Bodygram
Help online shoppers quickly find their perfect size using their body measurements
Bodygram | 2022-2024 | Senior UX Designer
Vision & OKR Planning, Strategy, Concept, Design workshop facilitation, Research, Cross-functional collaboration, Rapid prototyping, Client communication
Summary
As Bodygram's senior UX designer, I led the design of an AI-powered size-recommendation experience now used by top Japanese fashion brands. The company had planned to lead with its signature photo-based body scan—but through prototyping and user research across Japan and the US, I found the effort of taking photos was too much friction for everyday shopping. I pivoted the design to a choice-based experience that lets online shoppers choose a quick stats-based flow or the high-precision photo scan, serving both speed and accuracy. It shipped as the MVP and helped move Bodygram from custom builds toward a scalable product for apparel businesses, opening new opportunities in the US market.
Background & Business Problems
Bodygram provides a unique AI technology that generates over 30 body measurements from just two smartphone photos. After initial success with custom client implementations, the company needed a scalable solution to address broader market needs—especially in fashion e-commerce, where sizing confusion causes high return rates.
At the same time, many apparel businesses lacked technical resources, making integration difficult. A universal size recommendation product could streamline onboarding, reduce returns, and help shoppers make confident sizing decisions.
End-User Problems
Online shoppers struggled with inconsistent sizing across brands, leading to high return rates and purchase hesitation.
Apparel companies—especially small to mid-size ones—found it difficult to communicate sizing effectively online.
Bodygram needed to reduce its reliance on custom development and improve the usability of the body scan flow to increase conversion.
18%
Online shoppers have either returned clothes or considered returning them.
38%
38% of returns were caused by size issues. Size was the top reason for returns.
My Role
As the senior UX designer, I defined the product concept, collaborated closely with leadership, and conducted research and prototyping to balance user needs, technical constraints, and business goals. I worked cross-functionally with engineering, product, and sales to deliver an experience that could scale.
Competitive Analysis
I analyzed local and global size recommendation services, identifying key gaps and differentiators.
Key takeaways:
Most tools only consider product dimensions—not body shape.
Competitors required excessive manual input across multiple screens.
Bodygram’s strength: high accuracy from minimal input (or photos).
Visual aids (like 3D bodies or brand-based size matching) were common elsewhere.
Hypothesis & Prototyping
The initial company strategy was to make the photo-based flow the primary experience, leveraging Bodygram's unique AI body-scanning technology as the core differentiator. As the senior UX designer, I shared the team's confidence in the technology—but suspected from early user signals that the effort of taking photos might be a larger barrier in everyday shopping than we anticipated.
To test this without abandoning the photo-first strategy, I designed a sequential prototype: users would first complete a quick stats-based input (height, weight, age, gender) for an immediate size recommendation, and then have the option to enter the photo-based flow for higher precision. I tested this prototype with users in Japan and the US, asking participants to complete both flows and share their reactions.
What We Found
The feedback was sharper than expected. Users recognized the accuracy of the photo-based flow and found the idea compelling—but the effort required (proper lighting, posture, conditions for the photos) was consistently described as too much friction for everyday shopping. When asked which flow they would actually use in their day-to-day, most participants said they would stop at the stats-based recommendation, even though it offered less precision. "Good enough and instant" beat "more accurate but more effort."
The Pivot & MVP Launch
The pivot wasn't simply about replacing the photo flow with a simpler one—it was about reframing how both flows were positioned to users. Two considerations shaped this decision. From a product positioning perspective, the photo-based AI scanning is Bodygram's core differentiator; hiding it behind a sequential flow risked diluting the product's identity at the most important moment of user entry. At the same time, research had shown that users were unlikely to seek out the photo flow on their own—it needed to be surfaced upfront to be considered at all.
The MVP introduced a selection screen at the entry point, presenting both flows as first-class experiences from the start. Users could explicitly choose between a lightweight input-based flow for quick decisions or the photo-based flow when precision matters most. This decision served both speed-seekers and precision-seekers, while reinforcing Bodygram's brand promise of AI-powered accuracy at the very first touchpoint.
V2 Enhancements & Customization
Design Workshop
I facilitated a V2 design workshop to uncover improvements. Through this internal ideation and client collaboration, we introduced new UX refinements and clarified edge cases.
UI Customization Guidelines
To support brand consistency across clients, I developed visual customization guidelines. I worked with engineers to ensure UI flexibility while maintaining system integrity.
Result: Customizability helped unblock enterprise deals—such as Adastria—and led to in-store pilot testing.
Impact
Business Impact
Adopted by major Japanese fashion brands, including Adastria, with the product running in production across e-commerce and in-store pilot environments.
Contributed to enterprise deal wins by partnering with sales on client presentations, demos, and pre-sales prototyping, and by collaborating directly with client design teams on integration planning.
Helped initiate US market expansion, supporting prospect engagements and laying the groundwork for international growth.
Product Validation
Users who engaged with the photo-based scan flow showed several times higher engagement than those using the stats-based flow alone—an effect especially pronounced among male users. The data confirmed the strategic value of keeping the photo flow as a first-class option: a smaller segment opted in, but those who did derived disproportionately higher value from the experience.
Successfully migrated the existing custom-built product to the new universal experience, supporting Bodygram's shift from one-off implementations to a scalable SaaS model.
Established UI customization guidelines that maintained design system integrity while unblocking enterprise deal cycles.
Reflection
This project crystallized how product positioning and user research can both inform a single design decision. The pivot from photo-first to choice-based wasn't just a UX change—it was a strategic repositioning that let the product serve the natural diversity of how people shop, rather than forcing a single path.
What I'd Do Differently
The dual-flow design was the right call for users—but looking back, it also sidestepped a deeper tension I'd engage with more directly today. Bodygram's differentiation rested entirely on its photo-based AI body scan. By placing an easier, stats-based alternative right alongside it, the design all but ensured that most users would never experience the core technology the company was built on.
The data made this sharper, not simpler: users who engaged with the photo flow showed several times higher engagement. The photo experience wasn't low-value—it was high-value but high-friction, and few users chose to reach it.
At the time, I framed my role around the immediate UX question: which flow do users prefer? Today, I'd push equally hard on the strategic one—how do we make the differentiating technology something users genuinely want to reach for? I've since learned that a designer's job, especially at a startup, includes naming when user behavior and a company's core value proposition are diverging, and helping the team confront that gap rather than quietly designing around it.
Copyright©2026. Mikako Matsunaga