recommendation ai
integrate an AI-powered product recommendation system across key pages of Benetton's eCommerce platform to improve conversion rate, reduce friction in the shopping funnel, and increase user engagement.
my role
Senior UX/UI Designer – Leading the UX strategy and design execution.
I collaborated with the analytics agency, developers, and product owners to ensure seamless integration of the recommendation module.
Tools: Figma - Hotjar - Analytics - Adobe
key responsibilities
⟶ Heuristic evaluation of high-traffic pages (Homepage, PDP, Listing, Cart)
⟶ Identification of friction points using user behavior data (Hotjar, GA)
⟶ Redesign of strategic pages to include the AI module
⟶ Definition of A/B testing roadmap
⟶ Weekly analysis review with performance analytics partner
⟶ Supervision of UX implementation and iterative design adjustments
design process
ux approach
Heuristic Evaluation: Selected pages were evaluated according to international usability heuristics to identify usability violations and areas of improvement.
Each issue was rated on a severity scale from 1 (minor) to 3 (critical), based on impact on the user journey.
Data-Driven Insights: Analytics and sales data were used to prioritize interventions with the greatest impact. Quick-win opportunities were identified based on performance gaps.
strategic placement
Slider prediction ai models
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Results
+36% Transactions/visits to Checkout
+1% PDP pageviews
-1% Bounce rate
heatmaps results
Scroll: over 75% of users reached the recommendation module compared to the 50% for the previous design
