The Problems With Behavioral Targeting

From its inception, behavioral targeting revolutionized the online advertising landscape and changed the industry forever. It arose from the need among advertisers to focus their resources on the audiences that are more likely to be interested in their brand. These audiences were to be picked among a large pool of consumers using their online behavior data. On the other hand, behavioral targeting was also meant to improve the user experience overall, with consumers generally finding relevant advertisements less intrusive and annoying than non-targeted ones. So what are the problems with behavioral targeting, exactly?

Why Behavioral Targeting Isn’t All That

Each day, it seems more and more evident that the online advertising industry is looking for avenues to move away from behavioral targeting. Although it is still one of the most common advertising methods, advertisers are actively looking for alternatives to behavioral targeting (such as contextual, semantic, permission-based, and so on).

This is taking place for a number of reasons. First, legislative action in many parts of the world, such as GDPR in the EU, is making it more difficult for marketers to collect sufficient relevant data. Secondly, behavioral targeting seems to have missed the mark on making advertisements “less annoying” for the consumer. And thirdly, when you take a closer look at it, it is simply not as effective as it is lauded to be.

Not Privacy-Friendly

The basic tenet of behavioral targeting is the supposed precise targeting based on users’ online profiles and behaviors. However, this implies access to consumers’ private information that they may or may not be willing to give. This fact flew under the radar of a typical internet user for a long time, giving behavioral targeting the perfect environment to thrive.

However, today’s average internet user is better educated about giving away personal information. They are also more wary of platforms that covertly gather data or sell it to third parties. In fact, according to Twilio Segment’s 2023 report, only around half of consumers believe that brands will keep their personal information private.

Governments around the world are (albeit slowly) following suit and limiting or altering the ways that online platforms can gather personal information. For instance, as per GDPR, personal data can only be processed if at least one of several conditions has been met, such as the subject giving permission, for the purpose of fulfilling a contractual obligation with the subject, to protect the well-being of the subject in question, and more. Needless to say, many platforms have found ways to work around such legislations, such as by making the opt-out process time-consuming and unnecessarily complex or by having all the boxes for data processing consent checked by default.

Many industry experts agree with the general public that behavioral targeting poses a serious data privacy threat. Bennett Cyphers and Adam Schwarz of the Electronic Frontier Foundation state: “Online behavioral targeting is almost single-handedly responsible for the worst privacy problems on the internet today”, highlighting that such data is not only used for advertising purposes, but is also being sold to law enforcement agencies, the military, and hedge funds. 

Not as Effective as It’s Lauded to Be

The main idea behind behavioral targeting is that it allows brands to serve ads to people who are more likely to be interested in them. But does it really do that? Some data suggest that behavioral targeting may not be as effective at profiling audience members as it is believed to be. 

As Kasha Cacy, CMO of Known puts it, “Behavioral data does have some limitations. It can’t always tell you how a consumer feels. What do you do when your target isn’t defined by a behavior, but rather by how they think or what they believe?”

Not to mention that behaviorally targeted ads are often based on blatantly wrong parameters. Device and browser usage are often not reliable indicators of a user’s interests. For instance, a user who searched for and purchased a vacuum cleaner has no use for all the vacuum cleaner ads that are bound to mushroom around their online environment in the following period. 

But it’s not just expert opinions and personal experiences that are making a case against behavioral targeting. There are actual numbers to support these claims. As Jessica Davies of Digiday explains, New York Times International, a major global publisher, ceased all of its open-exchange ad trading and behavioral targeting operations in Europe as a reaction to the GDPR. Instead, the company focused its efforts on contextual and geographical targeting through programmatic guaranteed and PMP deals. As a result, not only did New York Times International not lose any money in the process, but it actually increased its ad revenue.

The Moral Dilemma

Even if behavioral targeting came with a guarantee that it would reach the most relevant audience, it would still be a problematic practice from an ethical point of view. Even with GDPR in place, many websites are still covert about the way in which they collect, process, and profit from user data. Or, in the words of Cyphers and Schwartz of EFF, “this pervasive online behavioral surveillance apparatus turns our lives into open books – every mouse click and screen swipe can be tracked and then disseminated throughout the vast ad tech ecosystem”. 

However, behavioral targeting has ethical issues beyond just data privacy. Some argue that it is a fertile breeding ground for all kinds of discrimination. 

One of the mechanisms behind this system is the process of creating user profiles based on the collected data. These profiles can then be misused to unethically target groups of people, such as in the example of Facebook helping an alleged fraud reach millions of retirees. 

Other examples of discriminatory practices in behavioral targeting include categorization based on gender, race, religion, and more. For instance, in 2019, Facebook (yes, again) was sued by a group of users for allowing real estate agencies to target ads based on a user’s race and nationality (some of which were reported to exclude users in the categories “African Americans” and “Hispanics”), effectively creating a digital redlining phenomenon. 

Third-Party Data Will Eventually Die Out

Lastly, the constant looming of Google’s plan to kill off third-party cookies is bound to harm the behavioral targeting landscape, at least to a degree. Although third-party cookies weren’t designed with advertising in mind, they have proven themselves to be so useful for the ad industry that they have stuck around despite the general awareness among internet users of their potential harm. 

The latest announced date for the third-party cookie phaseout is late 2024. By then, advertisers, brands, and publishers will have to find appropriate alternatives for reaching the right audience. 

Alternatives to Behavioral Targeting

Whether due to the phaseout of third-party cookies or for legal or ethical reasons, the advertising community has been coming up with possible alternatives, both for data collection and for ad targeting. 

Alex Campbell of Vibes highlights the potential of permission-based tracking and zero-party cookies in the post-third-party cookie world. This is a multifold solution among behavioral alternatives. First, it bypasses the privacy issues regarding data collection by asking for clear permission from the user. Secondly, it harnesses consumer loyalty through open and transparent communication. As Campbell explains, users are more likely to put their trust in brands that are transparent about their data collection processes. And third, by giving the users control over which information is shared, they can introduce themselves free of the systemic biases integral to behavioral targeting.

However, contextual targeting still takes the cake as the optimal ad targeting alternative. Not only does it completely do away with reliance on information about the audience, but it might actually yield more relevant results. Put simply, a user who is currently browsing for vacuum cleaners is more likely to be interested in an ad for vacuum cleaners than a user who did the same a week ago (and has been bombarded with vacuum cleaner ads since). 

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* This article was originally published here