One of the most fundamental problems facing the ad industry right now is privacy. Consumers are increasingly reluctant to share their data, and at the same time browsers, such as Apple’s Safari, are promoting private browsing. Google has already said it plans to eliminate third-party cookies from its Chrome browser.
Europe already cracked down on advertisers using personal data, as have a number of U.S. states, and that’s just a start. Currently, 11 states have consumer data privacy laws and 21 more have introduced bills to address the issue. It’s only a matter of time before consumer identity – or even demographic-based targeting – is completely removed from the advertising equation.
In advance of further privacy limitations, brands would be wise to see the ways that using generative artificial intelligence to optimize ad spending can eliminate the issue of privacy entirely while helping to get a bigger ROI.
Here are three ways AI can solve the issue of privacy:
Use AI to Discover New Audiences
AI reflects the collective wisdom of humanity as represented by the collective content of the internet. New tools can instantly understand the association between every word or phrase on a page with every other word or phrase that exists; and associates any page of internet content with the entire web.
These large language models can see the connections between things that might seem totally unrelated, but are actually highly correlated. For example, an AI program can determine that the brand Carhartt correlates with the movie “Interstellar” because it knows Matt McConaughey and Jessica Chastain’s characters wear Carhartt jackets in that movie. As a result, there’s an audience at the cross-section of those two themes, one that you would never have been able to identify, let alone purchase, using a consumer’s identity, which in this case – and many others – is largely irrelevant.
Remember It’s Not the Who But the Why
Conventional advertising uses identity-based solutions that rely on cookies, or universal IDs, to figure out WHO someone is, and then uses that identity to determine whether an ad should be shown. AI can shift the marketing model from being about WHO consumers are to WHY they are interested. When you target “who,” you get more of the same “who’s”; when you target “why,” you get all the “who’s” that share the same “why’s.”
In the past, brands would rely on surveys to understand consumers. But surveys are notoriously unreliable. Who needs surveys when the language model behind the AI is updating itself roughly every 5-minutes to capture the latest and greatest links among concepts and the association of those concepts to brands? So rather than focusing on the identity of one individual, marketers can continually target buyers without knowing any personal details about them.
Target Effectively Without Personal Data
By turning to generative AI for digital advertising, brands can target consumers in new, more effective ways without raising privacy issues. AI can provide cookie-level targeting without cookies, allowing advertisers to deliver targeted ads not to individuals or to IP addresses but to larger interconnected concepts without harvesting user data or third party information.
Many brands think the answer to a cookie-less future is collecting first-party data. But that essentially leads to the same problem. While users may “voluntarily” provide personal information, it may not be long before the same forces – consumer preferences and regulatory policies – begin setting limits on first-party, which even in the best of cases, is already proving itself to be considerably less effective than third-party. What’s more, collecting that data still leaves brands chasing the who, rather than the why, which limits their audiences, the effectiveness of their message and opens them up to the risk of consumer backlash on the brand.
AI provides constantly up-to-date knowledge of consumer intent, but without the specifics of any individual consumer. There’s no need to use a consumer’s identity and data through IP addresses or cookies, or URL tracking for media targeting.
With AI, ad spending is largely driven by browsing and purchasing patterns. Cookie-based targeting can only bid on 25% of users, but AI systems can target and bid on all users. Being able to locate and target audiences based on a prediction of why they are in front of any screen allows marketers to be more strategic with their brand content.
The Bottom Line: It’s important for marketers to understand that a future devoid of identity is upon us. And the sooner brands start thinking about providers and technologies that can help them move away from first-party targeting, the sooner they’ll be unshackled from the structured nature of that approach to marketing and open themselves up to new possibilities.