Investigating Complementarities in Subscription Software Usage Using Advertising Experiments

In this study, we examine complementarities in usage across a set of related software products from a multi-product firm. We employ a novel experimental approach to causally estimate complementarities, leveraging rich usage data and advertising experiments that affect usage of one product at a time to directly measure complementarities based on consumption rather than purchase. Our approach is particularly useful as digital contexts are characterized by scant price variation, bundled pricing plans, and infrequent purchase or subscription renewal decisions, often making typical cross-price elasticity measures for complementarities infeasible. We apply our approach to data from a software company with a suite of related products and find evidence for varying degrees of complementarity across both user groups and products. We show that accounting for complementarities significantly affects the measurement of ad effectiveness and may impact ad targeting decisions by the firm. We explore heterogeneity in complementarities, finding that complementarities are increasing in users’ prior experience with the product. Ours is one of the first studies to causally examine complementarity in usage in the context of subscription products and demonstrate the implications for advertising targeting decisions, and our identification strategy has application in a variety of contexts