Rakuten Ichiba is the largest e-commerce site in Japan and is among the largest in the world. The online giant offers more than 100 million products from about 40,000 merchants and has more than 500 million visitors a month.
With 40,000 vendors in the Rakuten ecosystem, it was increasingly difficult for shoppers to find the exact item they wanted due to inconsistent product data and keywords not matching customer intent.
These merchants are required to update information and images about products that they are selling online. Rakuten observed that product discoverability was a challenge, as the way in which merchants described a product often differed from the way shoppers were searching for products. The company had implemented best practices for merchants regarding product descriptions and meta tagging in the past, but was now looking for a solution that could solve this problem at scale, especially for their fashion category. The company wanted to transform the consumer’s discovery phase for fashion products on the site and therefore the challenge was broken down into two parts. First, Rakuten wanted to ensure that shoppers are enabled to search for products that are visually relevant to what they are looking for. The second part of the challenge was to enable shoppers to find complementary products based on color similarity.
Rakuten used ViSenze Smart Tagging to automatically optimize their product listings at scale, with a 99% accuracy compared to manual tagging.
This allowed customers to find the items they wanted using the text phrases they are most familiar with.
Rakuten used AWS infrastructure to power ViSenze’s AI/ML solutions using EC2, EKS, Aurora, SQS, and S3.