Ecommerce ops · Production

Under Armour achieves 35% higher conversion rate with Algolia search

The problem

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.

First attempt

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.

Workflow diagram · grounded in source
1
Customer initiates search
trigger
“most customers start their journey on a company's website — usually in the search bar”
2
Type-Ahead predicts intent
ai_action
“Type-Ahead dynamically predicts users' search intent and returns the most relevant results after each of their keystrokes, allowing Under Armour to provide near-instant search results to their website visitors to support a fast, relevant…”
3
Query Rules rank results
ai_action
“Under Armour used Algolia's Query Rules feature to customize their rankings based off their products' popularity, newness, and availability”
4
Analytics uncovers no-result queries
feedback_loop
“With the Analytics Dashboard, Under Armour was able to uncover the most common queries that returned no results, a reason why people bounce from Under Armour's website. This insight helped Under Armour return relevant search results for …”
5
Rankings refined via testing
feedback_loop
“Under Armour was able to test which products they thought their customers wanted and refine their rankings based on the experiment's outcome”
Reported 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.

Reported metrics
Conversion rate for search users35% higher
Reported stack
AlgoliaType-AheadQuery RulesAnalytics DashboardInstantSearch
Source
https://www.algolia.com/customers/under-armour
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

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 tools did this team use?

Algolia, Type-Ahead, Query Rules, Analytics Dashboard, InstantSearch.

What results were reported?

Conversion rate for search users: 35% higher (source-reported, not independently verified).

What failed first in this deployment?

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.

How is this ecommerce ops AI workflow structured?

Customer initiates search → Type-Ahead predicts intent → Query Rules rank results → Analytics uncovers no-result queries → Rankings refined via testing.

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