ZaraFit
AI-powered virtual Try-on tool for Zara shoppers to find the perfect fit before making a purchase.
Product Experience
Problem Statement
How might we improve Zara's online shopping experience to minimize the number of returns related to incorrect sizing?
Problem Background
Since the beginning of the pandemic in 2020, online shopping has surged, and customers are increasingly looking for ways to simulate the in-store experience virtually. Many online shoppers struggle with choosing the correct size, leading to higher returns and customer dissatisfaction.
Research Insights
User Pain Points
A survey of seven Zara shoppers highlighted a shared frustration: inconsistent sizing makes finding the right fit a challenge. Without a reliable virtual try-on solution, shoppers rely on guesswork, size charts, and reviews—none of which ensure accuracy. This results in frequent returns, wasted time, and a disappointing shopping experience, ultimately diminishing confidence in online shopping.
Supporting Data
72% of surveyed shoppers expressed dissatisfaction with the current online shopping experience, citing fit and size accuracy as major pain points.
85% of participants reported returning items due to poor fit.
Feedback
The key feedback included:
- Sizing inconsistency: Shoppers found Zara's sizing unpredictable, making it difficult to choose the right fit.
- Lack of personalization: Many participants felt that size charts and general recommendations didn’t account for individual body shapes.
- High return rates: Almost half of the participants mentioned frequently returning items due to poor fit, leading to frustration.
- Desire for a better solution: Most participants expressed interest in a tool that could provide a more accurate, personalized size recommendation.
Landing on the Solution
Based on our target users’ pain points, we knew we wanted to work on the following features to enhance the Zara online shopping experience:
- AI-Powered Virtual Try-On: Allow shoppers to visualize how a garment fits on a model based on their unique body parameters (height, bust, waist, hips).
- Personalized Size Recommendations: Use AI and past shopping data (purchases, returns, and preferences) to suggest the most accurate size for each user.
- Fit Comparison Tool: Enable users to compare different sizes side by side on a 3D model, helping them make more confident decisions.
- Personalized 3D body model generation based on user input (height, bust, waist, hips).
- Size comparison tool to help users switch between different sizes.
- Fit recommendation system using AI to suggest the best fit for each user.
Explanation of Solution
After we showcased our prototype to the users again, we learned that they were more likely to engage with the feature when it offered an immediate comparison between different garment sizes and provided personalized fit recommendations. This allowed them to feel more confident in their purchase decisions.
User Flows
Entry point - Product Page
- User browses Zara’s website or app and selects a product.
- They see a "Try It On" button next to the size selection.
2. Input Body Parameters
- Users are prompted to enter key measurements: height, bust, waist, hips.
- Option to save these details for future purchases.
3. AI-Generated Virtual Try-On
- A 3D model appears, dynamically adjusting to the user’s body shape.
- Garment is displayed on the model with realistic fit, drape, and stretch.
4. Compare Fit Across Sizes
- Users can toggle between different sizes (e.g., S, M, L) to compare fit.
- Color-coded fit indicators highlight areas that may be too tight or loose.
5. Personalized Size Recommendation
- AI suggests the best size based on past purchases, and fit preferences.
- A confidence score (e.g., "90% match") is displayed for reassurance.
6. User Decision & Checkout
- User selects the recommended size and adds the item to their cart.
- Option to save fit preferences for future shopping.
7. Post-Purchase Feedback Loop
- After receiving the item, the user is prompted to rate the fit.
- Feedback is used to continuously improve AI recommendations.
Future Steps
We identified these opportunities from speaking to customers
- Users love the ability to compare sizes and see how garments fit on a 3D model that reflects their body shape.
- There is a desire for even more personalization in the virtual try-on experience, such as color preferences and fabric textures.
- Integrating the feature with Zara’s existing mobile app for seamless AR try-ons.
- Expanding the body parameters to include more detailed customization options such as arm length and inseam
- After launching, success will be tracked by the percentage decrease in returns due to sizing issues over time and a comparison of return rates between ZaraFit users vs. non-users
Images
Learnings
Product Manager Learnings:
Toyin Obaja
CoLab was an eye-opening experience for me. Over the past few weeks, I’ve learned that cutting-edge AI technology can effectively solve real customer pain points, like sizing uncertainty and inconsistent fit. I also discovered that success in product development relies on an iterative approach, embracing continuous learning and adaptability to meet evolving customer needs and market trends. Most importantly, I learned that feedback is the driving force behind continuous improvement.
Designer Learnings:
Designer Learnings:
Jo Sturdivant
- Adapting to an Established Team: Joining the team in week 6 of 8 was challenging, as I had to quickly adapt to existing workflows, dynamics, and goals. This mirrors real-world situations where you often integrate into teams mid-project, and flexibility is essential.
- Work-Blocking for Efficiency: With only two weeks to complete the project, I learned the importance of a structured work-blocking system. This approach allowed me to manage my time effectively and meet deadlines under pressure.
- Making Data-Driven Design Decisions: Unlike my past projects, I had to rely on research conducted by others. This was a valuable experience in using pre-existing data to guide design decisions, helping me focus on the core insights without starting from scratch.
Developer Learnings:
Developer Learnings:
Vanady Beard
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As the back-end developer, I learned how important it is to create efficient and reliable systems that support the entire application. This experience also taught me the importance of optimising the database and ensuring the backend is scalable and easy to maintain.
Developer Learnings:
Stephen Asiedu
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As a back-end developer, I've come to understand the importance of being familiar with various database systems and modules. This knowledge enables me to build diverse applications and maintain versatility in my work. I've also learned that the responsibility for making the right choices rests on my shoulders, guided by my best judgement.
Developer Learnings:
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Developer Learnings:
Maurquise Williams
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- Process of Creating an MVP: Developing a Minimum Viable Product (MVP) taught me how to focus on delivering core functionalities balancing between essential features and avoiding scope creep.
- Collaboration in a Real-World Tech Setting: This experience taught me how to collaborate efficiently in a fast-paced tech environment, keeping the team aligned and productive, even while working remotely across time zones.
- Sharpening Critical Thinking and Problem-Solving Skills: This experience honed my ability to think critically and solve problems efficiently. By tackling challenges and finding quick solutions, I sharpened my decision-making and troubleshooting skills in a dynamic, real-world setting.
Developer Learnings:
Jeremiah Williams
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All in all this experience was very awesome I learned that in coding with others being transparent is key
Developers Learnings:
Justin Farley
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I learned how important communication is when working with a team. Communication provides understanding, advice, ideas, and much more. While working with the product team, I’ve found that communication keeps everything flowing smoothly. Working with a team also showed me that every member brings something different to the table and we all have to work together in order to align and meet our end goal.