AI-POWERED SIZE RECOMMENDATION FOR FASHION E-COMMERCE

AI Size Recommendation Engine (B2B)

Helping fashion retailers reduce returns and build shopper confidence through AI-driven sizing recommendations.

📍 Overview

Role: Product Manager

Timeline: 12 weeks (Concept → Prototype)

User Ecosystem: Retailers (clients) and shoppers (end users)

Goal: Validate the business and user value of AI-driven sizing recommendations

Key Skills: Product Discovery, UX Research, Value Mapping, Go-to-Market Strategy

Outcome: Validated problem space, designed MVP concept, and create a 90-day strategic launch plan.

<aside> 💡 Value Preposition

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Keep customers, not returns.

Reduce costly returns and boost customers' confidence with AI Sizing Engine. By learning the customers purchase and returns histories, measurements, and feedback, brand size data, it delivers accurate, personalized size recommendations. The result? Fewer returns, higher conversion, happier shoppers, and up to 50% power return rate for retailers.

Vision: To be among the top innovators revolutionizing the e-commerce fashion shopping experience through intelligent, data-driven sizing solutions.

Mission: Build the “fit intelligence layer” for fashion e-commerce, where every shopper’s experience feels tailor-made.

Goals: Reduce return rate by 50%.