DETERMINING ALGORITHMIC MULTI-CHANNEL MEDIA ATTRIBUTION BASED ON DISCRETE-TIME SURVIVAL MODELING

The present disclosure relates to a media attribution system that improves multi-channel media attribution by employing discrete-time survival modeling. In particular, the media attribution system uses event data (e.g., interactions and conversions) to generate positive and negative conversion paths, which the media attribution system uses to train an algorithmic attribution model. The media attribution system also uses the trained algorithmic attribution model to determine attribution scores for each interaction used in the conversion paths. Generally, the attribution score for an interaction indicates the effect the interaction has in influencing a user toward conversion.