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Artificial Intelligence: How Can It Aid With The Consent Problem With Data?

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Marketers are facing a difficult time. Imagine a dark world where website users hide behind the scenes and advertisers rely on their intuitions to decide who sees their digital ads. We are assured that this is the future of cookie-free advertising, and it is just around the corner.

This anxiety can be caused by the letter “C”. It was hard to imagine how the industry could survive such a paradigm shift until recently. Cookies allow us to target ads, understand how visitors use our websites, and evaluate our success. Why would you want to do this?

Recent attempts to manipulate their online data using hazy methods have led to many people being concerned about who can access their data, especially when playing online casino games NetBet. The GDPR introduced much-needed clarity about how consent for data should be obtained and raised public awareness of data privacy issues. We are now able to un-tick any unwanted boxes that appear on the screen.

The shift in public sentiment towards data sovereignty and fear of users abandoning ship has prompted platform operators to quickly react. Apple was the first company to make changes in this year’s software, while other platforms have followed suit. Google has pledged to eliminate cookies by 2024.

This is a problem for digital advertising and everyone who runs a website. Big tech is not happy with its bottom line.

Login-based services like Amazon and Facebook benefit users’ consent from their previous consent. However, they have not been able to avoid messy cookie warnings. Meta forecasted a drop of $10 billion in ad revenue as a result of Apple’s new data privacy regulations this year.

It is a race to find ways to keep advertising dollars flowing and to grow the data economy in the face a growing consent-averse population.

Auction-based ad systems such as Google have used AI for predicting how people will behave in order to target more effective ads. The data privacy revolution has changed the game.

Google Analytics 4 and Google Topics API are two examples of emerging ML-based solutions. They offer more information and track and target people based on prediction.

AI can be used to fill in the data gaps where users refuse to allow data collection. It also allows advertisers to track users’ entire journeys, regardless if they are using an Android or iOS device.

Contextual advertising targeting is another AI-based method that is on the rise: AI is used for analyzing the content of a website in order to determine which ads would be most useful to present to the user. It’s cutting-edge, isn’t it?

This is not a particularly creative invention. It’s more like a digital billboard advertising cars on the highway. But it’s done much faster.

This does not mean that context doesn’t produce results. Television and radio ads have not been cookie-free for decades but they are still powerful. It is possible to stick with the highway billboard, despite one network claiming a 3% increase in purchase intent, which could be a major triumph for contextual targeting.

The technology is still in its early stages so it’s difficult to say if AI will be the solution marketers seek to solve their cookie-free future.

There are positive signs with Google’s GA4, but consent is still at the forefront of data sovereignty movements, and that is not likely to change.

Cody Rhodes
Cody Rhodes
Cody Rhodes a learning specialist, designs and delivers learning initiatives (both in-class and online) for a global and internal audience. He is responsible for the ongoing development, delivery, and maintenance of training. He has the ability to manage competing priorities to execute time-sensitive deliverables within a changing environment. He contributes to continually improving the team's processes and standards and works as a member of the team to assist with team initiatives.

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