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 directly affect the usage of only one product at a time to measure complementarities based on consumption rather than purchase. Our approach is particularly useful as digital contexts are characterized by the simultaneous presence of both substitutability and complementarity between products. They also have 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 they are larger for users who have used the products heavily in the past, but small or zero for those who have not. Ours is one of the first studies to causally examine complementarity in usage in the context of subscription products, and our identification strategy can be applied to a variety of contexts.
