Shopify & personalization · France
Adapt recommendations from a 1,000-product catalog to each customer
A proprietary questionnaire turns visitor answers into personalized Shopify recommendations while supporting commercial follow-up.
+12%
conversion through the personalized recommendation journey
The operating point we started from
A large catalog makes choice difficult and exposes every visitor to the same products. Yuli wanted to guide each person toward a selection aligned with their answers and retain contact details for follow-up.
The system engineered by Nexxom
- 01Define questions and answers relevant to recommendations
- 02Map each answer to product attributes and families
- 03Combine signals to rank suitable products
- 04Embed results in the Shopify journey
- 05Collect consented email addresses for follow-up
Shopify
Recommendation algorithm
Marketing automation
How information moves through the architecture
Questions
Visitor preferences
01
Signals
Attributes inferred from answers
02
Algorithm
Catalog ranking
03
Selection
Suitable products in Shopify
04
Follow-up
Consented email and sales activity
05
What the project makes visible
+12%
conversion on the questionnaire journey
≈ +9%
average order value for guided visitors
≈ +25%
qualified contacts available for email follow-up
≈ 1,000
products covered by the recommendation logic