1. A method for creating a data-driven attribution model, comprising: identifying, for a given time period, a plurality of visits to a particular website; identifying, for each visitor identifier associated with the identified plurality of visits, a path associated with the visitor identifier, the path including at least one event, each of the at least one event having a corresponding index position indicating a position of the event relative to positions of other events included in the path; determining, by a processor, for each path type associated with the identified paths, a path-type conversion probability based on a number of visits corresponding to the path type that resulted in a conversion; calculating, by the processor, for each of a plurality of the path types associated with the identified paths, a counterfactual gain for each event based on a conversion probability of the given path type and a conversion probability of a path type that does not include the event for which the counterfactual gain is calculated; determining, by the processor, for each event of each of the plurality of path types, an attribution credit based on the calculated counterfactual gain of the event; and storing, for each of a plurality of the path types associated with the identified paths, the determined attribution credit for each event included in the path type.