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Real solutions for cookieless targeting

Targeting will be much harder for brands as cookies start to diminish. However, as the industry moves forward, a few targeting options stand out as promising alternatives, writes Eyeota’s Anand Das.

5 min read

Digital Technology

Real solutions for cookieless targeting

Rudy and Peter Skitterians / Pixabay

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Targeting will be much harder for brands as third-party cookies begin to wane. Advertisers will have to start looking to publishers, first-party data providers and technologies like machine learning to build robust new solutions.

In this new era of digital marketing and advertising, publishers get to take back some control as they hold the keys to their user data. Publishers know their site visitors, especially those who frequent their content. However, there will be new challenges ahead, particularly for smaller publishers who may have deep, niche audiences, but not the reach and scale of their larger peers.

At the same time, new technologies are emerging and older solutions are taking on a new sheen. Even as big players in ad tech are developing new ways to identify and learn more about consumer audiences, older techniques like contextual targeting are taking their moment in the spotlight.

Contextual targeting

Before the industry embraced audience targeting, contextual was our most relied-upon method for reaching customers. Context always seemed like a dependable proxy for behavior. If your brand is known for running shoes and apparel, make sure your ads surface in an article about running. If you sell high-end cooking and bakeware, advertise against content that features recipes or cooking tips.

However, there’s a reason that cookies ultimately outshone contextual targeting. Marketers are able to tell so much more about the buyer and where they are in their journey with the information tied to a cookie. Contextual simply cannot provide the same level of insight.

We cannot reliably infer that a customer is actually ready to buy sneakers because they’re reading about running – they may be a runner and have several pairs already. They may be researching on behalf of a friend or partner. They may have only briefly skimmed the page, lingering for just a moment in route to another online destination. Without cookies, it’s hard to know for certain.

First-party data

For larger publishers, first-party data sources will be the silver bullet. If we can no longer use cookies to identify and track users, the IAB suggests that email addresses or mobile numbers will be the next best thing. This is great news for websites that are either large enough to request a login for access to content or support newsletters and frequent communication via email or other mechanics – think sites like or – as well as large networks of sites.

When users enter, publishers can easily obtain consent and track user behavior for as long as they remain logged into the site. The benefit is enormous for Google, Facebook, NYT, ESPN, Time Inc. and other large publisher networks and social media platforms.

For smaller sites, the benefit is harder to realize, but not impossible. These sites may have loyal users who visit often and consume a lot of content. Their interests may be niche and desirable to brands. However, they may not have the troves of data, the scale or the reach of larger brands, and may, therefore, have to join a group/consortium – or form their own – to stay profitable.

For many publishers, particularly those who don’t rely on registered users, the best option will be to find a first-party data partner. Matching your own audience data with opt-in, first-party data from a partner, and from brand advertisers with registered users will create a clean and reliable database – but it will require a lot of customer data and machine learning to build models for matching profiles, manage accuracy for audience extension, look-alikes, to make it work.

The more data, the more effective artificial intelligence and machine learning will be in ensuring unique and useful data. Taking this approach will eliminate duplication by looking at behavior, IP addresses and mobile IDs and making sure similar profiles are assigned to the right users.

This will also make certain everyone is assigning the same descriptions to different profiles – in other words, your description of a “running enthusiast” and your advertisers’ will be the same. There are several tech companies looking at new ways to identify and follow prospects, including using mobile IDs and hashed email addresses as a new industry standard.

Meanwhile, all of these new innovations present privacy concerns, and the W3C has been endeavoring to address those. Google’s TURTLEDOVE represents a new privacy framework wherein the intelligence of RTB auctions occurs within the browser, rather than on servers run by supply-side platforms, exchanges or publishers. Criteo has introduced another technology, called SPARROW, that builds on Google’s proposal – but all of these are still in the discussion stages as the industry decides where to go next.

Life without cookies will be challenging, but publishers and marketers have survived so many other industry upheavals, we can be confident they’ll power through this one, as well. Necessity, after all, is the mother of invention, and our industry is certainly known for its innovation and inventiveness. The death of the cookies is likely to result in the rise of something even more effective, more respectful of the user and more beneficial to the entire ecosystem.


Anand Das is chief technology officer at Eyeota. Before joining Eyeota, Anand co-founded PubMatic in 2006, and in his role as CTO at PubMatic, he was responsible for establishing the company’s technical vision and positioning PubMatic for future growth. Anand has seven patents to his name in systems software, storage software, advertising and application software. He also served on the IAB Tech Lab board of directors from 2015 to 2018 and is on the board of TruckX and an advisor to Lemma Technologies.