Abstract: As described herein, a collaborative filtering system, method, and computer program provide a model used to calculate ranked predictions for subscribers. In use, data is received which correlates subscribers of a service provider with offers provided to the subscribers by the service provider, wherein each correlation is associated in the data with an indication of whether the offer was accepted by the subscriber. From the data, a plurality of unique correlations between subscribers and offers are determined. An implicit ranking is calculated for each unique correlation, based on the associated indication of acceptance for correlations matching the unique correlation. Input data is generated that includes each unique correlation with the implicit ranking calculated for the unique correlation. The input data is processed utilizing a collaborative filtering algorithm to generate a model configured to provide predicted implicit rankings for new correlations between subscribers and offers.