Abstract: The disclosed embodiments provide a system for performing unified propensity modeling across product versions. During operation, the system determines features and labels related to converting to multiple versions of a product by a first set of members, wherein the features and the labels span a unified timeframe and adhere to a unified data logic. Next, the system inputs the features and the labels as training data for one or more machine learning models. The system then applies the machine learning model(s) to additional features for a second set of members to produce scores representing likelihoods of the second set of members converting to the multiple versions of the product. Finally, the system generates, based on the scores, output for targeting the second set of members with the product.