By Mateusz Rumiński VP of Product, PrimeAudience
The advertising industry is at a crossroads. With the decline of third-party cookies, tightening privacy regulations, and increasing consumer demand for transparency, traditional targeting methods are quickly losing their effectiveness. The challenge for marketers is no longer just to reach the right audience but to do so in a way that aligns with evolving compliance standards while maintaining precision and impact.
One of the most critical distinctions that advertisers need to understand in this shifting landscape is the difference between interest and intent. Many traditional targeting models have relied on broad interest-based signals, often mistaking curiosity for readiness to buy. In a world where data-driven marketing must be both effective and privacy-conscious, advertisers need a more sophisticated approach. AI-powered intent prediction is emerging as a key solution, allowing marketers to refine audience targeting rather than just relying on outdated tracking methods.
Why traditional marketing is no longer enough
For years, digital advertising has been built on behavioural tracking, following users across the web to build audience profiles based on past activity , often collected without the expiration date, leading to outdated user characteristics. However, with the expansion of GDPR, CCPA, and a growing number of state-level and global privacy laws, the ability to track individuals at scale is disappearing. Simultaneously, major tech companies are reshaping the way that data is collected and used. Apple’s App Tracking Transparency (ATT) framework and Google’s Privacy Sandbox are reducing advertisers’ access to granular user data, making many conventional audience-targeting strategies increasingly obsolete.
The shift exposes a long-standing flaw in how many brands approach digital advertising. Traditional methods often assume that interest and intent are the same. A user reading about “The Future of Electric Vehicles” may have a general curiosity about the topic, while someone searching for “Best Hybrid SUVs Under £40,000” is likely considering making a purchase. Treating these two behaviours as equal leads to wasted ad spend, misalignment between messaging and consumer readiness, and a decline in campaign effectiveness.
Demographic-based targeting presents similar challenges. In most cases, stating that a given individual belongs to a specific demographic is a challenge, and knowing that a consumer fits a broad profile provides little insight into their actual needs or purchase readiness . These static datasets fail to capture real-time behavioural signals, making it harder for brands to connect with the right audience at the right moment. As privacy restrictions tighten, marketers need to move beyond these outdated models and rethink how they identify intent, without relying on invasive tracking techniques.
AI-powered intent prediction – a more smarter, more compliant approach
As third-party cookies disappear and traditional tracking methods fade, contextual AI-driven solutions are becoming essential for brands looking to maintain relevance. Rather than just tracking individuals, Generative AI can analyse the content users engage with to determine their interest in a given topic. This shift allows advertisers to reach consumers based on their real-time intent rather than their past browsing history.
AI-driven intent prediction also addresses one of the biggest challenges of the post-cookie era – compliance with privacy regulations. By leveraging content-based signals instead of personal tracking, brands can align with regulations while still delivering highly relevant, effective campaigns. This approach shifts the focus from who the user is, to what they are engaging with, reducing reliance on personally identifiable information while maintaining marketing effectiveness.
The future of advertising, from tracking to understanding
The industry is moving toward an intent-driven advertising model, where brands will need to move beyond broad interest signals and adopt smarter, privacy-compliant targeting strategies. AI-powered solutions, like Generative AI models used in intent prediction, will play a central role in this evolution. The ability to analyse context and real-time behaviour – rather than relying on obsolete historic data – will determine which brands succeed in an increasingly regulated and competitive digital landscape.
As privacy laws continue to evolve and consumer expectations around data transparency grow, the brands that thrive will be those that embrace AI-powered intent prediction, not just as a workaround to data restrictions, but as a smarter, more effective approach to audience engagement. Marketers must start prioritising solutions that allow for predicting intent, target with precision, and comply with privacy regulations – all without relying on invasive tracking methods.
In this new era, success in digital advertising will belong to those who understand the difference between interest and intent, and leverage AI-driven insights to build more meaningful, privacy-first connections with their audience.
I would add that in many cases this past activity is collected without the expiration date, so some data about user can be stored for a long period of time in which the user’s characteristics dramatically changed.
I would even add here, that in most cases even stating that a given individual belongs to a certain demographic is a challenge.
