Case Study: Mercari achieves sub-200ms search and scalable personalized discovery with Algolia

How Mercari keeps delivering dynamic experiences for marketplace buyers and sellers

Mercari is a large recommerce marketplace (founded in 2013) with millions of users and roughly 350,000 new unique listings added daily, where no two items are the same. That scale and constant inventory churn made it difficult for Mercari’s legacy open-source search to deliver fast, relevant results while also managing recency and sold items — a problem that required a more scalable, reliable search solution.

Mercari selected Algolia for its performance, reliability, and easy-to-use APIs to power keyword search, typeahead suggestions, seller-side suggestion indexes, guided listings, and improved filtering and tagging. As a result, Mercari reduced average search latency to under 200 ms (about 500 ms end-to-end), improved personalization, and now maintains search with a much smaller internal team, freeing resources for other projects while continuing to optimize speed and relevance.

Mercari

Manikandan Sankar

Head of Data