One of these attribution models distributes the credit for a conversion equally across all the channels a customer clicked or engaged with before converting. Which is it?

The Linear attribution model distributes credit for a conversion equally across all touchpoints in the customer journey. For example, if a user interacted with four different channels before converting, each channel would receive 25% of the credit. This model provides a balanced view of all contributing channels. Data-driven attribution uses machine learning to assign credit based on the actual contribution of each touchpoint. Time decay gives more credit to touchpoints that occurred closer in time to the conversion. Position-based attribution typically assigns 40% credit to the first and last interactions, and the remaining 20% is distributed evenly to the middle interactions.