Wish.com
Wish Increases Revenues with Personalized Ecommerce Recommendations Powered by TigerGraph
Wish is one of the fastest-growing ecommerce platforms in the world. Founded in San Francisco just over a decade ago, the company is already the third largest e-commerce platform in the United States, with revenues of $2.5 Billion in 2020. More than one million merchants list their products on Wish. The company’s app was the most downloaded ecommerce application worldwide, and approximately 90 million people use the app at least once a month globally.
The Challenge
Wish wanted a way to provide consumers with personalized recommendations in order to maximize revenues. To meet this challenge, the company needed a solution that would run real-time queries to suggest the appropriate products to shoppers, based on their past preferences and online behavior. Wish turned to TigerGraph for its ability to provide personalized recommendations, make better business decisions, and ultimately, increase revenues.
We are very happy with TigerGraph as it provides the speed and scalability we need using a framework that is natural for modeling data. TigerGraph empowers our business to tap into and make the most of our data relationships for competitive advantage.
Key Pain Points
TigerGraph provides Wish with the ability to model its vast product catalog and develop a precise understanding of consumers’ shopping patterns. Next, TigerGraph’s deep link analytics uncover insights that are based on product features, customer demographics, prior purchases, search context, and more, to provide accurate and personalized purchase recommendations—and do so in real time. Initially, the TigerGraph data platform was used to detect similar and duplicate products. However, after seeing the performance and potential of real-time graph analytics, Wish expanded their use of TigerGraph to provide real-time recommendations to customers—an important, business-critical project.
The Results
Along with increasing query speeds by 100-fold, TigerGraph is enabling Wish to use fewer machines—cutting hardware and associated management and maintenance costs. In one instance, TigerGraph has reduced memory usage by 10 times due to efficient graph-based encoding and compression. Moreover, TierGraph has increased the productivity of the data and analytics team at Wish enabling the business to make better decisions and improve time to market.
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