step journeys where every stage genuinely contributes and you want a simple, defensible baseline. It is also a sensible starting point before testing weighted models like time-decay.
What is the main weakness of linear attribution?
It assumes all touchpoints matter equally, which is rarely true, so it can over-reward low-impact interactions. When some steps clearly drive more value, a weighted model represents reality better.