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Fragmented AdTech: Measuring Data Without Third-Party Cookies

Dmytro Kustov
1 Oct 2021
6 min
Fragmented AdTech: Measuring Data Without Third-Party Cookies
Fragmented AdTech: Measuring Data Without Third-Party Cookies - photo 1

Many advertisers and providers seem to view the upcoming demise of third-party cookies as heralding an industry-wide apocalypse. But let’s not forget that worldwide AdTech was fragmented even before consumer data privacy laws and cookie blocking arrived on the scene. 

Let’s figure out why AdTech is so fragmented in the first place and how the end of third-party cookies can actually benefit you. Then we’ll look at existing alternatives and upcoming tools that could replace third-party cookies in the near future.

Why is AdTech so fragmented?

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    AdTech fragmentation refers to the separate sales channels, markets, and ecosystems in the digital marketing industry. As markets became flooded with over-complicated tools and ad networks, the industry became even more fragmented.

    The current AdTech landscape is overcrowded with separate ad networks, servers, SSPs, and formats. Organizations like the Interactive Advertising Bureau are trying to standardize the approaches and tools, but these efforts can’t keep up with new tech that emerges almost every day. 

    And it gets worse because AdTech will fragment even more by 2023. Why so?  

    Since 2008, the industry has relied on third-party cookies to cross-match user identities across devices, browsers, and websites. This technology helped measure the effectiveness of ad impressions but raised security and privacy concerns among consumers and regulators.

    To meet customers’ expectations while complying with laws in different territories, Safari blocked third-party cookies by default in 2017, with Firefox following shortly after. Now Google promises to phase out third-party cookies in Chrome in 2023—the date associated with the demise of third-party sources.

    What, though, does this mean for the AdTech sector?

    How fragmented AdTech affects advertisers and publishers

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    Until now, third-party cookies have helped AdTech resolve the scaling problems of digital advertising. Ad networks grouped inventory from advertisers into a single marketplace where ad spaces were sold programmatically or using header bidding services

    Third-party cookies made it possible to identify users across different websites. This allowed DSPs to identify user preferences (based on their browsing behavior, search histories, and past purchases) and target them with tailored ads. Plus, third-party cookies made it possible to measure the impact of these campaigns.

    So, what will change after the ban of third-party cookies comes into force? The key challenges for advertisers and publishers include:

    • Customization. Most companies will resort to contextual ads and won’t be able to track customers outside their platforms.
    • Interoperability. The industry is coming up with alternatives to third-party cookies, many of which have specific standards that are incompatible with one another.
    • Measuring. AdTech will rely on first-party tracking with no way to connect users’ digital footprints across websites. 

    To sum up, the industry will no longer be able to use the traditional approach to customize ads and measure their key performance indicators on the open web. But that doesn’t mean you won’t be able to measure online visibility.

    How to measure user data without third-party cookies

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    Many current AdTech point solutions could end up being offered as freeware services (as Google did with its Analytics tool) because they’ll provide limited metrics from scarce channels.

    So, how will you be able to measure user data in the near future? Thankfully, there are many effective alternatives to third-party data you can use right now (with even more solutions in development). Let’s start with the obvious.

    First-party data

    First-party data (also known as logged-in or authenticated data) provides the most valuable information about your consumers, visitors, and social media users. Brands and publishers can use this data to identify signed-up users across their sites and measure the performance of ad campaigns. 

    In other words, authenticated data solutions allow you to gather firsthand information about the existing audience to increase their engagement. Some larger publishers are already successfully targeting logged-in users with specific ads based on first-party data. 

    This approach can be challenging for smaller companies. Most websites are simply not worth signing into. You have to incentivize users to subscribe and share their data by offering bonuses (such as discounts or special conditions). On top of that, brands with smaller audiences won’t be able to scale logged-in data effectively unless they join forces with other companies.

    Cooperative brand networks

    You can maximize your first-party data gathering by joining brand ad networks (brand cooperatives). Brands in these co-ops can automatically anonymize logged-in data and share it with other companies.

    The result? You can aggregate data across multiple channels and vastly improve your analytics in the process. You’ll also comply with privacy regulations because your first-party data will lack personally identifiable information.

    Vertical ad networks

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      Niche brands and specialized industries will benefit from vertical ad networks. For example, wine businesses can join a wine-specific vertical advertising network to promote their offering to the relevant audience. 

      These networks combine first-party cookies, contextual technology, and analytics tools. We believe that tapping into vertical ad networks can be a very effective strategy to measure user demographics.

      Google’s cohort IDs

      Google is already beta-testing its alternative to third-party cookies—Federated Learning of Cohorts (FLoC). Instead of targeting individual user IDs, the Chrome browser will use browsing behavior to group people into cohorts. 

      According to Google, FLoC provides 95% conversions per dollar spent compared to cookie-based ads. And, in theory, this technology will be able to comply with data privacy regulations.

      ID-based solutions

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      Independent AdTech companies are working on point solutions that allow companies to identify users and track their activities in different environments. These tools will also encrypt all personally identifiable information. 

      The most notable ID technologies include:

      • Unified ID 2.0 by The Trade Desk 
      • Universal ID by ID5
      • BritePool ID
      • Authenticated Traffic Solution (ATS) by LiveRamp

      We expect these solutions to be used under both plug-and-play (will integrate into your tech infrastructure) and fully managed (you rely on ad agencies) models.

      AdTech companies won’t have to shift their practices too much if these cookie solutions gain traction. However, most of these solutions operate in silos, which brings their interoperability into question. 

      These tools can hash (encode) first-party data and turn it into unique identifiers. This way, you can differentiate between users but can’t reveal their personally identifiable data (like emails or IP addresses). Still, this approach has already raised some privacy concerns, which is one of the primary reasons why AdTech is so fragmented.

      CTV platforms

      Connected TVs (CTVs) could be a new focus for ad measurement. According to the 2020 State of Connected TV Report, CTVs are already overtaking desktop devices in terms of ad impressions, and their number will grow by up to 82% by 2023.

      With SSAI (Server-Side Ad Insertion), advertisers and publishers can seamlessly weave their ads into the video stream. And the best thing is that these platforms don’t rely on third-party cookies (and never did). Instead, they use device identifiers and soft data to track user behavior.

      On the downside, CTVs lack parameters for evaluating ad KPIs. Also, scammers often use this technology to create artificial traffic. 

      Panel-based browser attribution

      Panel-based attribution may make a return in the coming years. This model tracks a tiny percent of logged-in users and scales up the measurements. In other words, over 99% of your data will be based on assumptions.

      This approach can work for smaller brands, but it’s highly inaccurate for national or global campaigns due to the small sample sizes. However, you can fill in the gaps in the data with machine learning (ML), artificial intelligence (AI), and predictive analytics. Some businesses are already using AI to measure and target unauthenticated visitors based on logged-in users.

      To sum up

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      It should now be apparent why AdTech is so fragmented. Also, you should now understand that the industry can survive without third-party cookies. Most companies will turn to vertical ad networks and upcoming ID solutions, which can be just as effective at measuring ad impressions.

      Advertisers can also focus on building first-party data infrastructures and join brand co-ops to measure their audiences across multiple channels. Maybe this will become an opportunity to finally capture value from Google’s and Facebook’s monopolistic walled gardens.

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