Our approach to ad privacy

December 5, 2022

A white woman browsing on a cell phone while lying on a grey yoga mat.

Over 445 million people come to Pinterest every month to find new ideas.1 They take actions like searching, saving or creating boards, and this activity provides Pinterest with unique signals about consumer behavior and interests. These signals power some of our advertising solutions, like keyword targeting and Pinterest Trends, that help brands reach relevant audiences on our platform. 

Pinners are here to feel inspired—and inspiration can only happen when people feel safe. That's why Pinterest keeps privacy a priority as we make product and policy decisions. Our approach to privacy includes protections for both consumers, and the brands who want to reach them. We’ve made it simple for Pinners to control how their data is used through their privacy settings, while brands follow our Ad Data Terms and Policies

Our current solutions

Pinterest’s goal is to simultaneously protect Pinner privacy and to ensure brands find success on the platform. We regularly review our policies and update our products as needed. We have already implemented solutions that minimize the use of personal information associated with people’s activity off of Pinterest.

Examples of these solutions include: 

Modeled conversions
Modeled conversions use machine learning techniques that can help brands see a more complete view of campaign performance. They may allow us to report on conversions even in cases where certain signals like third-party cookies are unavailable. 

De-identification techniques
In some cases, we apply de-identification techniques to a specific user’s offsite activity, before using this data for advertising purposes. 

Conversion optimization model improvements
For advertisers running conversion campaigns or shopping campaigns, we use machine learning models that help serve ads to the people we believe are the most likely to convert. We’ve built parts of our models to emphasize platform signals and extrapolation techniques, reducing reliance on offsite data.  

We are also exploring enhancements to other elements of our ads privacy practices, like how we use information associated with people’s activity off of Pinterest and how we design machine learning models.

Our explorations include:  

Third-party attribution solutions
These can include browser-based solutions from platforms like Apple or Google. Their solutions share information with Pinterest that doesn’t contain personal information associated with a specific individual’s activity on these platforms. Even though these solutions remove an individual’s personal information before sharing the data with third parties, they can still be used to attribute conversions. 

Privacy enhancing technologies
We are focused on ensuring advertisers understand the performance of their campaigns, while continuing to protect Pinner privacy. As such, we are exploring new technologies that can help facilitate privacy-centric data collaboration between multiple parties. 

Machine learning improvements
We’re improving our modeling and machine learning techniques to help advertisers continue to evaluate their campaign performance. This includes modeling techniques like extrapolation, which helps estimate expected conversions without identifying specific individuals.

Prioritizing privacy so you can inspire customers

As the advertising landscape evolves, privacy will always be top of mind. We aim to make advertising on Pinterest easy, safe and effective for brands while protecting the privacy of consumers. Thank you for your partnership as we continue on our mission to make Pinterest a safe and positive place for everyone.