One of these attribution models relies on machine learning algorithms to assign credit for a conversion across various touchpoints. Which is it?

Data-driven attribution uses machine learning to analyze your account's unique conversion paths and assign fractional credit to each touchpoint. It considers factors like the position of the interaction, the type of interaction, and the time between interactions, providing a more accurate and nuanced understanding of how different channels contribute to conversions. Time decay attribution gives more credit to touchpoints that happened closer in time to the conversion. First click attribution assigns all credit to the first interaction a user had with your content. Last click attribution gives all credit to the final interaction before a conversion. While simpler, these models don't leverage advanced analytics to understand complex user journeys as effectively as data-driven attribution.