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Facebook’s Private Exclusion Targeting Rendered Exclusively Locally (Petrel) is aimed to allow marketers to stop sending ads to users based on specific prior activity, such as recently having purchased their product. In addition to the marketer benefit of no longer wasting budget, exclusion targeting also addresses consumer complaints about seeing ads for the products they just purchased.[1]

Facebook’s proposal adopts the goal of Google's Privacy Sandbox to prevent marketers from engaging a particular audience in a particular context.


Petrel suggests that just as other proposals add interest topics to web clients, so too should a proposal be in place to remove such assignments.

The Petrel proposal suggests that the web client stored "exclusion group" that are analogous to the Turtledove "interest group".[2] Each exclusion group could contain a number of product_IDs that are proprietary to a given organization.[3]

Petrel suggests that an ad response ought to contain an ordered list of potential ads which each individually include a product_id, such that the web client can display the first ad that does not contain a product_id belonging to an exclusion group it has previously stored.[4]

The exclusion rule for a given product_ID can be time bound, such as for the next 90 days.[5]

The proposal assumes that the auction logic will be analogous to Turtledove/Fledge, where the publisher will not receive any information about what products the organization wishes to suppress users from.


The proposal is limited only to advertising use cases, and hence does not address content management needs of publishers that are wishing to personalize content that is ad-funded. An information site might see interest in a given set of research and reviews in the previous seven days. When the user returns, unbeknownst to the publisher the user has already purchased the product associated with prior activity. While Petrel would suppress the ads to fund the recommended articles related to that product, the site would now be showing less relevant content to the user that would negatively impact their experience. Larger sites that both sell and provide reviews would thus be at a competitive advantage under such a system to smaller sites that only provide information.

As with other user-controlled attribute proposals, Petrel confuses the concern people have regarding receiving output content with the attribute data input that may or may not have been used to match the content. If someone would prefer not seeing running shoes, removing “sports” or “shoes” from their profile does not prevent matching on current context, geography or even registration data. To more directly address such user concerns, these proposals could be improved by storing sets of “paused” ads or brands, rather than unlimited number of potential inputs that might lead to the unwanted content.

Not all interest attributes are equally valuable to all marketers. By restricting the list of available attributes, or ranking them on criteria independent from publisher monetization, will further impair publisher revenues.

Open Questions

  • How will any interests scale if each organization wants its topic information to remain proprietary?
  • As there are millions of organizations, if each is assigning custom nodes what is the impact on local storage or classification process of interests?
  • How many organizations can be allowed from a given sandboxed element without impacting user experience?
  • Is the allow setting at a controller (e.g., marketer) level or at a vendor (e.g., verification vendor) level?
  • Why match ads on interest attributes but exclude at product_ID, rather than more directly pause based on ad or brand?
  • How can smaller publishers compete on a level playing field with larger rivals under this model?

See Also