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.
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.
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.
Frequently asked questions
What did this team achieve with this AI workflow?
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 4…
What tools did this team use?
Algolia, Drupal.
What results were reported?
Global search interactions: 190%; Click throughs from search: six times; No results rate improvement: 100%; Global search navigator usage rate: 35 to 40 percent (source-reported, not independently verified).
What failed first in this deployment?
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 marketin…
How is this ecommerce ops AI workflow structured?
User initiates global search → Products and pricing indexed → Federated content search expanded → Filtered and merchandised results delivered → Monthly analytics review.