Behavioral Advertising and Consumer Welfare: An Empirical Investigation

What is it about?

The value that consumers derive from behavioral advertising has been more often posited than empirically demonstrated. The majority of empirical work on behavioral advertising has focused on estimating the effectiveness of behaviorally targeted ads, measured in terms of click or conversion rates. We present the results of two online within-subject experiments (Study 1 and Study 2) that, instead, employ a counterfactual approach, designed to assess comparatively some of the consumer welfare implications of behaviorally targeted advertising. Participants are presented with alternative product offers: products advertised in ads displayed to them on websites that commonly show behaviorally targeted ads (ad condition); competing products from the organic results of online searches (search condition); and random products (random condition). The alternatives are compared along a variety of metrics, including objective measures (such as product price and vendor quality) and participants’ self-reports (such as purchase intention and perceived product relevance). In Study 1 (n = 489) we find, first, that both ads and organic search results within our sample of participants are dominated by a minority of vendors; however, ads are more likely to present participants with less popular (and therefore lesser known) vendors. Second, we find that purchase intentions are higher in the ad and the search conditions than in the random condition; the effect is driven by higher product relevance in the ad and search conditions; however, in absolute terms, product relevance is low, even in the ad condition. Third, we find that ads are more likely to be associated with lower quality vendors, and higher prices (for identical products), compared to competing alternatives found in search results. Study 2 (n = 493) replicates Study 1 results. In addition, Study 2 finds that higher purchase intentions and higher relevance in the ad condition are driven by participants having previously searched for the advertised product. Furthermore, we use a latent utility model to estimate differences in consumer surplus (a commonly used measure of consumer welfare) across conditions. In our sample of participants, the random condition is associated with the lowest surplus. After accounting for differences in vendor quality, the search condition is associated with slightly higher surplus relative to the ad condition.

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