ecommerce_ops · ecommerce · workflow
YourSurprise gains efficiency improvements and search functionality with Algolia
YourSurprise relied on an outdated, over-complicated custom Elasticsearch integration that only one person fully understood, creating a bottleneck where issues were routinely deferred and search optimisation required a ten-person team working country-by-country.
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 search query submitted
Customers submit search queries through the main search bar, individual gift pages, FAQ pages, and category pages.
Tools used
AlgoliaElasticsearchReact
Outcome
YourSurprise reduced its search management team from 10 to 2 people while covering 28 countries, achieved a 9% improvement in conversions, and resolved issues that previously took a day near-instantly.
What failed first
The custom Elasticsearch system had become a single point of failure: only one person in the entire company fully understood it, and that individual's overload created a permanent backlog of unresolved search issues.
Results
Time saved<1 month
Volumefrom 10 to 2 people
Running since2021
Grounding & classification
Source type: vendor customer story
27 fields verified against source quotes.
enterprise searchpersonalizationrecommendation systemknowledge baseproduct catalogfailure mode describedmetric backednamed customerproduction runtime claimedsource backedtools describedworkflow describedecommerceretailconversion increaseemployee productivitytime savedvendor customer storyecommerce opsdata sync enrichment