The role of data: A two-sided model of competition between Google and DuckDuckGo

This thesis aims to analyze the consumer data’s role as a revenue-shifting input in a two-sided competition-in-utility model between a search engine collecting personalized consumer data (Google) and one that does not (DuckDuckGo). Search engines are examples of platforms characterized by network externalities. They harvest the attention of users and resell this attention to advertisers. As such, standard market mechanisms typical of single-sided markets do not apply. In our model, advertisers are willing to pay a higher premium for targeted search results utilizing consumer data. As such, a search engine like Google can command higher prices per sponsored link if it collects more personalized data from its users. This must be balanced against demand effects stemming from consumer aversion towards the disclosure of personal data. DuckDuckGo, a search engine that explicitly does not collect consumer data, can use investments in consumer aversion strategically to capture market shares from Google. We find that Google has an incentive to collect consumer data and that the presence of DuckDuckGo will moderate the amount. We also find that as consumer aversion to advertisements increases, Google will choose to collect more consumer data as DuckDuckGo’s incentives to respond with investments in privacy awareness are reduced.