A Model of Multi-dimensional Targeting

Abstract

The advancements in targeting technology have allowed firms to engage in more precise targeting based on several distinct aspects of customer preferences. Exposed to more targeted ads, consumers are becoming increasingly aware of being targeted and respond accordingly. In this paper, we provide a theoretical analysis of multi-dimensional targeting in which consumers are aware that ads are targeted and, therefore, draw inferences about their expected utility from the advertised product based on whether or not they are targeted. By comparing single-dimensional and multi-dimensional targeting, we show that the firm can be worse off under multi-dimensional targeting. When this result holds, the firm may want to adopt a single-dimensional targeting strategy. However, we show that the firm cannot credibly commit to such a strategy once given access to multiple dimensions of customer data. We further find that the firm's commitment problem for how to utilize customer data for targeting can be mitigated by a higher advertising cost, and thus the firm's profit can counter-intuitively increase in the advertising cost. We also show that the firm can use pricing as a commitment device and thus recover some of, but not entirely offset, the pitfalls of multi-dimensional targeting. We provide implications of our results to the recently observed practice of more transparency in online targeted advertising.