Pinterest shares algorithm insights as it shifts focus to non-engagement signals
The platform warns that relying too heavily on engagement signals to rank content can result in a poor user experience.
Pinterest provided insights into how its algorithm works while warning of the risks of overreliance on user engagement. The platform emphasized that excessive reliance on engagement to rank content can result in a negative user experience, and proposed non-engagement signals as a solution.
To encourage other companies to follow suit and contribute to “building a more inspired Internet,” Pinterest published a new document titled ‘Field Guide to Non-Engagement Signals’.
Why we care. By having a better understanding of how Pinterest’s algorithm works, brands can identify what metrics they should prioritize in order to secure more visibility for their content.
What are non-engagement signals? Non-engagement signals are generated from two primary sources:
- In-app surveys: These give users have the opportunity to provide direct feedback about the platform. For instance, Pinterest may conduct surveys within the app to gather user insights.
- Independent assessments of content quality: This tends to be generated from manual labeling.
In addition to balancing engagement signals in content ranking, non-engagement signals enable Pinterest to align with its values. For example, Pinterest’s commitment to inclusivity is supported by non-engagement signals. When users specify preferences regarding body type, hair pattern, or skin tone in their feed, Pinterest can prioritize relevant content accordingly.
Field guide. Pinterest teamed up with UC Berkeley and the Integrity Institute to create the Field Guide to Non-Engagement Signals in a bid to help platforms create a better user experiences over time. Pinterest noted that the purpose of the guide is simply to help platforms make informed decisions when it comes to utilizing Non-Engagement Signals, as opposed to tell them what to do.
Key takeaways. The field guide, which is based on practical industry knowledge, offers several practical applications for product development, including:
- How to tune for emotional well-being.
- Using Generative AI to scale content quality signals.
- Improving user retention.
What Pinterest is saying. Leif Sigerson, Pinterest Sr. Data Scientist, and Wendy Matheny, Pinterest Sr. Lead Public Policy Manager, said in a blog post:
- “User engagement is a critical signal used by Pinterest and other online platforms to determine which content to show users. However, it is widely known that optimizing purely for user engagement can surface content that is low-quality (e.g., clickbait), or even harmful.”
- “Our CEO, Bill Ready, explained that if we’re not careful, content ranking can surface the ‘car crash we can’t look away from’, On the other hand, if you ask somebody after they saw the crash, ‘you want to see another one?’’ the vast majority of people will say ‘Goodness no’.”
- “Non-Engagement Signals are a critical component to ensure we don’t optimize for ‘the car crash we can’t look away from.'”
Deep dive. Read Pinterest’s blog in full or download a PDF copy of the field guide for more information.
Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.
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