A key advantage of online advertising over offline is that online advertising can, with sufficient data, be far more accurately targeted than traditional advertising. But how much data is enough? The empirical literature tends to suggest that there are indeed economies of scale in using data for market targeting, but that these benefits are subject to diminishing returns in a static perspective. Is there a plateau, and is it perhaps very large? It is clear that a certain amount of data is necessary to identify meaningful consumer segments and to offer targeted advertising space as part of an advertising campaign; however, a simple correlation between the volume of data gathered by an advertiser and the return on investment of an advertising campaign neglects the complexity of advertising effectiveness. We provide a general assessment of key elements of the literature on economies of scale in the use of data for online advertising, and then seek to link these to the general literature on market targeting in order to provide insights as to the factors that limit effectiveness in using big data for market targeting.
