How to monetize data: An economic analysis of data monetization strategies under competition

Abstract

With data being generated at an unprecedented rate, monetizing data has become a paramount issue in this era of the digital economy. Firms have traditionally leveraged consumer data to improve their product or service offerings and increase their sales revenue, which is indirect data monetization. The recent emergence of online data markets and the data brokerage industry have facilitated direct data monetization, enabling firms to obtain additional revenue by selling their anonymized data directly to data brokers. This study develops a game-theoretic model to investigate the impact of direct data monetization on competition between firms. Our results show that in equilibrium, high-value firms with competitive advantages in product or service value often sell less data than low-value firms, implying that high-value firms rely less on direct data monetization than low-value firms. Surprisingly, as direct data monetization prevails, high-value firms further dominate the market for selling products or services, especially when the data broker's analytics capability is high. This result reveals that data brokers with high analytics capabilities can hinder, rather than facilitate, market competition. Finally, direct data monetization may benefit both consumer surplus and social welfare because it facilitates data-sharing between firms, allowing firms to obtain additional insights to improve their product or service offerings. These findings are explored in-depth, along with different model extensions and their relevant managerial implications.