Discovering the Ad ID of the Future

As an independent advertising technology consultant, Ivan Guzenko provides professional advice to the CEO and senior management of the company. SmartyAds Inc.

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Remember the frustration of standing in a long line at an amusement park only to find out the ride you were waiting for is temporarily closed? That feeling is making its way through the ad tech world as the cookie shutdown has been pushed back to 2025—an extreme but thrilling “ride” the industry has been gearing up for since 2020.

In a twist, Privacy Sandbox has also been stuck in limbo. Earlier this year, after the UK Competition and Markets Authority raised concerns about Privacy Sandbox and the IAB revealed some critical issues in match-gap analysis, the market was slow to adopt new targeting solutions, which is why 36% of EU brands are still not cookie-free. Despite this, 40% of EU marketers are optimistic about the future as they adopt alternative mechanisms such as probabilistic graphs.

The next most popular identifier: who will take the title

There’s bad news and good news for Privacy Sandbox, a major player in the cookieless identifier race. First the bad news: To add to the points above, remember that transparency, usability, and potential unfair competition are issues critics were buzzing about in early 2024.

The good news is that major players like Criteo and RTB House are investing a lot of effort, time, and budget into testing and improving the Sandbox and some of its features—including improving the integrity of PAAPI auctions. Despite all the implications, the Sandbox boasts an impressive Net Promoter Score (NPS) of 81.5, reflecting growing trust and support from the market (p. 25).

Now, a few points about the alternatives: This year, marketers have seen an increase in trust and confidence in using contextual signals to reach their audiences (NPS 81.5). Contextual and location-based targeting at the page level emerged as the second most popular method (NPS 77.5).

With connected TV now the new darling of EU marketers, CTV identifiers are the most popular here, with 43% of surveyed marketers using them as their primary targeting source (p. 23). Probabilistic charts were chosen as the second most popular identifier, with 40% of respondents preferring them. With 4 in 10 ad campaigns set to launch on CTV in the next 24 months, it’s clear that this growth will extend to all types of businesses and markets.

From determinism to probabilism: the need for a paradigm shift

As users now migrate across their CTV devices, new mechanisms are needed to interpret important touchpoints along the customer journey, and probabilistic graphs can serve as that important link. For centuries, cookies have provided advertisers with deterministic tracking mechanisms.

In the post-cookie era, they need to focus on probabilistic graphs that aggregate and analyze disparate data—such as device identifiers, IP addresses, and behavioral signals—to create comprehensive, targetable audience profiles.

With this approach, advertisers can create a unified image of the message for their audience and, based on this, adjust the message strategy to ensure better personalization and a more engaging user experience, which will translate into better brand recall and higher conversion rates.

Boon or Curse: What Probabilistic Graphs Can Do for Advertising Tech

Which will you choose: the convenience and scale of programmatic CTV platforms, as is the case for two-thirds of media buyers and agencies, or building relationships with CTV publishers, like most independent marketers who also prefer private marketplace deals?

Regardless of your choice, it should come as no surprise that RTB and direct trading, as well as PMP inventory purchasing, are now available on software platforms that are increasingly equipped with first-party data and alternative identifiers such as probabilistic charts.

So what makes probabilistic charts so groundbreaking? Here’s how they can be used in both programmatic advertising and direct transactions:

• Segmentation: As mentioned earlier, probabilistic graphs aggregate and analyze data points across the entire customer journey, including behavioral signals. This allows for more refined and precise cookie-free targeting strategies.

• Omni-channel experience: Probabilistic graphs can attribute different devices to a single user. This gives advertisers a powerful identification tool, allowing them to create effective creative and multi-channel user experiences tailored to each environment and device type.

• Equipping platforms with cookie-free targeting functionality: Probabilistic graphs can be one alternative to cookies for targeting that allows ad tech providers to diversify their offerings with robust targeting mechanisms that comply with numerous international privacy frameworks.

• Improve attribution and measurement: Because probabilistic graphs connect different data points across devices, platforms can leverage them to measure campaign effectiveness. In particular, this can be valuable for both direct and programmatic RTB campaigns in areas where attribution and measurement are suppressed by privacy-driven transformations.

Navigating Big Change: When and How Businesses Should Adapt

Implementing new measurement and attribution methods is like learning to drive a car with a whole new set of controls. It will require companies to rethink their measurement approach. Building systems that protect user privacy while delivering actionable insights is not just about having the right technology.

It’s great that Google is giving us plenty of time to implement a completed version of Privacy Sandbox, but clear communication about progress and industry collaboration will be key to ensuring this initiative delivers benefits to all involved.

It is important to prevent delays in implementing new technologies and proving their true value in the market. For 58% of companies (p. 28), the biggest obstacle is the cost of changing the methodology and the lack of investment in this area.

That’s why collaboration across the industry is so important. Now we need to get everyone on the same page to chip in and address the financial burdens on businesses by creating a framework that makes it easier to test and adopt new methodologies.

Summary

Marketers are turning to probabilistic graphs and similar solutions like explorers charting new territory in a cookie-free world. These explorers need the chance and support to move from their old methods to innovative alternatives that can open up new possibilities for platforms and market participants.

We need industry teamwork, financial support for small and medium-sized businesses, and openness to new ideas. This collaboration will pave the way for a privacy-friendly and sustainable future where everyone can stay ahead of the curve.

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