Gymshark adds Algolia Recommend to boost Black Friday order rates by 150%
Gymshark's previous recommendation solution required extensive manual configuration and constant upkeep, creating operational burden and limiting the team's ability to improve recommendation quality efficiently.
The prior recommendation solution demanded so much manual configuration and constant upkeep when making changes that the team spent significant effort on maintenance rather than improving recommendation quality.
Algolia Recommend delivered a 150% increase in order rate and 32% increase in add-to-cart rate with new users on Black Friday, a 13% higher order rate for returning customers, and reduced manual configuration burden on the IT team.
Show all 9 reported metrics
Frequently asked questions
What did this team achieve with this AI workflow?
Algolia Recommend delivered a 150% increase in order rate and 32% increase in add-to-cart rate with new users on Black Friday, a 13% higher order rate for returning customers, and reduced manual configuration burden o…
What tools did this team use?
Algolia, Algolia Recommend, Shopify, Contentful, React, AWS.
What results were reported?
order rate increase (new users, Black Friday): 150%; add to cart rate (new users, Black Friday): 32%; Order rate higher (returning customers): 13% higher; Add to cart rate higher (returning customers): 10% higher (source-reported, not independently verified).
What failed first in this deployment?
The prior recommendation solution demanded so much manual configuration and constant upkeep when making changes that the team spent significant effort on maintenance rather than improving recommendation quality.
How is this ecommerce ops AI workflow structured?
Customer visits product page → AI recommendation generation → Recommendations displayed to user → A/B test validates performance → Iterative improvement and expansion.