Bodygram
Bodygram | 2022-2024 | UX Designer
Vision & OKR Planning, Strategy, Concept, Design workshop facilitation, Research, Cross-functional collaboration, Rapid prototyping, Client communication
Bodygram offers unique technology to easily and accurately acquire 30+ body measurements. Users simply take two photos of themselves, from the front and back, with their smartphone and upload them. AI then instantly returns their body measurements.
Problem
Online Shoppers
Online shoppers often struggle with selecting the right clothing size. While they may have a rough idea of their size, they're unsure because everyone’s body is unique, and each shop has its own fit. As a result, shoppers often end up returning clothes because they don’t fit or they don’t like how they fit. Size is one of the top reasons for returns, just like poor materials.
Apparel Businesses
For apparel businesses, handling returns is costly—receiving returned items, refunding shoppers, inspecting products, and more. Additionally, many businesses in the apparel industry are not tech-savvy, making it difficult for them to find efficient ways to communicate clothing sizes in their online stores.
Bodygram
Bodygram needed a size recommendation product that was easy for clients to integrate in order to scale the business. At the time, there were only a few custom products built for specific clients. If other clients wanted to use the product, a new one had to be built while maintaining the existing products.
Additionally, the UX for the body scan flow, where users take and upload photos, was not well thought out. Improving the body scan flow to make it easier for users to perform the scan became one of the top priorities.
38%
38% of returns were caused by size issues. Size was the top reason for returns.
Approach
To address this issue, Bodygram decided to develop a universal size recommendation service aimed at boosting shopper confidence while minimizing integration costs for businesses. This streamlined approach replaced Bodygram's previous custom products, allowing for broader adoption and greater efficiency.
I began creating the concept for the universal product while ensuring consistency with the features of existing products. I also focused on optimizing the experience for online shoppers to find their size, taking both internal and external feedback into consideration.
The goal of the size recommendation was to help users successfully select the right size and purchase clothes. The experience needed to be quick and easy, so users wouldn’t spend too much time on the size recommendation process.
Competitive Analysis
I conducted a competitive analysis to gain insights into the needs and pain points of online shoppers in both the US and Japan. Overall, competitors ask for more user input across multiple screens than Bodygram in order to personalize the recommendations.
Key Takeaways
Most online size recommendation products consider only the product size.
The recommended size is not as personalized as Bodygram's.
Competitors ask users to provide input on their body size, such as height, weight, age, and gender, as well as details about their body shape, like whether their belly is flat, average, or rounded, in order to personalize the body information.
Competitors also ask about the size of clothes the shoppers already own, including the brand, product, and the size they wear.
They display the recommended size with visuals, such as illustrations of the clothes on top of a body, or the probability of the recommended size.
Prototype
I hypothesized that the value proposition of Bodygram lies in its personalization, accuracy, and ease of use. I quickly created two versions of the design, as there were two options for users to receive size recommendations. One was based solely on height, weight, age, and gender, while the other required two photos in addition to this information. I also redesigned the body scan flow to simplify the instructions for uploading the photos.
I shared the two ideas with the product and engineering teams to discuss not only the user experience, but also technical feasibility and competitive advantages. Based on the discussion, I updated the prototype to gather user feedback.
User Research
I conducted user surveys and competitive analyses to gain insights into the needs and pain points of online shoppers, as well as the competitive landscape. Building on these findings, I conducted user interviews with a prototype in both the US and Japan.
Key Takeaways
Users found the size recommendations helpful.
There were two methods: one based on simple user input and the other requiring user input along with two photos. Users preferred the user-input-based recommendations due to their ease of use.
Although they perceived the photo-based recommendations to be more accurate, they felt it required too much effort.
MVP
Based on insights from user interviews, I have completed the design refinement process. I proposed two solutions: one involves offering size recommendations based on both data and user input, while the other enhances recommendation quality by analyzing user input along with photos.
MVP Result
The MVP was successfully built, and the existing product was successfully migrated to the new experience. Since then, we have successfully onboarded clients, including some of Japan's top brands, and American brands have also started considering the use of this solution.
V2 Design Workshop
To improve and acquire more clients, I facilitated a design workshop with the team to brainstorm enhanced user experiences. I proposed UX improvements both internally and externally, gaining agreement from our team and clients on these changes. Additionally, I conducted further user interviews specifically focused on the photo experience.
V2 Iteration
Improvements
We continuously improved the experience while closely collaborating with our clients. When we implemented the updates, I explained the UX changes and answered clients' questions in client-facing meetings, as well as in the documentation.
Design Customization Guidelines
Additionally, I set up guidelines for customizing the UI's visual design to align with each apparel business's brand identity, ensuring a consistent brand experience. During the creation of the customization system, I closely collaborated with engineers and clients to balance the clients' needs, system maintenance costs, and a consistent experience for other customers.
V2 Result
UI customization was one of the blockers for some clients, such as Adastria, the second-largest apparel brand in Japan, preventing them from adopting Bodygram in their native application. We also partnered with another major brand to test the in-store size recommendation with a tablet.
The new features, including visual design customization, unblocked the sales pipeline, allowing the team to reach out to more clients, not just in Japan, but also in the US.
On the other hand, we started receiving more client feedback, including feature requests and complaints about the recommended size, etc. I also conducted several rounds of user interviews to validate new ideas and understand user pain points more deeply. We continued to incorporate feedback from both clients and users to improve the size recommendation experience.