Case Study: Gymshark achieves £6.5M annual revenue uplift with Algolia search and navigation

Gymshark’s journey to MACH The practical case for search and navigation

Gymshark, a fast-growing UK fitness apparel brand selling internationally through 15 online stores, faced a critical technology failure on Black Friday 2015 that exposed limitations in its Magento stack—poor search relevance, out-of-stock items surfacing, no personalization or localization, and an unscalable manual merchandising workflow. The team adopted MACH principles (microservices, API-first, cloud, headless) to rebuild a composable stack around Shopify, Algolia, Contentful, React and AWS.

They replaced native search and navigation with Algolia-powered, headless solutions that added business data to ranking, AI-generated synonyms, automated merchandising and personalized experiences across search, collection pages and apps. The changes boosted performance and automation, generating an estimated £2M/year from search improvements and £4.5M/year from collection-page merchandising while eliminating manual reranking and enabling rapid, iterative product launches.

Gymshark

Ben Pusey

Product Manager