Why global brands are making the switch to cookie-free, interest-based targeting

The ad tech world is steadily shifting to more inclusive and privacy-centric advertising practices that align with the requisites of consumers and data privacy regulations. Fundamentally, audience categorization has largely been based on the demographics and past behavior patterns of users. This practice is based on assumptions and stereotypes that are limiting, not always accurate, and relies on third-party cookies.

The audience selection and classification process plays a crucial role in determining the success of an ad campaign. By collecting data from various sources, advertisers leverage data to display ads to users based on their assumed interests, hobbies, and browsing activities. The main data points include -

  • The websites and apps a user chooses to visit, browsing patterns and interactions, and what kind of content they engage with
  • Demographics like age, gender, and location
  • Interests listed by the user on platforms like social media
  • Third-party data

Using this data, marketers profile potential customers who are most likely to buy their product or service and target their ads to those individuals.

What is interest-based targeting?

Consumers have become increasingly apprised of digital advertising practices and are well-informed about their data and personal information being collected whenever they are online. The increase in awareness and rising frustration of consumers around data privacy resulted in the decision to phase out third-party cookies and governments implementing more stringent data privacy regulations. Marketers are facing several restrictions today and the conventional audience categorization and targeting practices will result ineffective as they are built on stereotypes and assumptions, and are not privacy compliant.

While traditional advertising practices reach a broader audience, they are not necessarily effective as everyone who views the ad might not be interested in the product/service, leading to wasted ad spend. Consumers have access to a plethora of information and are bombarded with hundreds of ads daily. A blanket targeting approach sans any personalization or relevance is not just ineffective but could have a negative impact as it disrupts the user journey. Additionally, consumers are also using ad blockers to avoid traditional ads while streaming services give them the option to skip ads.

New-age targeting goes well beyond the conventional, identity-based targeting approach and focuses on a user’s current areas of interest and the context of the content they consume. Breaking away from stereotypes, interest-based targeting is held as a more effective, non-intrusive, and privacy-centric alternative.

The rise of interest-based targeting in the cookieless world

Contextual targeting is a strategy that focuses on categorizing consumers based on what they are interested in at present, by displaying ads that align with the content they are consuming on a web page or app. When the on-page content and context align with the ads, it ensures a seamless, privacy-centric, and non-intrusive customer experience. Interest-based targeting enables personalization and allows marketers to tailor ads to individual preferences, thus enhancing relevance and engagement. Users are more likely to engage and resonate with the ad because it aligns with what they are looking for in the moment and since the ads blend with the content they are reading, the ads don’t hamper their browsing experience.

Seedtag Contextual Audiences help brands go beyond conventional targeting practices and engage with users based on what they are looking for or interested in at the moment. Powered by Liz©, our pioneering AI technology,  custom AI, contextual categories, images, and cookieless sociodemographic models, allows brands to target an audience base that’s diverse, inclusive, and relevant. Our Contextual Audiences evolve from customer input and diverse market research enabling brands to build unique and dynamic audience categories to suit specific business needs.

Interest-based targeting practices like contextual targeting empower marketers to appeal to a more relevant customer base with ads that align with their real-time interests. Contextual ads appear at the most optimal time and place with tailored messaging without violating privacy, thus helping brands reach the desired audiences with a targeting capability that is more flexible and accurate. With interest-based targeting, brands can capture user attention at the ideal moment without relying on cookies, and overcome the limitations of rigid taxonomies and stereotypes.

With Seedtag Contextual Audiences, brands can build a hyper-personalized target group. Backed by AI, this unique targeting capability provides flexibility, scale, and higher accuracy. To know more about the exclusive offering and types of contextual audiences, contact us.

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Find answers to get the most out of Seedtag.

What is Neuro-Contextual Advertising?

Neuro-Contextual Advertising is an evolution of contextual advertising that uses AI to understand interest, emotion, and intent within content. Instead of relying on personal data, it helps brands align advertising with the moment people are experiencing in real time.

What is contextual advertising?

Contextual advertising places ads based on the content a person is engaging with, rather than personal browsing history or identifiers. Neuro-Contextual approaches go beyond traditional contextual targeting by understanding audience interest, emotion, and intent.

What is CTV advertising?

CTV advertising refers to ads delivered through Connected TV environments, including streaming platforms and smart TV applications. It allows brands to reach audiences across premium video experiences using more contextual and privacy-first targeting approaches.

How does Seedtag’s AI work?

Liz is Seedtag’s proprietary Neuro-Contextual AI, designed for full-funnel advertising across premium open web, video, and CTV environments. Grounded in neuroscience, Liz understands contextual signals such as interest, emotion, and intent in a human-like way to deliver relevant advertising experiences in real time while respecting user privacy.

Why is privacy-first advertising becoming important?

With consumers increasingly wary of data collection and cookies, privacy-first advertising focuses on delivering personalized and relevant ads while respecting user privacy. Neuro-Contextual advertising enables relevant advertising experiences without relying on personal data or third-party cookies.

How does AI improve digital advertising?

Leveraging neuroscience principles, Liz recognizes patterns, interprets context, and responds dynamically to user interests, emotions, and intentions. This creates a more cohesive and intelligent system capable of delivering more relevant advertising experiences.