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Shopify Engineering·Apr 30, 2020·14 min read58

Categorizing Products at Scale - Shopify

By: Jeet Mehta and Kathy Ge With over 1M business owners now on Shopify, there are billions of products being created and sold across the platform. Just like those business owners, the products that they sell are extremely diverse! Even when selling similar products, they tend to describe products very differently. One may describe their sock product as a “woolen long sock,” whereas another may have a similar sock product described as a “blue striped long sock.” How can we identify similar products, and why is that even useful? Applications of Product Categorization Business owners come to our platform for its multiple sales/marketing channels, app and partner ecosystem, brick and mortar support, and so much more. By understanding the types of products they sell, we provide personalized insights to help them capitalize on valuable business opportunities. For example, when business owners try to sell on other channels like Facebook Marketplace, we can leverage our product categorization engine to pre-fill category related information and save them time. In this blog post, we’re going to step through how we implemented a model to categorize all our products at Shopify, and in doing so, enabled cross-platform teams to deliver personalized insights to business owners. The system is used by 20+ teams across Shopify to power features like marketing recommendations for business owners (imagine: “t-shirts are trending, you should run an ad for your apparel products”), identification of brick-and-mortar stores for Shopify POS, market segmentation, and much more! We’ll also walk through problems, challenges, and technical tradeoffs made along the way. Why is Categorizing Products a Hard Problem? To start off, how do we even come up with a set of categories that represents all the products in the commerce space? Business owners are constantly coming up with new, creative ideas for products to sell! Luckily, Google has defined their own hierarchical Google Product Taxonomy (GPT) which we leveraged in our problem. The particular task of classifying over a large-scale hierarchical taxonomy presented

LLMs
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