Case Study: Gymshark achieves 150% increase in new-user Black Friday order rate with Algolia Recommend

Gymshark Adds Algolia Recommend to Handle Crucial Black Friday Period

Gymshark, the fast-growing UK fitness apparel brand, faced limits with its previous recommendation system—heavy manual configuration, constant upkeep, and concerns about handling traffic spikes during critical periods like Black Friday. The company needed a more reliable, scalable way to deliver relevant product suggestions that would increase incremental revenue and reduce demand on engineering resources.

By adding Algolia Recommend, Gymshark deployed an AI-powered, easy-to-integrate recommendation engine that unified catalog, logic, and analytics across its storefront. The impact was significant: new-site users saw a 150% lift in order rate and 32% higher add-to-cart rate on Black Friday, returning customers had a 13% higher order rate and 10% higher add-to-cart rate, users clicked more recommendations (1.4 vs. 1.1), and IT overhead for configuration fell—driving stronger mobile performance and higher conversions overall.

Gymshark

Ben Pusey

Software Product Owner