A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: tracking touchpoints by a user over a first time period; after receiving an order, determining, using a machine-learning model, a respective contribution of each of the touchpoints, wherein the machine-learning model is trained to predict a probability of the user placing the order during a second time period based on an input feature vector representing a set of touchpoints; and allocating a respective percentage of credit for the order to the each of the touchpoints based on the respective contributions of the each of the touchpoints. Other embodiments are disclosed.