With the digital industry another step closer to the complete phasing out of third-party cookies — with Google gradually reducing their availability to marketers via Chrome throughout 2024 — brands must be ready for life without them. Yet nearly three-quarters of UK marketers still feel underprepared for these changes.

Traditionally, advertisers have honed in on consumers based on their shopping and browsing habits and inferred interests as gathered through third-party cookies — a practice known as behavioural targeting. However, moves to regulate and then remove cookies have simply added to existing limitations in their ability to form an accurate picture of the consumer; due to their reliance on past browsing and interests, their susceptibility to corruptions, anomalies, or deletion, and because they are untransferable across different devices.

The demise of cookies has coincided with a resurgence of contextual advertising. This uses AI models and natural language processing to analyse the content and intent of a webpage, along with first-party data such as user location and geographical conditions, to determine where and when ads are displayed. Instead of predicting whether a user will be interested in an ad based on their previous interests, contextual advertising shows users ads based on the content they are consuming in real-time.

As a result, contextual advertising can help marketers reach valuable and relevant audiences, deliver tailored experiences, and boost campaign performance, despite not relying on third-party cookies. This is particularly beneficial with advertising on the open web, which has largely depended on third-party data because it does not have the same access to first-party data as the walled gardens.

So what makes contextual advertising the ideal alternative in the post-cookie digital space, and what part does AI play in this process?

Contextual ads prioritise privacy

Half of consumers are not happy about their personal information, such as browsing history, being used to suggest ads to them. Brands have an opportunity to be privacy-centric and non-intrusive with their advertising campaigns by basing them on the current contexts of consumers instead.

As contextual advertising uses AI and machine learning to analyse keywords, visual media, and text within webpages to determine ad suitability, there is no need to track a user’s personal browsing habits; therefore privacy is preserved. This allows marketers to reach users who are most likely to engage with their ads without tracking their behaviour across websites using third-party cookies.

In addition, minimal first-party insights such as user location, device type, demographic data, and website or app usage analytics — passively collected in full compliance with privacy regulations and with total transparency to the user — can be harnessed by contextual advertising solutions to tailor ads towards user preferences.

Brands adopting this approach can align with growing regulatory and public expectations to be privacy-centric; clearly communicating to their stakeholders and users how they process and store data and respect user consent. 

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AI-powered contextual advertising is more intentional

A survey by Connatix found that 82% of consumers notice when an ad matches the content they are already viewing. By targeting users who are actively interested in a product or service, brands can impactfully reach the right audience groups — maximising relevance and engagement — and avoid spending ad budgets on unsuitable consumers.

As the context, intent, and nuances of webpages are holistically examined before ad placement, brands can also ensure their ads are shown alongside content that matches their values and messaging. In this way, advertisers can prevent being associated with misinformation and harmful content, inadvertently damaging their reputation, and wasting ad spend on illegitimate publishers — an advantage not offered by cookie-based advertising.

Moreover, discriminative AI-powered contextual advertising can replace traditional keyword blocklists that are not nuanced enough to accurately identify harmful or misleading content online  — and are even detrimental at prioritising minority-owned publishers — by intelligently placing brands’ ads in safe environments that align with brands’ Diversity, Equality and Inclusion (DE&I) goals.

Brands that align with industry-wide standards laid out by Global Alliance for Responsible Media (GARM) can further improve brand safety by incorporating key guidelines for identifying misinformation and harmful content into their contextual advertising algorithms. As a result, the impact of bad actors and distributors of online misinformation can be stifled while innovatively targeting high-quality audiences.

Furthermore, as contextual advertising is in-tune with real-time factors – such as geographical conditions – users can be targeted with increasingly personalised and relevant offerings. For example, consumers living in an area that is projected to experience a snowstorm can be targeted with snow equipment, maximising conversions and ROI for marketers. 

Moving forward in a cookieless future

Although the removal of third-party cookies is bound to disrupt marketers’ operations across the industry, it can also be an opportunity for brands to enhance customer experiences, user privacy, and online safety. 

Recent advancements in discriminative and generative AI are enabling contextual advertising solutions to be more precise than ever at analysing and determining the intent and suitability of dynamic online content and placing ads in front of engaged, appropriate audiences. 

By forming strategic partnerships and developing AI-powered contextual advertising capabilities, brands can elevate their campaigns to new heights by delivering hyper-relevant, timely ads that perform well while maintaining user privacy and moving beyond outdated cookie-based targeting.

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