Ecommerce ops · Production

Zeeman improves Search performance and gives customers a 'remarkably simple' experience with Algolia

The problem

Zeeman's website crashed in October 2021 after a popular campaign overwhelmed its existing search engine, causing downtime and revenue loss. The company needed a stable, scalable, and future-ready replacement aligned with its commitment to simplicity.

First attempt

The existing search engine was identified as the root cause of the crash and could not scale under high-traffic conditions, prompting Zeeman to replace it with an external cloud-based solution.

Workflow diagram · grounded in source
1
Website crash triggers search replacement
trigger
“In October 2021, Zeeman's site crashed following a particularly popular campaign. Their previous e-commerce platform couldn't handle the increased traffic the website was receiving, and the root cause was determined to be their existing …”
2
Algolia MVP deployed in two weeks
integration
“Two weeks after signing the minimum viable product (MVP) was already ready to go live”
3
AI Synonyms and Merchandising optimization
ai_action
“train merchandising to develop synonyms in conjunction with AI Synonyms”
4
Search bar placement test
validation
“a small layout change around the placement of its search bar resulted in a notable uptick in conversions and more traffic using search than merely browsing”
5
Algolia Recommend implemented
integration
“The company's most recent implementation is Algolia Recommend, from which they've seen similar performance out the gate without any refinements or improvements and they expect to see great results once they've optimized it more.”
Reported outcome

After deploying Algolia, Zeeman achieved stable and high-performance search across seven countries, with improvements in conversions year-over-year, a notable increase in average order value, reduced cart abandonment, and increased revenue, while eliminating prior downtime issues.

Reported metrics
Conversionsimprovements in conversions year-over-year
average order value (AOV)notable increase in average order value
Cart abandonmentreduction in cart abandonment
Revenueincreased revenue
Show all 5 reported metrics
conversionsimprovements in conversions year-over-year
average order value (AOV)notable increase in average order value
cart abandonmentreduction in cart abandonment
revenueincreased revenue
search-driven conversions from layout testnotable uptick in conversions
Reported stack
AlgoliaAlgolia RecommendMerchandisingAI SynonymsAdobe Commerce (Magento)
Source
https://www.algolia.com/customers/Zeeman
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

After deploying Algolia, Zeeman achieved stable and high-performance search across seven countries, with improvements in conversions year-over-year, a notable increase in average order value, reduced cart abandonment,…

What tools did this team use?

Algolia, Algolia Recommend, Merchandising, AI Synonyms, Adobe Commerce (Magento).

What results were reported?

Conversions: improvements in conversions year-over-year; average order value (AOV): notable increase in average order value; Cart abandonment: reduction in cart abandonment; Revenue: increased revenue (source-reported, not independently verified).

What failed first in this deployment?

The existing search engine was identified as the root cause of the crash and could not scale under high-traffic conditions, prompting Zeeman to replace it with an external cloud-based solution.

How is this ecommerce ops AI workflow structured?

Website crash triggers search replacement → Algolia MVP deployed in two weeks → AI Synonyms and Merchandising optimization → Search bar placement test → Algolia Recommend implemented.