Stay on Target: Why Google Should Use AI to Stick to Their Plan to End Cookies in 2024

By Richard Howe, Chairman & CEO, Inuvo

With Google once again announcing a delay in the demise of cookies, now until 2025, it’s tempting to think the cookie-less future will never come.

The U.K.’s Competition and Markets Authority (CMA) impacted Google’s plans when they expressed concerns that the company’s Privacy Sandbox, its proprietary replacement for third-party cookies, would give Google Ads a competitive advantage.

But both assumptions are wrong.

There are already many viable alternatives that don’t involve cookies or Sandbox, thanks mostly to AI. Google can stay on track to transform tracking, and the internet will be better for it.

The advent of AI has boosted contextual tracking to the extent Google could legitimately point to it as being equal to Sandbox – and available to all, right now.

Here’s four ways AI has transformed contextual targeting into the most powerful cookie alternative.

AI puts the ‘context’ into contextual targeting

Contextual targeting doesn’t rely on personal information to make targeting decisions. The technology attempts to match the words a brand uses to describe and position itself with the words that represent any audience-focused media.

In the past, that’s made it a weaker performer than cookies – because of the limitations associated with understanding and modeling the contextual information itself.

Today we have the technological ability to read and understand the relationships between words, phrases, page URLs, TV programs, podcasts, radio and any other advertising media, by using the most exciting advancement in AI in a generation, large language models (LLM).

Thanks to an ability to process enormous amounts of data, LLM can make instant connections that would previously require human intervention.

AI can recontextualize contextual targeting

Using LLM can make the objective even simpler. Rather than analyzing who a consumer is, the system can be designed around analyzing, without knowing who someone is, why they are interested in things. Why they might be consuming internet content at any moment in time. This gives marketers the ability to recontextualize contextual targeting.

Audiences of anonymous people can be targetable across media types based on “contextually” based reasons why. This approach has the potential to outperform both the existing user based targeting, and conventional contextual targeting.

AI makes contextual targeting feel personal

People interpret and experience the world through language. Given this reality, it’s logical that the best technology for identifying and actioning audiences would be based on understanding language.

This understanding creates a new alignment, allowing for a more seamless online experience for consumers who have been halted by ads ill-aligned with the intent they had for consuming the media upon which the advertisement was placed.

Large language generative AI facilitates contextual ad-targeting in a manner that allows audiences to feel understood, because it targets the actual reasons behind why audiences are interested to begin with. AI makes contextual targeting feel personal, without compromising privacy.

AI can adapt to improve contextual targeting

Thousands of new words enter the dictionary every single year. These can be generational slang like “boujee,” or a new product like “Vision Pro.” With structured user based targeting, there is no method to adapt to these ongoing changes so brands can remain relevant with their audience selections and targeting.

This is again where the next evolution in contextual shines. These large language model technologies have the ability to bridge the colloquial old and the new and in so doing assure all audiences are approached correctly.

These LLMs can for example associate “boujee” with “luxury” and, depending on the context, can even determine whether the sentiment is positive or negative.

The bottom line: Whenever it happens, the internet is evolving. As cookies go away in 2025, new technologies will be required to keep marketing relevant. Luckily, semantic targeting techniques have advanced through AI into a sophisticated method of keeping ads relevant, and audiences happy – across every consumer generation.

Tags: AI