The ability to make accurate predictions relating to consumer preferences is a key factor of a digital firm’s success. Examples include targeted advertisements and, more broadly, business models relying on capturing consumers’ attention. The prediction technologies used to learn consumer preferences rely on consumer generated data. Despite the importance of data-driven technologies, there is a lack of knowledge about the precise role that data-scale plays for prediction accuracy. From a policy perspective, a better understanding about the role of data is needed to assess the risks that “big data” might pose for competition. This article highlights potential complementarities in algorithmic learning, which suggest data-scale advantages might be substantial. We analyze our hypothesis using search engine data from Yahoo! and provide evidence consistent with locally increasing returns to scale. The ability to make accurate predictions relating to consumer preferences is a key factor of a digital firm’s success. Examples include targeted advertisements and, more broadly, business models relying on capturing consumers’ attention. The prediction technologies used to learn consumer preferences rely on consumer generated data. Despite the importance of data-driven technologies, there is a lack of knowledge about the precise role that data-scale plays for prediction accuracy. From a policy perspective, a better understanding about the role of data is needed to assess the risks that “big data” might pose for competition. This article highlights potential complementarities in algorithmic learning, which suggest data-scale advantages might be substantial. We analyze our hypothesis using search engine data from Yahoo! and provide evidence consistent with locally increasing returns to scale..
This is the sixth in a series of papers prepared by a collection of economists and policy experts in the United States, the UK, and the European Union who have studied, and are committed to the improvement of, competition in digital markets. Previous papers addressed consumer protection in online markets, regulating the market for general search services, the concepts of “fairness” and “contestability” as used in the Digital Markets Act, the use of “equitable interoperability” as a “super tool” to restore and encourage competition in online markets, and coherence between US and European approaches to digital regulation.