Can Artificial Intelligence Address the Consent Problem with Data?

Marketers are in for a rough patch. Consider a gloomy world in which website users hide in the shadows and advertisers rely solely on their wits to determine who sees their digital ads. This, we're assured, is the cookie-free future, and it's just around the corner.

The letter 'C' can cause this type of anxiety. Until recently, it was difficult to fathom how the industry could withstand such a paradigm shift. Cookies enable us to target our adverts, understand what visitors do on our websites, and assess our success. What's the harm in doing so?

Many people are concerned about who has access to their online data as a result of recent hazy attempts to map and manipulate them using their data. The introduction of GDPR provided much-needed clarity on how data consent should be obtained, as well as greatly increased public awareness of data protection problems. As a result, we've become well-trained to un-tick the relevant boxes when that unpleasant box appears on the screen.

Platform operators have been quick to react to a shift in public sentiment toward data sovereignty and the fear of users abandoning ship. Apple was the first to implement changes this year, and others have since followed suit, with Google pledging to phase away cookies by 2024.

This is a source of consternation for digital advertising and, well, everyone who operates a website. Unsatisfied advertisers are terrible for big tech's bottom line.

Users' previous consent benefits login-based services such as Facebook and Amazon. They haven't, however, avoided messy cookie warnings. Meta predicted a $10 billion drop in ad income as a result of Apple's new data privacy rules this year.

It's a race to discover methods to keep the advertising bucks flowing and the data economy growing in the face of a growing consent-averse public.

AI has long been employed by auction-based ad systems like Google to predict how people behave so that adverts can be targeted more successfully. However, the data privacy revolution has altered the game.

Emerging ML-based solutions, like Google's Topics API and Google Analytics 4, offer to do more with less information, tracking and targeting people based on prediction and relying less on unique IDs to monitor user interactions.

AI not only helps to 'fill the gaps' where users have refused to enable data collection, but it also allows advertisers to track users' whole journeys, regardless of device.

Contextual ad targeting is another growing AI-based method: AI is used to analyse the content on a website to determine which ads are most relevant to present to the user. Isn't it cutting-edge?

It's not precisely a creative invention; more like the digital equivalent of posting a billboard ad about cars on the highway, but done faster.

That is not to imply that context does not produce results. For decades, TV and radio advertisements have been cookie-free, but they remain powerful. However, with one ad network recently proclaiming a 3% rise in purchase intent as a significant triumph for contextual targeting, you might be better off sticking with the highway billboard for the time being.

With the technology still in its early stages, the judgment is still out on whether AI will be the savior marketers are looking for to deal with a cookie-free future.

With the launch of Google's GA4, there are some hopeful signs, but consent remains at the forefront of the data sovereignty movement, and that is unlikely to change.