Cookies (especially third-party cookies) have long been the backbone of digital marketing efforts: behavioral targeting. However, the end of the cookie is near—and so, too, may be the end of behavioral targeting’s reign as digital advertising’s go-to for reaching target audiences.
As more people and their elected representatives voice data privacy concerns over who does what with their personal data, brands and advertisers should anticipate more privacy regulations (like the GDPR) to come sooner rather than later. And, with a cookieless future on the horizon, each brand must rethink its marketing strategy and how its digital ads reach potential customers. As behavioral advertising goes the way of the cookie, brands would be wise to begin supplanting behavioral ads with contextual ads.
Where behavioral targeting reaches wide audiences, contextual targeting capitalizes on the rise of CTV, ensuring they meet audiences where they are, not where they were a few screens ago.
Contextual targeting is a type of programmatic advertising based on a website’s content and relies on the reader’s implied intent or interest. Based on these factors, an automated system selects appropriate ads to show the user. It’s an effective targeting method that works on:
Essentially, contextual targeting shows the reader relevant ads based on real-time actions and interests; if a reader sees a targeted ad for fly fishing gear while browsing an outdoor tour company site, they’re more likely to click the ad than if they were shown the ad while browsing a formal clothing site.
Succinctly, relevant content is key.
Contextual advertising is effective because it relies on website content the user sees in real-time, coupled with a brand’s identified keyword analysis instead of browsing history and behavior. Informed, real-time contextual ad placement gives readers more reason to engage with brands’ ads based on what they’re doing right then—not based on user data from six sites ago.
To reach relevant audiences, contextual targeting relies on a demand-side platform (DSP) for ad placement. DSPs base that ad placement on brands’ contextual targeting parameters, like keyword lists, topics, location, language, and user demographics. Advertisers use DSPs to buy ads from a marketplace that contains publishers’ ad inventory. This enables brands to manage ads over several real-time bidding networks, ensuring brands reach relevant audiences wherever they are at that moment; brands don’t waste precious ad spend trying to reach users based on browsing history or past behavior.
Once a brand has chosen its targeting parameters, the DSP analyzes all pages in its network to reveal only the most relevant content to meet the brand’s goal of showing ads that users actually want to see. The DSP scours its ad server by evaluating relevance based on keywords, text, language, and page and link structure, ensuring it leaves no stone unturned, so to speak.
As soon as the DSP finds relevant content, brands’ ads enter a real-time auction; the winner’s ads get placed in front of relevant users. Remember the fly fishing ad? It’s now in front of a user looking to book a fly fishing trip through a local guide’s website.
But the process doesn’t stop there. Brands can tweak and/or relaunch their ad campaigns based on these ads’ performance. The more concise a brand’s ads, the better chance they have of finding users who will resonate with them. It’s an especially appealing targeting method for ecommerce sites; contextual ads increase the viewer’s purchase intent by 63%.
It’s worth repeating: the end of the cookie is here, and behavioral targeting is barely clinging on for dear life. While contextual targeting meets users where they are based on niche parameters, behavioral targeting shows ads to users based on their past behavior, user behavior that may no longer be relevant. For example, if the guy viewing fly fishing gear leaves all associated sites to go about his day, logs back on to check the price of a suit on the formal clothing website, and sees a fly fishing gear ad, he may not be as likely to click the ad in that context.
Because behavioral targeting relies on retargeting based on previous online behavior, this audience targeting method may miss users when they’re most likely to engage with an ad, making it an increasingly poor advertising strategy—even with sound messaging when placed in front of the wrong audience. At the very least, it can create a poor user experience if a brand’s ad gets placed next to an unflattering or inappropriate piece of content, simply because of poor audience targeting work.
In short, behavioral targeting is on the way out, and it’s not doing brands any favors in its waning years.
Contextual targeting cuts costs for brands in a few ways. Not only is it a more cost-effective method of paying for ads, but it can increase a brand’s ROI by up to 30%. That’s because contextual advertising shines where behavioral advertising fails: audiences who see relevant ads are more likely to engage with them, meaning a better chance of conversion. Brands spend their dollars only on promising, high-value impressions, rather than going for a broader, bigger audience.
Aside from immediate cost-effectiveness, brands must consider reputation costs. For example, if a brand that employs a behavioral targeting strategy doesn’t set safeguards against sites with which it doesn’t want to be associated, it runs the risk of an ad placement next to unrelated or even offensive, violent content. Once that happens, it can damage a brand’s reputation—and its bottom line probably won’t escape the fallout.
Reputation matters, and contextual targeting helps brands protect their reputations.
Finally, brands must consider late-to-the-party costs. Brands constantly compete for users’ attention. Now that more and more brands are pivoting to contextual advertising, those that don’t are bound to scramble to catch up once they finally abandon behavioral ads and cookies; first-party data can only get them so far. Now is the time to plan for a cookieless future.
Brands are demanding more transparency in the CTV landscape, as many don’t know which channel, show, or program their ads will show on, let alone how to analyze their campaign successes or failures. This (understandably) makes marketers nervous. Peer39’s contextual connected TV solutions help marketers navigate CTV ads by providing in-depth, show-level transparency reports that include:
Brands can also rest easy knowing that their contextual ads won’t show next to offensive or violent content; brands can prevent placement by setting negative keywords and other unsavory channels or placements. This protects both budgets and reputations.
Brands have a lot to consider when creating ads for various audience segments, including when and where those audiences see those ads. If they see them in the wrong place, that’s potentially money wasted and a potential customer lost. Contextual advertising helps brands optimize their ad spend by helping them reach audiences in the most appropriate and relevant context.
Peer39’s machine learning-enabled advertising solution gives brands lucid insight into their ad campaigns across the contextual data marketplace. With optimized data to determine the right audience fit on the most appropriate channels, brands can reach a more targeted audience who’s eager to see their ads in the context they were meant to be seen, meaning better performance, less risk, and higher ROI.
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