ecommerce_ops · ecommerce · workflow
Under Armour achieves 35% higher conversion rate with Algolia search
Under Armour's in-house open source search platform depended on a small group of developers who became the sole subject matter experts; when those developers moved to other roles, the product team lost the ability to adapt the platform to emerging search trends in real time.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Customer initiates search
Most customers start their journey on the website in the search bar.
Tools used
AlgoliaType-AheadQuery RulesAnalytics DashboardInstantSearch
Outcome
After implementing Algolia in 2017, Under Armour consistently sees a 35% higher conversion rate for customers who use search, and converts at a higher rate on search than any other brand in the sports apparel industry.
What failed first
The custom in-house platform had troubleshooting challenges and concentrated knowledge in a few developers, making it impossible to maintain and iterate once those developers left.
Results
Volume35% higher
Running since2017
Grounding & classification
Source type: vendor customer story
21 fields verified against source quotes.
enterprise searchpersonalizationpredictive analyticsproduct catalogfailure mode describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedretailconversion increaseemployee productivityvendor customer storyecommerce ops