How does the Data-Driven Attribution (DDA) model differ from models that assign all credit to a single touchpoint?

Data-driven attribution distributes credit for a key event based on data from each touchpoint in the user journey. It differs from single-touchpoint models because it does not assign all credit to only the first or last interaction. The model uses machine learning to evaluate converting and non-converting paths. This helps estimate the actual contribution of each interaction to the key event outcome.