Personalization in advertising is a lot older than you may think. Fun fact: The very first personalized ad came from Sears in 1892 when they launched a massive (at least by 1800s standards) direct mail campaign with 8K postcards. Ultimately, they received a whopping 2K new orders–or a 25% conversion rate.
Fast forward many years to the digital advertising age and personalization is a highly sophisticated practice that continues evolving at a rapid pace. And for good reason–80% of consumers are more likely to purchase from a company that provides a tailored experience.
The main challenge marketers face is getting the volume of data to enable a plethora of ad experiences–each tailored to a distinct audience. For years, brands have relied on third-party cookies to track website visitors, enhance the user experience, and collect data. Plus, they grant visibility into user behavior beyond your owned website. But as many know, that time is coming to an end soon.
As we pivot towards a third-party cookieless world, it’s time to hone our focus on alternatives. In doing so, we have to answer the question at the core of this change. What would marketers be using today if third-party cookies had never been an option at all?
Slow your roll. What’s a third-party cookie?
A third-party cookie is a tracking code placed on a web visitor’s device after being created via a website visit. Meaning, when someone visits a site (yours or otherwise) the third-party cookie tracks this information and relays it to the third-party who created the cookie. Typically, this is an advertiser.
Third-party cookie data can help reveal more information about your target audience’s online behaviors like where they visit often, what they buy, their general interests, articles they read, etc. Once that data is collected, advertisers can build audience buckets to organize users in. Thereafter, you can build a retargeting list–so tailored ads are sent to past visitors or even target users who have seen your ad before.
Why must the cookie crumble?
Naturally, advertisers are less than thrilled about the change. But it wasn’t the most surprising development. In fact, Firefox and Safari had already phased out third-party cookies when Google announced the change to Chrome in January 2020 (and subsequently announced an extension to the end of 2023). You may be wondering why there’s so much noise around Chrome compared to other browsers. Significantly, Chrome made up 65.3% of the web browser market in 2021.
Onto the why of it all. If you ask Google, the answer is improving user privacy. Still, many privacy experts have posited that the change actually won’t have a tremendous impact in that regard. So we’ll leave the theorizing to you. Either way, Google is currently working on a new solution called Topics (not to be confused with their previous project, FLoC).
Got it. So what are the third-party cookie alternatives?
With the elimination of third-party cookies, 41% of marketers believe their biggest challenge will be the inability to track the right data. Here’s the thing though–third-party cookies might not be all they’re cracked up to be. In fact, when 2 companies try to match cookie data on the same set of consumers, the accuracy rate is rather low at 40-50%.
Still, marketers need data like plants need water. What options do they have? Or, what would they be doing now without the option for third-party cookies?
First-party cookies/ data tracking
Perhaps you had the data you needed all along. A first-party cookie is a code that is built and stored on your visitor’s computer by default after visiting your site. The main purpose is typically to improve the user experience (remembering passwords, preferences, etc).
With first-party cookies, publishers and advertisers each gather distinct audience and consumer data. That data can be merged when there’s overlap to uncover customer spending habits across both the brand and publisher sites. Ultimately, you can more effectively target ads.
The downside? While these basic analytics can be very useful in building or automating marketing campaigns, you are still confined to the sites affiliated with your domain.
With identity solutions, identifiers such as email addresses, phone numbers, and/or logins are hashed and anonymized in order to track users. When a user visits a site or app, information is collected and sent to an ID provider where a user is paired to an existing ID, or a new one is created.
The biggest challenge advertisers will face with identity solutions is scale, since this requires 1000s of publishers and advertisers to agree to sharing data. Currently, multiple ID solutions (at once) have proven effective in providing the data needed to identify users.
There are plenty of solutions to choose from too, including LiverRamp, TTD Unified 2.0, and OpenAP.
Contextual targeting is the process of serving ads based on webpage triggers, which are typically key words and terms. Since it doesn’t rely on personal data, contextual targeting may use publisher data, including device, time of browsing, etc. And with machine learning (ML), advertisers can pair the right pages and timing for each user.
For instance, imagine a user goes to glossier.com. Similar makeup brands such as Milk Makeup or Undone Beauty know that this context is relevant to help improve the impact of their ads. So they will likely show their ads to the same audiences as Glossier. Still, issues can arise for brands with broader and more varied audiences. Let’s say that Glossier users are also interested in hair tools (which Glossier does not sell). Due to the limitations of contextual advertising, a brand like Sephora, that sells both, might not be able to reach that user.
Data clean rooms
In short, a data clean room is a secure area between advertisers, data aggregators, and publishers where they can consolidate both of their customer data, in a privacy-safe way, and measure the potential effectiveness of their advertising investment. No sensitive information is harmed in the process.
Think of a clean room as Switzerland. A neutral territory to analyze the advertiser’s first- or third-party data against the ad exposure data from disjointed platforms. A clean room provides one place to consolidate measurements across advertising platforms like Instagram, Apple, Google, and more.
A potential downside of clean rooms is the need for market adoption. When leveraging a clean room, you're essentially setting up an entirely new database within someone else's system. This is often a time-consuming and labor-intensive process. Therefore, you ideally need multiple partners leveraging the same clean room partner to benefit from the enhanced security and data matching benefits of the solution. Because if your partners use different clean rooms, you'll need to conduct this process multiple times across clean room partners.
Additionally, as with any data collection process, consumers need to provide clear consent to advertisers before a brand can share any data "clean room or not."
Looking forward: An interoperable approach
Who’s to say you need to choose just one solution? Each advertiser has unique objectives, capabilities, and other factors which will shape how they approach the demise of third-party cookies. Regardless of your needs, now is an ideal time to begin testing and seeing what works—before that late 2023 countdown ends.
As a general rule of thumb, we recommend a diversified approach that combines data with other publishers alongside keeping up on first party data. If all else fails, or you need an extra boost, employ contextual targeting.
Change can be scary, especially when you’ve longed-relied on something. Yet, we don’t think it’s worth the panic. Advertisers across the board are in the same boat, and there are plenty of alternatives to maintain workflows and advertising effectiveness.
Want to learn more about the end of third-party cookies? Check out our identity resolution infographic here.
The video below has some great nuggets too.