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Is behavioral advertising good for consumers?

April 26, 2023 | By Rande Price, Research VP – DCN

Most of today’s digital display advertising is sold programmatically. The process is automated from buying to displaying ads and determining which ads are shown to which users. Programmatic advertising uses behavioral ad targeting and relies on extensive online consumer tracking, which raises important privacy concerns.

The benefits are often the counterargument to privacy – asserting the strong economic value consumers derive from targeted ads. But is this really the case for consumers? Do the purported positives – such as oft-touted “better effectiveness” and “ad relevance” – outweigh or offset the impact on consumer welfare?  Further, how is the product’s quality viewed in targeted ads compared to other vendors, and how do the prices compare?

New research, Behavioral advertising, and consumer welfare: An empirical investigation from Eduardo Abraham Schnadower Mustri, Idris Adjerid, and Alessandro Acquisti, answers these questions. The findings show little consumer benefit in seeing targeted ads. In fact, respondents are less aware of vendors displayed and perceive products of lower quality, and at a higher price.

Study details

The research encompasses two studies. Study 1 included 489 participants across two phases. Phase One asked participants to browse randomly across selected websites using a Chrome browser on their computers. If they clicked on an ad, URL of the ad was captured. The research team then used automated scripts and the Google search engine to find competitive products of the advertised brands. They collected several pieces of information for the competitive analysis; landing pages, the product image, price, description, brand, and name of the website that sells the product. 

Approximately one week later, respondents return for Phase 2.  The researchers show nine product photos randomly to participants.

Respondents assessed all nine products:

  • three products from the ads they viewed (ad condition),
  • three competitive products from the organic search results (search condition), and
  • three randomly selected products from ads served to other participants in the study (random condition).

Study 1 included objective metrics in the analysis, like price. The study also included self-reported metrics such as participants’ assessments of purchase intention, product quality, price fairness, relevance, and novelty of product type, brand, and vendor. This design captured participants’ perceptions and purchase intentions independent of their vendors’ perceptions.

The second study replicates the first. However, it includes third-party objective data vendor rankings from the Better Business Bureau and SiteJabber. The researchers share the vendor ratings with the respondents before asking about their purchase intent.


The research shows that participants’ intention to purchase products in targeted display advertisements is low but still higher than for random products. Notably, 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.

The findings also state that, on average, products in targeted display advertisements are only somewhat relevant to respondents. However, while participants appear to benefit from the pricing of targeted products, search results can offer better prices and higher-rated vendors.

The researchers only find one major difference in the direction of the results between Study 1 and Study 2.  Study 1, without vendor ratings, shows significantly lower purchase intention. Study 2, including vendor ratings, shows a higher purchase intention for higher-rated vendors. Therefore, vendor quality is a relevant factor in consumers’ purchase decisions. 

The research results offer insight into understanding the complexities of measuring the impact of targeted ads on consumer welfare. These two studies take a new route and look beyond ad effectiveness and click-through. Using objective and self-reported metrics across three conditions – ads, search, and random, results in low awareness, low-quality, and high-priced vendors. This new empirical study further questions the benefits of behaviorally targeted advertising.  

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