ecommerce_ops · manufacturing · workflow
Swedol grows conversions 22% and time on site 26% after switching to Algolia AI Search
Swedol's previous e-commerce search solution lacked flexibility and relevancy, required development tickets for any change, offered no self-serve dashboard, and generated persistent internal complaints that 'the search is terrible.'
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 or sales rep browses site
Customers and internal sales team members browse products and search on Swedol's online store.
Tools used
AlgoliaDynamic Re-RankingAdobe Commerce
Outcome
After switching to Algolia, Swedol's customers spend 26% more time on site, searches increased 7.5%, and the conversion rate rose 22%, directly translating to an increase in revenue.
Results
Time saved26% more
Volume7.5% increase
Cost replacedincrease in revenue
Running since2019
Grounding & classification
Source type: vendor customer story
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enterprise searchpersonalizationrecommendation systemproduct catalogfailure mode describedmetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedmanufacturingretailconversion increasecustomer satisfactionrevenue increasethroughput increasevendor customer storyecommerce opssales opsdata sync enrichmentextract classify route