Ecommerce ops · Production

HANOS SHOP provides fast, relevant B2B search and recommendations with Algolia

The problem

Launching a new B2B web shop with over 12,000 non-food products and a diverse customer base spanning many industries and multiple countries, HANOS SHOP needed best-in-class search and recommendation capabilities that could be managed without developer expertise, while also avoiding manual, cumbersome back-end processes for surfacing related products.

Workflow diagram · grounded in source
1
Customer searches or browses
trigger
“Algolia has been implemented through the HANOSSHOP.com search bar, within product pages where it provides recommendations, and within product category pages where customers can filter their selections”
2
AI re-ranks product listings
ai_action
“our product listings are re-ranked based on Search and behavior from our customers”
3
AI generates regional synonyms
ai_action
“AI Synonyms, because we have Dutch customers but also Belgian customers, and they use different words for the same products. The AI Synonyms are automatically generated”
4
Business user approves synonyms
feedback_loop
“I must only click on them to say "OK," and they are automatically added to the product”
5
Fast search results delivered
output
“The search results are within 36 milliseconds”
6
Related products recommended
output
“the Recommend tool is proving to be a key part of creating a great digital experience, offering up relevant related products to customers — a back-end process that would be manual and cumbersome otherwise”
Reported outcome

Algolia delivered search results within 36 milliseconds, earning customer praise for near-instant speed, while the Recommend feature eliminated previously manual and cumbersome processes for surfacing related products, and AI Synonyms automatically reconciled regional terminology differences across markets.

Reported metrics
Search response timewithin 36 milliseconds
Product catalog size12,000+
Implementation timewithin only one and one-half months
Manual processes for related productsElimination of manual processes around related products
Reported stack
AlgoliaRecommendDynamic Re-RankingAI SynonymsAlgolia Filters & Facets
Source
https://www.algolia.com/customers/hanos-shop
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Algolia delivered search results within 36 milliseconds, earning customer praise for near-instant speed, while the Recommend feature eliminated previously manual and cumbersome processes for surfacing related products…

What tools did this team use?

Algolia, Recommend, Dynamic Re-Ranking, AI Synonyms, Algolia Filters & Facets.

What results were reported?

Search response time: within 36 milliseconds; Product catalog size: 12,000+; Implementation time: within only one and one-half months; Manual processes for related products: Elimination of manual processes around related products (source-reported, not independently verified).

How is this ecommerce ops AI workflow structured?

Customer searches or browses → AI re-ranks product listings → AI generates regional synonyms → Business user approves synonyms → Fast search results delivered → Related products recommended.

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