52 Pages Posted: 7 Sep 2016
Date Written: September 4, 2016
Success breeds success in many mass market industries, as well known products gain further consumer acceptance because of their visibility. However, new products must struggle to gain consumer’s scarce attention and initiate that virtuous cycle. The newest mass market industry, mobile apps, has these features. Success among apps is highly concentrated, in part because the “top app lists” recommend apps based on past success as measured by downloads. Consequently, in order to introduce themselves to users, new app developers attempt to gain a position on the top app lists by “buying downloads,” i.e., paying a user to download the app onto her device. We build a model to rationalize this behavior, taking into account the impact of buying downloads on top list ranking and optimal investment in buying downloads. We leverage a private dataset from one platform for buying downloads to identify the return on this investment, as a test for the assumption of the model. $100 invested will improve the ranking by 2.2%. We provide some informal tests of the two empirical predictions of the model: (1) there are two humps in the diffusion pattern of the app, and (2) early rankings are less persistent than later rankings. We estimate an empirical analog of the model to show the relative importance of buying downloads and rich heterogeneity in the market. We simulate counterfactuals to evaluate the efficiency of top-ranking lists.
Suggested Citation: Suggested Citation
Li, Xing and Bresnahan, Timothy and Yin, Pai-Ling, Paying Incumbents and Customers to Enter an Industry: Buying Downloads (September 4, 2016). Available at SSRN: https://ssrn.com/abstract=2834564 or http://dx.doi.org/10.2139/ssrn.2834564