ecommerce_ops · manufacturing · workflow
Industrial safety gear company improves search speed and relevance with Algolia
Ergodyne's Magento site with Solr search was slow, required heavy developer involvement for configuration changes, and couldn't adequately serve its wide mix of B2B users — distributors, sales reps, and end customers — who needed both product search and content resources.
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 · User initiates global search
Thirty-five to forty-five percent of site visitors use the global navigation search to find products and content.
Tools used
Algolia
Outcome
After adopting Algolia, Ergodyne saw a 190% increase in global search interactions, six times the number of click throughs, and a 100% improvement in no-results rates, with the global search navigator now used 35 to 40 percent of the time.
What failed first
Solr on the Magento platform could not deliver the multi-faceted search capabilities needed for Ergodyne's diverse B2B customer base without ongoing, resource-intensive developer effort from its small digital marketing team.
Results
Volume190%
Running since2018
Grounding & classification
Source type: vendor customer story
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enterprise searchpersonalizationrecommendation systemknowledge baseproduct cataloghuman review describedmetric backednamed customerproduction runtime claimedsource backedtools describedworkflow describedmanufacturingaccuracy improvementcustomer satisfactionthroughput increasevendor customer storyecommerce opsdata sync enrichment