Using PID controllers to diversify content types on home feed

Every day millions of Pinners visit the home feed to find inspiration on Pinterest. As a member of the home feed ranking team, it’s my job to not only figure out what relevant pins to show Pinners but also to make sure that…

Real-time experiment analytics at Pinterest using Apache Flink

At Pinterest, we run thousands of experiments every day, and rely mostly on daily metrics to evaluate performance. The daily pipelines can take 10+ hours to run and sometimes are delayed, which has created some inconvenience in verifying the setup of…

Privacy Power-Up: Upgrading Pin Links from HTTP to HTTPS

HTTPS should be everywhere. Your website likely runs over HTTPS, giving your users a secure, encrypted connection, but what about all the outbound links? Can you guarantee that they all use HTTPS? In this post, we describe the steps we took…

Building a more inclusive way to search

Every day, tens of millions of people search for ideas on Pinterest, whether it’s a recipe to cook for dinner that night or a new hairstyle to try over the weekend. According to a Pinterest study, 70 percent of people use Pinterest to…

User state-based notification volume optimization

Notifications play an important role in helping Pinterest’s 335M+ monthly active users discover and engage with inspiring content. It’s crucial to send the right number of notifications with high quality content. If we send too few notifications, Pinners might miss out on great opportunities…

Building a universal search system for Pinterest

On Pinterest, the best answer goes beyond text, but can even go beyond an image too. When you’re looking for eye makeup ideas for example, a video personalized to your skin tone range teaching you how to create a certain look is likely…

How Pinterest runs Traffic-based Interlinking experiments for SEO

Search Engine Optimization, or SEO, is an important channel for people to find ideas and inspiration on Pinterest, and can also help expose new users to first use cases, such as hairstyle tutorials or a home office setup. …

Adventures in big data wonderland: Going down the Pinterest Path

Have you ever started looking for plants on Pinterest, only to end up shopping for pillows instead? Ever find yourself layers of Pins deep into finding a new idea, not sure of how you got there or where you started? When Pinners are in…

How we built rearranging Pins

Listening to user feedback is essential to building a product Pinners love and use to discover and save ideas every day. Often, their feature requests present interesting technical challenges for our engineers. For example, today we launched the ability to…

What we learned from an iOS app OOMs incident

In early 2020, we started seeing significantly elevated out-of-memory (OOM) crashes in the Pinterest iOS app. That incident resulted in a declined Crash-Free Users Rate (CFUR), from the previous 99% to 96%, which was a steep drop. What was going on? We improved…

Detecting Image Similarity in (Near) Real-time Using Apache Flink

Pinterest is a visual platform at its core, so the need to understand and act on images is paramount. A couple of years ago, the Content Quality team designed and implemented our own batch pipeline to detect…

Improving the Quality of Recommended Pins with Lightweight Ranking

The Pinterest corpus is composed of billions of Pins, however, each Pinner only sees a small subset based on their interests when…

La evolución de la búsqueda en Pinterest

This blog article was originally posted in English. To read the English version click here. Cuando Pinterest se lanzó por primera vez, ofrecía una nueva forma de recopilar y organizar ideas de toda la web. Sin embargo, lo que comenzó como un lugar…

Building Pin stats

A few months back, we started building a way for businesses to create and showcase their latest and favorite content on their profiles. We also wanted to make it easier for businesses to understand how their Pins are performing. If a business can…

Understanding Pins through keyword extraction

Pinterest is well known for its visual discovery engine, but much of our content is also accompanied by text. As a result, it’s important for us to be able to understand text to ensure we recommend relevant ideas to Pinners. In this blog post…

Administrar videos en Android

La función de video se lanzó en la aplicación de Pinterest para Android en 2016 a fin de ofrecer una experiencia de video completamente integrada en la aplicación. Esto incluía la capacidad de admitir varios videos por pantalla…

Introducing inclusive beauty searches for mobile

This week, we’re announcing skin tone ranges is coming to iOS (followed by Android) so Pinners can discover relevant hair and makeup ideas. Over the coming weeks, when Pinners search for beauty ideas on their iPhone or iPad app, a palette representing a range of skin tones will appear. The palette enables them to personalized Pins and videos they see. By combining the latest in machine learning and inclusive product development, we’re able to directly respond to Pinner feedback and build a more useful product. Last year, nearly 60% of the top 100 search terms for skin-related searches involved a tone, such as dark skin, pale skin, and olive skin, which showed us women of all skin types wanted a way to customize their searches. Keep an eye out for a deeper look at the design process behind the product. Acknowledgements: Emma Herold, Lulu Cheng, Long Cheng, Yixue Li, Larkin Brown, Candice Morgan, Xixia Wang, and Laksh Bhasin.

Four lessons in making Pinterest faster on Android

As engineers, we intuitively know that a faster app is a better experience for Pinners, but we also have proof that when web pages load faster, user growth improves. Last year, we doubled down on performance across our platforms so…

Supporting React Native at Pinterest

Early last year, a small group of engineers started investigating the possibility of adopting React Native at Pinterest. We’ve been following the ecosystem with interest since it was first open-sourced in 2015. Since then, a robust community has developed around it, and it’s been…

Pinterest + ktlint = ❤

It’s been nearly a year since Pinterest’s Android codebase became Kotlin-first, and about two years since we adopted ktlint for Kotlin linting and formatting. Today, we’re sharing that Pinterest has officially taken ownership over the project. Initially, we chose ktlint because of its…

Ad Metrics Quality and Testing on Mobile

Every day at Pinterest, we help our advertising partners reach Pinners through different ad formats, and we provide them with metrics and analytics on how their ads are performing. Maintaining our partners’ trust and delivering value is critical, so the metrics we expose…

Building Pin cohesion

At Pinterest, we’re building a visual discovery engine where ideas become actionable with links to more information. Once a Pin is saved, its linked content may be updated or expire over time, and so it’s critical to know…

User retention at Pinterest: tackling an ambiguous problem

User retention is an important but nebulous idea. It’s hard to acquire users and even harder to help them feel at home through an engaging and relevant experience. So when some of those users start to leave the platform, your first thought is…

Using graph algorithms to optimize Kafka operations, Part 1

Pinterest uses Kafka across the board for data movement. The Logging Platform team alone manages over 3,000 Kafka brokers transporting trillions of messages per day to help bring more than 320 million monthly active Pinners the inspiration to create a life they love. …

Bottoms-Up: How the Pinterest growth team decentralizes team structure

On the growth team at Pinterest, we describe our structure as “bottoms-up”, meaning ideas and responsibilities flow throughout the team in a way that provides a lot of autonomy to work on the projects each person wants to tackle, across a variety of roles. The…