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CLIENT CASE STUDY • SOCIAL MEDIA & E-COMMERCE

Building Pinterest's Shopping Experience Engine

Pinterest needed to enhance their shopping experience to bridge the gap between inspiration and purchase. We helped build the shoppable pins engine with real-time product catalog integration.

Pinterest project team

PROJECT SUMMARY

A partnership built for measurable momentum.

Pinterest needed to enhance their shopping experience to bridge the gap between inspiration and purchase. We helped build the shoppable pins engine with real-time product catalog integration.

18

Engagement length

8

Specialists assigned

martech

Industry

Dedicated team

Engagement model

THE CHALLENGE

The challenge worth solving.

Pinterest needed to build a scalable shopping experience that could process millions of product catalog updates daily while providing personalized recommendations to users.

Our expertise in high-scale distributed systems and machine learning integration made us the ideal partner.

Building a real-time shopping experience engine that processes 50M+ product catalog updates daily across 450M+ users.
Collaborative product planning

THE SOLUTION

A solution designed to move faster.

We assembled a dedicated team of React, GraphQL, and Python engineers to build the shoppable pins infrastructure. Our team implemented real-time catalog synchronization and ML-powered product recommendations.

About Pinterest. Pinterest is a visual discovery engine used by over 450 million people worldwide to find ideas like recipes, home and style inspiration, and more. Their shopping features connect millions of users with products they love.

RESOURCES & TECHNOLOGIES

All technologies used.

8Dedicated developers, QA and delivery specialists
ReactGraphQLPythonKafkaRedis
WatchHow delivery team

THE OUTCOME

What we built together.

Over our 18-month engagement, we:

What we builtHow the client benefited

Built the shoppable pins engine processing 50M+ daily catalog updates.

Reduced product discovery latency by 70%.

Increased shopping-related engagement by 40%.

Enabled real-time inventory sync across 100K+ merchant partners.

Reduced product discovery latency by 70%.

Built the shoppable pins engine processing 50M+ daily catalog updates.

Enabled real-time inventory sync across 100K+ merchant partners.

Increased shopping-related engagement by 40%.

Redis capability integrated into the delivery roadmap.

Reduced product discovery latency by 70%.

React capability integrated into the delivery roadmap.

Enabled real-time inventory sync across 100K+ merchant partners.

COMMON QUESTIONS

Case study FAQs.

We assembled a dedicated team of React, GraphQL, and Python engineers to build the shoppable pins infrastructure. Our team implemented real-time catalog synchronization and ML-powered product recommendations.
Pinterest logo

KIND WORDS

WatchHow proved to be efficient in hitting every milestone in their most challenging roadmaps. They delivered ahead of schedule and exceeded our expectations.
Engineering ManagerPinterest

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