Abstract: Aspects of the disclosure relate to a computing system, computer-implemented method, and computer readable storage media for predicting, for a consumer in a group of consumers assigned to a subset of consumers in a plurality of subsets at the present time, which subset the consumer will be assigned to at a predetermined time in the future. Further aspects of the disclosure relate to a computer-implemented method for determining the likelihood that consumers in a group of consumers will migrate between subsets in a plurality of subsets of consumers. Further aspects of the disclosure related to a computer-implemented method for determining an expected revenue for a group of consumers at a predetermined time in the future.

Abstract: A system, method, and computer readable storage media for training a model to estimate an unknown consumer behavior while preserving consumer privacy by combining a first training data set of a first organization with a second training data set of a second organization on a third-party computer system, wherein the second training data set contains an attribute value the first organization wishes to estimate, and wherein the first organization cannot access the third-party computing system, providing a trainable model definition to the third-party computer, training the model, and returning the trained computer model.