Ecommerce ops · Production

Harry Rosen achieves 360% conversion rate increase with Algolia omnichannel search

The problem

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.

First attempt

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.

Workflow diagram · grounded in source

ERP data fed to Algolia index

integration

“Data is sent from Harry Rosen's enterprise resource planning (ERP) system as custom ranking attributes for Algolia to rank results sets based on product performance across the entire enterprise, not just based on online performance”

Associate or customer initiates search

trigger

“Algolia is allowing Harry Rosen associates and advisors to search clothing based on attributes, based on sizes, and stock availability in specific stores”

Personalization and Dynamic Re-Ranking

ai_action

“Using a combination of A/B Testing and Personalization features, Harry Rosen has been able to determine the best conditions to give the best search results to improve click-through-rates or conversions”

Layered rules engine applied

validation

“its ability to have multiple rules that can "trigger independently or layered together". he use the example of searching by store, or size, or attribute — or all three in a single query”

Personalized results delivered

output

“Harry Rosen uses Algolia for its clienteling application, dubbed Herringbone, which it uses internally to search for both product and client data and then send out personalized curated product assemblies”

Conversion events feed back to Algolia

feedback_loop

“Harry Rosen can feed into Algolia conversion events such as "add to Wishlist" and "add to cart", so they are incorporating different milestones in the customer journey”

Reported 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.

Reported metrics

Conversion rate increase360%

Transactions increase68%

online sessions using Search2x

Average order value increase18%

Reported stack

AlgoliaHerringbonecommercetoolsSAP HybrisSolrAmplienceNext.jsERPOriumTalon.OneDynamic Yield

Source

https://www.algolia.com/customers/harry-rosen

Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

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…

What tools did this team use?

Algolia, Herringbone, commercetools, SAP Hybris, Solr, Amplience, Next.js, ERP, Orium, Talon.One.

What results were reported?

Conversion rate increase: 360%; Transactions increase: 68%; online sessions using Search: 2x; Average order value increase: 18% (source-reported, not independently verified).

What failed first in this deployment?