Introduction

With rising online apparel return rates—especially in China where returns are among the highest globally—consumers demand more accurate and efficient ways to visualize and select clothing online. This project addresses these challenges by constructing a preliminary user mental model for a 3D Virtual Fitting Room. Through integrated 3D modeling, smart outfit recommendations, and enhanced user interaction, the goal is to optimize the shopping process, improve decision-making efficiency, lower return rates, and boost user satisfaction and loyalty.

Methods

  • Product Analysis:

    • Explored 3D virtual fitting room functions: high-precision body modeling, real-time try-on visualization, smart outfit recommendations, interactive wardrobe management, and community features
    • Assessed technical advantages, brand partnerships, and the ability to visualize every clothing detail

  • User Persona Development:

    • Profiled target users from first- and second-tier Chinese cities, aged 20–30, with varying online apparel shopping proportions and moderate to high consumption levels
    • Identified behavioral traits: openness to new shopping experiences, high standards for clothing quality and style, proficiency in mobile/social apps, and a blend of emotional and rational shopping motives

  • User Mental Model Construction:

    • Form: Users expect a modern, intuitive interface that clearly presents virtual fitting effects.
    • Function: Features include easy data import, multiple body/wardrobe profiles, adjustable try-on settings, and one-click data saving and sharing.
    • Content: Rich information on fabric, brand, care instructions, personalized wardrobe analytics, outfit analysis reports, and community sharing.
    • Behavior: Guided onboarding, separation of simple and advanced operations, intelligent data completion, 360° garment viewing, instant feedback and recommendations, and seasonal outfit reminders.

  • Usability Testing Scenarios:

    • Designed realistic user tasks to evaluate onboarding, shopping decision support, and wardrobe management:
      • Creating a personal avatar and importing body data
      • Using e-commerce integration for direct try-on from product pages
      • Receiving smart fit and style suggestions
      • Managing wardrobe records and analyzing outfit compatibility

Results & Conclusion

  • Preliminary Mental Model:
    Developed a user mental model based on four dimensions—form, function, content, and behavior—ensuring the system aligns with real user expectations in virtual apparel shopping

  • Key Insights:

    • Users value intuitive interfaces, detailed try-on effects, and seamless integration with online shopping platforms.
    • Smart recommendations and virtual wardrobe management enhance decision-making and satisfaction.
    • Community and sharing features foster engagement and social shopping behaviors.
    • The model supports optimizing shopping experiences, lowering return rates, and driving innovation in online fashion retail.

My Contributions to the Project

  • Led user research, persona creation, and needs analysis
  • Constructed the user mental model framework and mapped it to core product features
  • Designed usability testing scenarios reflecting real-world shopping flows
  • Summarized findings into actionable recommendations for product and UX design