Prominence-for-Data Schemes in Digital Platform Ecosystems: Implications for Platform Bias and Consumer Data Collection

Abstract

It is crucial for content providers (CPs) to appear prominently on dominant online platforms in order to attract consumer demand. Platforms often offer content providers prominence in return for a monetary compensation (e.g., a sponsored listing). We consider the case where CPs can pay the platform for prominence by sharing data about their consumers, rather than money. Since data is non-rivalrous, the economic effects of data sharing for prominence are more complex and differ from paying for prominence with money. In a game-theoretic model we show that more consumer data will be collected as soon as CPs can obtain prominence on the platform. Whether the platform is more biased under a prominence-for-money scheme or under a prominence-for-data scheme depends on the marginal revenue from shared (non-exclusive) data. If this marginal revenue is high, e.g., because the platform and the CPs do not compete fiercely on the data market, then prominence-for-data will yield a higher platform bias, lead to more data collection by the CPs, and ultimately lower consumer surplus. We also show that a vertically integrated dominant platform can extort the non-integrated CP to share data even without giving prominence, and that our results are robust when CPs can strategically invest in data analytics technology. Our results therefore bear important insights for the regulation of data-rich online platforms.