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Product Management Improvement Question: Enhancing virtual try-on accuracy for online fashion shopping

How can we enhance Zalando's virtual try-on feature to make it more accurate and user-friendly?

Product Improvement Medium Member-only
User-Centric Design Feature Prioritization Data Analysis E-commerce Fashion Retail Technology
User Experience Product Improvement E-Commerce Fashion Tech Virtual Try-On

Introduction

Enhancing Zalando's virtual try-on feature to make it more accurate and user-friendly is a critical initiative that could significantly impact user experience and conversion rates. This improvement aligns with the growing trend of augmented reality in e-commerce and addresses the persistent challenge of fit and style uncertainty in online fashion shopping. I'll approach this problem by first clarifying the context, then analyzing user segments and pain points, before proposing and evaluating solutions.

Step 1

Clarifying Questions

  • Looking at the current market trends, I'm seeing increased adoption of AR technologies in e-commerce. Could you share some insights on how our virtual try-on feature compares to competitors in terms of user engagement and conversion impact?

Why it matters: Helps prioritize areas for improvement and benchmark our performance. Expected answer: Our feature has good engagement but lower conversion impact compared to leaders. Impact on approach: Would focus on improving accuracy and user trust to drive conversions.

  • Considering the complexity of fashion items, I'm curious about the technical foundation of our current virtual try-on feature. What type of technology are we using (e.g., 2D overlay, 3D modeling, or AI-driven simulation), and what are its current limitations?

Why it matters: Determines the scope of potential improvements and technical constraints. Expected answer: Using AI-driven 3D modeling with limitations in fabric physics and body diversity. Impact on approach: Would prioritize improvements in these specific areas.

  • Given the importance of user data in personalizing experiences, I'm wondering about our current data collection and usage practices. What kind of user data are we currently leveraging for the virtual try-on feature, and are there any privacy concerns or regulations we need to consider?

Why it matters: Influences the extent of personalization possible and potential ethical considerations. Expected answer: Collecting basic body measurements and style preferences, adhering to GDPR. Impact on approach: Would explore ways to enhance personalization while maintaining privacy.

  • Considering Zalando's position as a multi-brand retailer, I'm curious about our relationships with brand partners. How are brands currently involved in the virtual try-on process, and what opportunities exist for deeper collaboration?

Why it matters: Affects the scope of improvements and potential for brand-specific enhancements. Expected answer: Limited brand involvement, mostly providing product images and measurements. Impact on approach: Would explore ways to integrate brand-specific data and styling recommendations.

Tip

Now that we've clarified the context, let's take a brief moment to organize our thoughts before moving on to user segmentation.

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