Identifying Complementarities in Subscription Software Usage Using Advertising Experiments

In this study, we causally examine complementarity in usage across a set of related soft- ware products from a multi-product firm. Digital contexts are characterized by little price variation, bundled pricing plans, and infrequent purchase or subscription renewal decisions. In these settings, computing typical cross-price elasticity measures for complementarities is often infeasible. We employ a novel experimental approach to causally identify complementarities, leveraging rich usage data and advertising experiments that affect usage of one product at a time. Though this approach, we directly measure complementarities based on usage rather than purchase. We test our approach using data from a software company with a suite of related products, and find evidence for varying degrees of complementarity between products in the suite. We also explore variation in these effects across user populations, finding that they vary across both product and consumer segments. We show that accounting for complementarity significantly affects the measurement of ad effective- ness. We also document the impact of our estimates on ad targeting decisions by the firm. Ours is one of the first studies to causally examine complementarity and substitutability between products in this context of subscription products, and our identification strategy has application in a variety of contexts.