Meta expands use of off-site data to personalize feeds and train AI tools

The news: Meta started using data from ad partners on users’ activity outside of its platforms to improve personalization of social feeds and inform AI responses.

  • Meta is removing the “Your activity off Meta technologies” setting that lets users disconnect activity that businesses share and expanding “Activity from other businesses." The latter lets users adjust settings to permit or prevent shared activity data from being used to personalize feed content and AI responses.
  • The company said this builds off of its existing practice of using information that businesses share with Meta—such as games that users play or purchases made on other websites—to personalize ads.

Although this isn’t a net-new activity for Meta, which already uses off-site activity data for ad tailoring, it’s using that ad data as an AI advantage.

By applying this information across the entire Meta ecosystem, including feed ranking and AI products, it’s turning ad and partner data into a multi-purpose tool. It could also help Meta AI become more effective at understanding consumer intent, making its responses feel more unique and helpful.

The caveat: Every major AI platform is looking for new, proprietary data that competitors can’t easily replicate—for example, Meta turned employee behavioral data into a resource for model training. These decisions could shake user trust by blurring the line between data shared for personalized advertising and data used to power AI conversations.

  • While Meta is preserving some user controls, expanding use cases for partner data could spark anxieties about transparency and consent, especially as consumers become more aware of how their personal information is used for AI development.
  • That tradeoff exemplifies an emerging challenge for AI platforms: building more useful experiences without burning customer trust or attracting regulatory scrutiny.

Implications for brands: As AI and ad tech become more intertwined, better personalization and performance could come at the cost of greater scrutiny from consumers.

The setting changes could help ads in personalized feeds feel more native, and brand-specific data could help AI responses improve recommendations in social commerce, but too much customization may alienate users.

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