top of page
Indyx cover.png

Leveraging AI for recommendations based on Kibbe Body Type & Personal Style.

Timeline

8 hours

My Role

Lead designer

Deliverables

High Fidelity Flows, Prototypes, Product Mockups, Process

Project Overview

As part of a passion project, I added a new AI-powered body type recommendation feature to Indyx, a personal styling app that helps users make the most of their existing wardrobe. This feature allows users to either upload photos or take a quiz to identify their Kibbe body type, and then receive AI-powered outfit suggestions based on their body type and wardrobe items.

The goal of the project was to help users better understand their body type and style preferences, curating outfits that flatter their body shape using the pieces they already own. This feature was designed to encourage users to be more intentional with their wardrobe, reduce unnecessary purchases, and make the most out of what they already have.

Context

The idea for this project arose from conversations with friends about how difficult it can be to shop for clothing that flatters our individual body types. I realized that while many styling apps recommend outfits based on style or trends, they often overlook how body shape affects what looks good on a person. The Kibbe body type system provides a framework for understanding what kinds of clothing best suit different body types, and I saw an opportunity to integrate this system into Indyx to create more personalized styling recommendations.

I wanted to help users not only discover their body type but also use the clothes they already own to create outfits that fit their body shape, making it easier to shop mindfully and style themselves confidently.

Discovery and Competitive Analysis

I began by analyzing other popular styling apps, such as Cladwell and Style AI. These apps allowed users to upload clothing items and receive outfit suggestions, but none of them incorporated body type as a factor in styling recommendations. Cladwell even provided insights into your style preferences, but again, it did not address how body type plays a significant role in choosing flattering outfits.

This gap in the market led to the idea of integrating body type analysis to enhance the app’s existing features and provide more personalized styling recommendations.

Ideation and Design

Once the concept was established, I began sketching wireframes and exploring user flows to visualize how users would interact with the new features. After ideating, I created low-fidelity mockups to represent the core idea and then moved on to high-fidelity mockups that showcased the final design.

These mockups focused on the steps a user would take to identify their body type and receive personalized recommendations based on their wardrobe items.

Design Execution

The final design includes:

  • Photo Upload Feature: Users can either upload photos or take a quiz to determine their body type.

  • Body Type Analysis: Once the user provides their information, the AI analyzes their body type (based on the Kibbe system) and generates personalized outfit recommendations using the clothes they have already uploaded.

Frame 20.png

The new INDYX STYLE AI section shows two features leveraging AI for outfit recommendations.

Frame 21.png

The journey a user can take to upload a picture for AI's suggestions based on body type.

Frame 22.png

The recommendations can be found when a filter is applied and easily accessible to the user under collections.

Challenges faced and User reactions

  • AI Accuracy & Body Type Analysis:

    • One challenge was ensuring the AI accurately identifies the user’s body type based on the uploaded photos. AI models are continuously learning, and while the system performs well, it may need to refine results over time based on user feedback.

  • Quiz Complexity:

    • The Kibbe system includes specific terminology for body shapes, and it was essential to make sure the quiz was easy for users to navigate. I focused on clear instructions and visual aids to guide users through the process of determining their body type.​

      While the Kibbe system is generally well-received, some users may feel surprised by the results. To mitigate this, I ensured that there was an alternative feature for users to explore outfit suggestions based on their personal style preferences, which will follow soon, in the next iteration.

Results

After presenting the prototype of the body type recommendation feature, I tested it with a group of 5 users. All 5 users responded very positively, expressing excitement about the idea of receiving tailored outfit recommendations based on their body type. They were particularly thrilled by the ability to discover new outfit combinations from the clothes they already owned. The prospect of future iterations that would incorporate both body type and personal style was also highly anticipated. Users were eager for this feature to be implemented in the app, as they saw great potential in using AI to create more personalized styling advice without having to buy new clothes.

bottom of page