How the Cookieless Shift Reshapes the Advertising Industry

The advertising industry is being reshaped by a convergence of necessity, curiosity and opportunity, driven by consumer expectations for more privacy and advancements in technology.  

A new generation of performance advertising is emerging. Currently, 86% of users state that privacy is a high priority, and this number continues to grow. Mozilla and Apple have already responded to this demand by blocking third-party cookies completely, and now Chrome—the browser with the highest market share—is poised to dramatically increase the fraction of users who won’t allow third-party cookies to be set.

This growing demand for privacy, combined with customer expectations for personalized interactions presents a challenge and opportunity for brands, requiring innovative solutions and a shift in thinking.

Necessity - Evolving towards first-party solutions

Despite Google’s recent pivot to give users control over third-party cookies, the privacy revolution shows no signs of slowing down. The recent Google announcement, introducing new features and industry-requested improvements to Privacy Sandbox—a strong replacement for the existing technologies—reaffirms it. We expect the majority of users to opt out of third-party cookies when given the option, just as they did with Apple’s App Tracking Transparency when it was first introduced. 

The need to compensate for anticipated signal loss pushed the whole industry to evolve. Ad tech firms pioneered first-party solutions designed for precision bidding and personalized offers, now fully implemented into the Privacy Sandbox.  

In turn, the Sandbox now stands as a single, most promising and durable way to deliver first-party advertising to users without third-party cookies. The quality and accuracy of first-party signals have taken centre stage, and the most advanced deep learning algorithms powering digital campaigns gained even more edge as they excel with chaotic data. 

Addressing all audiences, regardless of available signals, has become a priority for brands. The mid-term future will showcase next-generation solutions coexisting with traditional systems.

Curiosity - Enhancing contextual targeting

With the industry shifting from an abundance of user-specific signals to limited user-level data, marketers are re-embracing an old friend: contextual targeting. This approach had long fallen out of favor, unable to compete with solutions leveraging rich, freely accessible user data. Yet, the classic keyword-based contextual targeting is simply underpowered and can’t serve as a viable replacement for most marketing use cases. 

Traditional contextual targeting relies on human-generated keyword lists and struggles to differentiate between pre-purchase and post-purchase contexts. Even machine learning approaches are fooled rather easily: consider the article about the "blind Venetian." Would ads for window treatments really excel there? What marketers need is technology that fully understands the meaning and context of each specific page on a web publisher’s site.

Marketers are curious whether contextual targeting could be improved to where it can serve as a viable replacement for some cookie-based technology. This demand from marketers–along with the explosion of generative AI technology, such as Large Language Models (LLMs), has led to the development of IntentGPT—the next generation of contextual targeting. 

Unlike conventional methods, IntentGPT understands the full context of a publisher’s site, allowing for precise targeting. By analyzing the semantic meaning of each page and aligning it with a brand’s conversion goals, IntentGPT provides additional signals to Deep Learning algorithms, enhancing outcomes across both upper-funnel and lower-funnel campaigns. 

Opportunity - Regaining control through measurement

The forced transition to Google Analytics 4 (GA4) has transformed the measurement paradigm of the digital landscape. While GA4 was designed to address the decline of user-level signals, its complexity has made it challenging for marketers to take full advantage of its robust feature set. 

As a reaction to GA4, many marketers have seized the opportunity to upgrade their approach to measurement, moving beyond their reliance on user-level data and leveraging GA4 alternatives,  such as media mix modeling and incrementality testing. 

Media mix modeling evaluates the effectiveness of various channels by linking changes in key outcomes to changes in marketing spend. Incrementality Testing—often conducted by brands' current partners—provides insights into the true impact of a specific ad-tech vendor’s marketing. 

Incrementality testing involves controlled experiments that split populations into test and control groups, allowing marketers to assess the true additional value generated by specific campaigns, and it functions well even in a world where users are anonymous.

As the industry moves beyond GA4 and other “attribution” systems of measurement,  marketers can regain control. They can now make informed, data-driven decisions about the technologies and innovations that best serve their brand’s objectives. 

The transition to a cookieless reality presents not only a challenge but also a blend of necessity, curiosity, and opportunity, serving as a catalyst for innovation. By leveraging first-party solutions, embracing advanced contextual targeting through IntentGPT, and adopting upgraded measurement frameworks, brands can navigate the evolving landscape with greater confidence.