ecommerce_ops · ecommerce · workflow
Harry Rosen achieves 360% conversion rate increase with Algolia omnichannel search
Harry Rosen's e-commerce merchandising required heavy developer involvement and business users could not control the search experience; the company's existing tech stack served only the online channel in isolation from in-store operations.
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 · ERP data fed to Algolia index
Data is sent from Harry Rosen's ERP system as custom ranking attributes for Algolia to rank results based on product performance across the entire enterprise.
Tools used
AlgoliaHerringbonecommercetools · partnerSAP HybrisSolrAmplienceNext.jsERP
Outcome
Harry Rosen achieved a 360% increase in conversion rate, 68% increase in transactions, 2x online sessions using search, and 18% increase in average order value, while empowering business users to manage merchandising without developer involvement.
What failed first
Harry Rosen's previous search was a Solr index bundled with its SAP Hybris platform; merchandising changes required developer coding and business users had no self-service control.
Results
Volume360%
Running since2019
Grounding & classification
Source type: vendor customer story
31 fields verified against source quotes.
enterprise searchpersonalizationproduct catalogfailure mode describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedretailconversion increaseemployee productivityrevenue increasethroughput increasevendor customer storyecommerce opssales opsdata sync enrichment