Abstract: 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.

Abstract: 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.

Abstract: Systems and methods for distributing online ads with electronic content according to a campaign strategy that is adjusted based on intraday modeling. One embodiment of the invention determines a campaign strategy for a current day allocating a daily budget to automatically bid on online ad opportunities using allocated budget amounts and distributes online ads during a first portion of the current day according to the campaign strategy. Current day data regarding use of the distributed online ads during the first portion of the current day is received and compared with historical data to determine a correction factor that accounts for a magnitude of difference between the current day data and the historical data. The campaign strategy for the current day is adjusted using the correction factor and additional online ads are distributed during a second, later portion of the current day according to the adjusted campaign strategy.