President & GM at AppsFlyer, overseeing the strategy and operations for North America.
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Nearly a quarter of marketing professionals in organizations use AI. Among them, 76% use it for basic content creation and to write copy. And I can guarantee that number is sure to increase as the availability and adoption of generative AI tools increases. Brands and agencies face the delicate task of employing AI-powered solutions while also respecting customer privacy. While beneficial, AI and generative bots, like ChatGPT, do not inherently guarantee data privacy. Balancing the technology’s need to consume data with protecting consumers’ private data is at the core of the tightrope walk.
For many consumers, privacy is top of mind, and the same applies to marketers. Let’s take a look at the ramifications of user-level privacy changes, data privacy regulations and how marketers are balancing the demand for customized content and meaningful interactions while protecting consumer data.
Personalization—The Hot Topic Of 2023
Personalization goes hand in hand with omnichannel marketing. Imagine walking into a physical store; does it bother you if the employee does not greet you upon entering or offer their assistance? The same is applied to online experiences. Seventy-one percent of consumers expect companies to deliver personalized interactions, and 76% get frustrated when this doesn’t happen.
The challenge with personalized experiences is that consumers expect tailored and relevant content while also wanting to share minimal amounts of personal data. As regulations, laws and platform modifications are being introduced to protect users, consumers are becoming more aware of the value and sensitivity of their data and the value exchange of this information, especially with recent data breaches, including those involving Topgolf Callaway brands, 23andMe and Duolingo. No wonder consumers are wary.
This year, quite publicly, there’s been an increased wave of generative AI being injected into all digital platforms and services, promising better experiences for customers, reduced costs and operations and increased effectiveness. Ranging from text generators like ChatGPT and Google Bard to image generators like Midjourney and Dall-E—and even music created by generative AI that is rising in popularity—everything has its own use cases and privacy drawbacks.
The Challenges And Risks Facing Your AI Solution
The privacy wave, combined with the AI wave, means these forces of next-gen technology and consumer privacy can be at odds with each other. Why? Because AI feeds off of data. It needs data—and lots of it—to train the models, to change the weights of the inputs and to work effectively. Once the model is in production, the more data it is fed means, the more it learns and the better the output. The system challenge at a technical level means that private user-level data is too often put at risk of exposure.
Privacy laws and restrictions, including President Biden’s new Executive Order, are all around the principle of data minimization and protection. Ideally, this results in marketers contending with how to get the same output and deliver the same experiences while protecting consumer privacy with the loss of signal.
Finding a way to balance that has been challenging for many brands, who have to navigate this dynamic from the customer without the user-level data that was previously available to them. This is the fundamental challenge that is being addressed through privacy-enhancing technologies (PETs) moving forward.
The Clean Room
Data clean rooms have become one solution for marketers looking to leverage data in a privacy-centric way. It provides aggregated and anonymized user information to protect user privacy while providing advertisers with non-personally identifiable information.
These clean rooms, which have been around for years but are becoming more widely adopted, are pivotal in helping companies enrich their own first- and third-party data with attribution data, including with self-reporting networks (SRNs) like Meta, in a way they could not do before. Marketers don’t need to rely on their data science teams to understand and generate insights so they can quickly optimize and act on their campaigns. Consumers have peace of mind that their data is safe, secure and being used appropriately according to the strictest and newest data privacy regulations and guidelines.
On top of that, there’s been a wider adoption of privacy-enhancing technologies or other solutions that allow information to be collected, processed, analyzed and shared while protecting data confidentiality and privacy. PETs, while not without their challenges, have the potential to combine consumer protection with the data needs of digital marketers.
What's Next
Advertising and marketing technology has relied for many years on using third-party cookies and mobile device IDs, serving as an unofficial standard for how operations have worked. But this is quickly going away.
Laws are coming into place to restrict the use of these methods, and large platforms are changing their policies to restrict the way data is used and shared. Brands are listening to consumers and agreeing not to share their sensitive customer information with their partners. In the future, there will be no exchange of user-level data without the individual’s consent unless there is a use of these clean rooms or similar infrastructures.
Combined with AI, marketers—who are already hyper-focused on data privacy laws—will need to be more vigilant about the data that AI is processing. Utilizing these technologies, like data clean rooms and PETs, means marketers can now create tailored experiences with a heightened awareness of how data is being used.
Whether it’s for creative analytics, fraud protection, predictions or other measurement and optimization tactics, there is an inefficiency to humans owning so much of the process. The symphony of tech and privacy-conscious marketers and tech leaders can make this move fluidly into the next phase of technological development.
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