Behavioral Advertising, Which Encourages Extensive Data Collection, Is One of the Most Dominant Online Business Models

Behavioral advertising is one of the most dominant online business models, and it has enabled a new mode of advertising that capitalizes on data to target users in unprecedented ways. As discussed by Maréchal in her opening remarks, behavioral advertising emerged in the late 1990s, when companies sought to monetize their products and services through what has since become known as surveillance capitalism.¹ As Google became an increasingly popular search engine, it began tracking users’ online activities by collecting data on what they were typing into the search field, what they clicked on before and after searching for different terms, how much time they spent visiting the pages they clicked on, and more. After decades of accruing data, Google has leveraged its data trove and built a sophisticated behavioral advertising apparatus that predicts user behavior and identifies what ads individuals are most likely to click on.

Behavioral advertising spread throughout Silicon Valley and beyond, with far-reaching implications outside the tech sector. Namely, it has disrupted journalism by taking away critical revenue. As Maréchal has written, behavioral advertising

stole journalism's lunch money and used it to sustain platforms whose driving logic isn't to educate, to inform, or to hold the powerful to account, but to keep people engaged. This logic of engagement is motivated by the twin needs to collect more data and show more ads, and manifests itself in algorithms that value popularity over quality.²

To offset this loss of revenue, some news outlets are implementing behavioral advertising on their own sites. The New York Times, ESPN, and USA Today now deliver targeted ads based on users’ moods.³ The Washington Post developed an ad targeting tool that collects user data, and then uses machine learning to “match that data to its existing audience data pools, which it has accumulated over the last four years, to create assumptions on what that news user’s consumption intent will be.”⁴

Behavioral advertising does provide some benefits. As Maréchal explained, to most observers, the business model may seem like a win-win for companies and consumers. Behavioral advertising allows consumers to access online services, typically without paying a monetary fee. In exchange, companies gain a steady revenue stream through automated advertising exchanges, allowing them to focus on developing new products and services. Advertisers benefit from increased efficiency and innovation that enables them to optimize their ad investment strategy. Advertising networks, in turn, are able to charge more for each ad placement. Consumers also benefit from the free flow of information and potentially from efficiency gains, as they are in theory more likely to see relevant ads; they may even accept the associated trade-off in privacy.⁵

Despite its potential benefits, the behavioral advertising business model encourages extensive and intrusive data collection that threatens consumer privacy. Behavioral advertising is driven by clicks and visibility—companies want more people to click and visit certain pages, and the data informs which pages ads are placed on to drive these clicks. Under this business model, there is a clear competitive advantage to having more data. Companies have incentives to collect data, even if they do not need it, in the hopes that it will be useful someday. This practice has led to serious privacy harms.