
eXenSa is developping an e-commerce recommendations solution : eXenSa SalesAdviser. It serves to automate up-selling / cross-selling and other personnalization of a e-commerce site. Recommendations is a must have for any serious e-commerce business. In a typical retailer site, recommendations can drive between 25 and 45% of the sales, and because they allow a customer to find more quickly the products that fits their needs, it can boost e-commerce revenues by 10-25%. eXenSa has its origin in a new data-mining algorithm able to make very relevant inference from text data AND from usage data. It also allows to combine one's salesmen knowledge with the empiric data of a site's visitors, and will even allow recently added products to appear in recommendations thanks to its semantic understanding of products descriptions.

eXenSa is developping an e-commerce recommendations solution : eXenSa SalesAdviser. It serves to automate up-selling / cross-selling and other personnalization of a e-commerce site. Recommendations is a must have for any serious e-commerce business. In a typical retailer site, recommendations can drive between 25 and 45% of the sales, and because they allow a customer to find more quickly the products that fits their needs, it can boost e-commerce revenues by 10-25%. eXenSa has its origin in a new data-mining algorithm able to make very relevant inference from text data AND from usage data. It also allows to combine one's salesmen knowledge with the empiric data of a site's visitors, and will even allow recently added products to appear in recommendations thanks to its semantic understanding of products descriptions.
Product: eXenSa SalesAdviser — e-commerce recommendations for up‑/cross‑selling and personalization
Tech: Data‑mining algorithm combining text (semantic) and usage data
HQ / launch: Montrouge, France; activity dating to 2011
Team size (reported): Approximately 2–10 employees (profiles report small team; one snapshot lists 4)
Funding signal: Small historical funding entries including a Dec 2011 round and a Sep 2019 Eurostars grant; total funding reported in one snapshot: 190000 USD (last funding date 2011-12-02)
E‑commerce personalization, up‑selling and cross‑selling through recommendation systems
2011
E‑commerce / Machine Learning
190000.00
Listed last funding date and amount in company snapshot
Dealroom shows a Dec 2011 round marked N/A
Dealroom lists a Sep 2019 Eurostars SME programme grant