Project Overview

I worked at FitFlex as a UX Researcher, which is an eCommerce clothing app. The app's goal is to help people find their perfect fits from clothing shops such as: (Shein, Fashion Nova, Pretty Little Thing, etc). All they need to do is input their size and select if they like a tighter fit or a looser fit, to get a selection of clothes that will be their perfect fit.  As a researcher, I work on the company's B2C side, but there is also a relevant B2B aspect.Today, I will talk to you about a project we did to better understand the personas on our platform and their top usability issues.

My Role

Working on this project, I was the only qualitative user researcher. I lead all of the interviews, and the end-to-end process, such as recruitment, synthesis, and workshops. The project had come from a road mapping session the product team had done. I was part of that session, so I had a lot of background knowledge. However, I had them fill out a research request template. This helped me prioritize the project against other requests coming in, as it was a company priority.

Research statement and Role

We wanted to better understand ”How do users think about ordering clothes online?" and, “How do they interact with our product?” to improve our app's experience?

• Accurately Measure and Fit Clothing:

  The app should use advanced technologies such as computer vision or machine learning, to provide accurate measurements and fit recommendations to users. This will help users to find clothes well and feel comfortable, reducing the likelihood of returns or exchanges.

  
  

• Enhance User Experience: 

  The app should be easy to use and intuitive, with a clear interface the guides uses through the process of measuring and fitting clothes. It should also provide helpful tips and suggestions to users, such as recommending complementary clothing items or providing styling advice.

  
  

• Increase Customer Engagement and Loyalty: 

  The app should provide a personalized experience for each user, allowing them to save their measurements and preferences for future shopping experiences. Adding some incentives such as Loyalty rewards, discounts, or exclusive promotions can also help with engagement.

Design Process

Research and Discovery

Objective: Understand the market, user needs, and current solutions.

• Market Analysis: Analyzed existing eCommerce clothing apps to identify strengths, weaknesses, and gaps. Focused
  on popular platforms such as Shein, Fashion Nova, and Pretty Little Things

• User Research: Conducted surveys and interviews with potential users to understand their pain points, preferences,
  and behaviors regarding online clothing shopping.

• Competitive Analysis: Studied competitors to understand their design patterns, features, and user experiences.

Key Insights:

• Users struggle with finding the right fit and often return items.

• Users desire a simplified and personalized shopping experience.

• Fit preference (tighter or looser) is a significant factor in purchasing decisions.

Define and Ideate

Objective: Define the app’s core functionalities and ideate on potential solutions.

• User Personas: Created detailed personas representing different segments of the target audience (e.g.,size-conscious shoppers, fashion enthusiasts).

• User Journeys: Mapped out user journeys to understand how users would interact with the app from start to finish.Feature Brainstorming: Ideated on features such as size input, fit preference selection, personalized recommendations, and seamless integration with partner shops.

Wireframing

Objective: Develop low-fidelity wireframes to outline the app’s structure and layout.

• Sketching: Started with rough sketches to explore different layout ideas and flows.

• Wireframes: Created low-fidelity wireframes in Figma to establish the app’s structure, focusing on key screens like onboarding, size input, fit preference selection, and product recommendations.

Key Insights:

• Onboarding: Introduction to the app and its benefits.

• Size Input: A simple interface for users to input their measurements.

• Fit Preference: Options to select tighter or looser fit preferences.

• Product Recommendations: A personalized feed showing clothes that match the user’s size and fit preferences.

  
  

Prototyping

Objective: Develop high-fidelity prototypes to visualize the final design.

• Design System: Created a design system in Figma to ensure consistency across the app, including typography, color
  palette, and UI components.

• High-Fidelity Prototypes: Developed high-fidelity prototypes in Figma, adding visual details, branding elements, and
  interactive components.

Interactive Features:

• Filter and Sort: Allow users to filter and sort products based on various criteria (e.g., price, brand, style).

• Product Details: Detailed product pages with size and fit information, reviews, and high-quality images.

• Wishlist and Cart: Easy-to-use wishlist and cart functionalities for seamless shopping.

Usability Testing

Objective: Validate the design with real users and gather feedback for improvements.

• Test Plan: Developed a test plan outlining the goals, tasks, and metrics for usability testing.

• User Testing: Conducted usability tests using UserTesting with a diverse group of participants. Focused on key tasks
  such as entering size, selecting fit preference, and browsing recommendations.

• Feedback Analysis: Analyzed feedback to identify pain points, confusion, and areas for improvement.

Key Findings:

• Users appreciated the simplicity of the size and fit input process.

• Some users requested more detailed size guides and fit descriptions.

• The personalized recommendation feature was highly praised but needed better filtering options.

Outputs and Deliverables

I summarized the key takeaways and pain points we were finding. In this report, I included videos and links to more information. This also included a new persona, I chose user personas because, before this project, the teams had little understanding of who was using our product and why. These personas enabled them to have a better understanding of what should be prioritized going towards our next stages.

Technical Complexity

We needed a good understanding about what the actual level of technical complexity FitFlex can presumably be.

I made a list of some of the aspects of the technical compartments that would need FitFlex, then drew a conclusion of the level of complexity.

1. Integration with eCommerce Platform: 

   FitFlex eCommerce app needs to be seamlessly integrated with eCommerce platform to provide users with a complete shopping experience. This requires technical expertise in API integration, payment processing, and and inventory management

   
   

2. User Interface and Experience: 

   The user interface and experience of FitFlex app needs to be easy to use and intuitive, with clear instructions for users on how to take measurements, choose clothing options, and make purchases. This requires user experience design and usability testing.

   
   

3. Image Processing:

   Accurate display of clothing options to users. This involves using specialized algorithms to ensure that clothing images are displayed accurately, with the right color, textures, and details. In conclusion, the FitFlex app involves several technical complexities, which is a high level.