Case Study: Farfetch achieves faster, data-driven product experimentation to help boutiques sell online with Optimizely

Farfetch Uses Data to Help Boutiques Adapt, Innovate, and Go Faster

Farfetch is a global marketplace for luxury fashion that faced sudden disruption as brick-and-mortar boutiques closed and tourism dropped during COVID-19. The company’s challenge was to help its network of high-end shops quickly create reliable digital revenue streams while maintaining the quality and personalization luxury customers expect.

Farfetch leveraged a data-first platform—powering recommendations, search, visual merchandising and pricing—and a strong experimentation culture to run rapid, hypothesis-driven tests using both quantitative and qualitative insights. By “failing fast” and treating results as probabilistic ranges, teams prioritized high-impact bets, validated cumulative business effects each quarter, and accelerated learnings that helped boutiques go online and stabilize revenue.

Farfetch

Luis Trindade

Principal Product Manager of Experimentation