And yet there’s a successional gap. Nobody seems to know what to do next. The same survey reports that 41% of marketers aren’t familiar with targeting methods other than third-party cookies or IDs. “I think everyone’s talking about it but not many people are actually doing a lot of preparation yet,” says one anonymous advertising executive quoted in the study. “I think it’s just going to catch a lot of people [off guard].”
Marketers had better figure out a plan fast, because Google has announced that, come January 2024, marketers will no longer be able to track browsing data via third-party cookies on the browser Chrome, by far the world’s most popular consumer browser option, with almost two-thirds of the market share. The Firefox and Safari browsers have already banned third-party cookies. The upshot is that marketers will lose direct visibility into user behavior beyond a brand’s website.
So let’s discuss some alternative tactics marketers can use to effectively target users when third-party cookies are no longer an option.
Instead of relying on individual user data, marketers can focus on contextually relevant advertising. “Context” in this case is the content of web pages where you’re placing ads, in addition to the user’s location, device type and time of day. In other words, you serve up ads that are aligned with what’s on the page and the environmental context of the user. By fully understanding the topic or theme of the content, marketers can target their ads to reach the right audience without relying on cookies.
For example, if you work for a stationery company, you might bid to place a banner ad on a page with a video about creative bullet journal ideas. By recognizing the content’s theme, you can target users who are interested in stationery and likely to engage with your ad. You could also target early risers, hypothesizing that early birds are more into extreme journaling.
Contextual advertising is effective because it lets you align your ads with the user’s current interests or needs. By displaying relevant ads within the context of the user’s browsing experience, you’ll have a higher likelihood of capturing their attention – and generating the desired outcome.
Wait, weren’t we leaving cookies behind? The situation is more nuanced than implied by my headline here. The year 2024 is not the end of all marketing cookies; first-party cookies are directly stored on the website that a consumer visits, and they aren’t going anywhere.
As you may know, third-party data refers to user information collected by external entities across multiple websites, while first-party data is data collected directly from users on a company’s own website or owned channels. When you browse for pillows on Amazon, and then you’re perpetually haunted by advertisements for pillows everywhere you go online, that’s a third-party cookie that is following you around. By contrast, when Amazon saves your login info for you, and makes recommendations based on your past purchases, that’s a first-party cookie.
Marketers can leverage their own first-party data to gain insights about their audience. You can collect first-party data directly from users through their interactions with your brand’s website, app, or other owned channels. For example, you can offer users the option to create an account or subscribe to receive special offers and discounts, which allows you to collect valuable information such as their preferences, purchase history or demographic data.
First-party data is good to cultivate even if third-party cookies were sticking around. As far back as 2012, consumers reported being uncomfortable with being “stalked” by targeted cookies online. Plus, the quality of third-party data can be unreliable. According to machine learning scientist Jiaxi Liang, “data providers aren’t always as concerned with the accuracy of the data they’re collecting, opting to instead focus on building massive datasets that they can sell to businesses.” First-party data, because it comes from the horse’s mouth, is much more effective for targeted marketing.
Finally, let’s talk about AI. I’m not talking about the hyper-buzzy ChatGPT and its ilk. I’m talking about the machine learning algorithms that analyze large data sets and identify patterns and correlations that were previously reliant on cookies. Machine learning algorithms can mix contextual data with first-party data to generate key insights and predictions about user behavior.
How does it do that? The simplified version is that marketers feed algorithms data through some kind of data management platform, like Adobe Audience Manager. A data scientist will train the algorithm to recognize patterns and relationships in the data through a training process. Based on the identified patterns, the algorithm generates insights and predictions about user behavior. Marketers use these insights to make data-driven decisions, optimize ad targeting and personalize experiences.
For example, by examining past user behavior, the algorithm may learn that users who have previously shown interest in beer-related content, say by signing up for your beer newsletter, are more likely to engage with ads featuring sports products or events. With this insight, marketers can then tailor their ad campaigns to target users reading a Top Ten Beers listicle with sports-related ads.
Although these new targeting methods are more reliable than third-party data, it’s important to address ongoing privacy and consent concerns. It’s always a good practice to make sure you inform your customers of exactly how you’re using their data, why you’re using it and how they can opt out if they choose. In some states (e.g. California) and countries (e.g. the EU), there are regulations requiring companies to do this. In other places, it’s just good practice, and a good habit to get into not only in case these regulations proliferate but in order to increase overall trust and transparency with consumers.
Data quality should also remain a priority. AI may be useful, but its predictions are only as good as its data set. Plus, while contextual data and first-party data are more reliable than third-party data, they can still become outdated or contain errors. Make it a regular practice to run quality control on all the data you use to target customers.
As long as you stay up to date on data cleaning, and ensure you keep your customers in the loop, you can navigate the cookie-free marketing landscape successfully while addressing privacy concerns and maintaining data quality.
The death of third-party targeting isn’t the death of marketing, full stop. In fact, as I mentioned earlier in the article, I believe that the new methods of targeting customers can be even more valuable, more relevant and more effective than retargeting someone on the internet with ads for the last thing they Googled.
Contextual advertising, first-party data and machine learning algorithms are just three good places to start thinking about cookie-free marketing. In the end, the death of third-party targeting presents an opportunity for marketers to evolve and embrace new and improved methods of reaching their target audience.
Lisa Abousaleh is the Co-CEO and Founder of Neutronian, a SaaS company that provides data quality and compliance verification services. Neutronian also developed the NQI Certification, a comprehensive data quality, compliance and transparency certification, to bring more trust and transparency to the marketing industry.