ecommerce_ops · ecommerce · workflow
MadeiraMadeira enhances customer experience and boosts revenue with Algolia Search
MadeiraMadeira's existing search engine was too slow and insufficiently relevant for its expansive product catalog, undermining the digital-first customer journey the company depended on for growth.
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 initiated
Customers enter queries across search bars and category pages on the website and mobile app.
Tools used
Algolia SearchDynamic Re-RankingQuery CategorizationA/B TestingAlgolia Recommend
Outcome
Adopting Algolia Search with Dynamic Re-ranking and A/B Testing improved click-throughs, conversions, and revenue, with A/B tests confirming that removing Dynamic Re-ranking caused a major decrease in CTR, CVR, and sales.
Results
Cost replacedgrowing revenue
Running since2019
Grounding & classification
Source type: vendor customer story
28 fields verified against source quotes.
personalizationrecommendation systemproduct catalogfailure mode describedmetric backednamed customerproduction runtime claimedtools describedvendor confirmedworkflow describedecommerceconversion increasecustomer satisfactionrevenue increasevendor customer storyecommerce opsextract classify route