SAZANI: Virtual Manikin Chrome Extension

A sustainable way to online shop
Association

James Madison
University

Project

Senior Thesis

Timeline

2022 - 2023
(13 months)

Role

User Researcher +
Product Designer

🔴Problem

Overview

In today's digital age, online shopping, particularly in the fashion industry, has gained immense popularity. However, it comes with its fair share of challenges, including sizing discrepancies and a high rate of returns. These issues can significantly impact customer satisfaction and the profitability of retailers. Our project aims to revolutionize the online shopping experience by introducing a user-friendly Chrome extension to make purchasing clothes easier and more convenient.

Core Features

SAZANI's Virtual Manikin enables users to accurately determine the right size for the clothing they plan to purchase. Backed by extensive user and market research, SAZANI ensures a personalized fit, enhancing confidence in every purchase.

🟢solution
Adding User Measurements
Find the best size options tailored to your exact body type, enhancing fit and optimizing user satisfaction with every purchase.
🟢solution
Choosing The Correct Size
Assisting users in determining whether a clothing item’s size will fit their unique body measurements, providing confidence in their purchase decisions.
Now that you're acquainted...
Lets take a few steps back

Quick Statistics

Based on data from 106 research participants and scholarly studies

16.5%

The average retailer faces $165 million in returns for every $1 billion in sales (NRF)

62.86%

Find issues with sizing inconsistencies within different brands

75.24%

Do not return if the company doesn't offer free returns

40%

Return on average 40 percent of clothing they order online (NRF)
This is what is wrong with online retailers...

Vanity Sizing

Mislabeling garments with smaller sizes to boost consumer self-esteem, often differing between brands

Fit Modeling

brands hire a model to size garments and ensure they fit their target audience's body type

Sizing Chart

Aim to fit the maximum number of people with the minimum number of sizes
Problem Scope

How might we build a platform that reduces product returns, enhances sizing accuracy, and strengthens consumer trust?

Lets find gaps!

Competitive Analysis

The competitive analysis provided valuable insights into the features offered—and missing—on other platforms, revealing gaps in the market and opportunities for differentiation.

All this boils down to...

Users need a reliable way to see exactly how clothing will look and fit on their own bodies to make confident purchasing decisions.

How does this shape the product?

While researching the existing market, I realized I needed to remove the idea of
the 'model' and focus on the user, placing them (literally) at the center of the design.

WHo are we designing for?

Meet Lily

After researching the problem we created personas to better understand a generic, not specific, consumer, backed by research.

Beginning design process

Why a Chrome Extension?

User Insights: Many participants emphasized the importance of convenience and integration. They expressed frustration with having to switch between multiple platforms or learn complex tools. These insights guided our decision to focus on simplicity and accessibility, ensuring the Chrome extension could integrate naturally into their browsing habits.

User-friendly site: A virtual mannequin is not a tool most people are familiar with. To address this, we decided to develop a Chrome extension that is hassle-free and intuitive, enabling users of any technological background to navigate and use it seamlessly.

User Interface

Mockups

Before I created the final prototype, I created different variations of mockups. The one below was the final low-fidelity prototype. It included all of the user flows and the corresponding styles. Before this version, I also mocked up user flows with pen and paper and got user feedback.

User Interface

Responsive High-Fidelity Prototype

I created a high-fidelity prototype; a computer-based interactive depiction of a product. Through the findings in the background research, primary and secondary research, a prototype of a Chrome extension called SAZANI was created. ​SAZANI is a game-changing Chrome extension designed to help users determine the perfect clothing size for their body type. With its user-friendly interface and detailed explanations, SAZANI empowers users of all shapes and sizes with confidence when shopping online!

downloading sazani

Download Page

SAZANI is a Chrome extension and users will have to download SAZANI on the Chrome web store.
Creating an account

Sign in/Login page

Users have the option to signin or create an account. They than have the option to do it through Google.
Home page Tutorial

Tutorial

This is the beginning of the tutorial. Users are shown how to access the features on the home page.
customizing sizes

Tutorial

Users are prompted to add their body sizes to SAZANI. We give users tips on how to correctly measure themselves so there is low user error. After the users impute their body measurements, SAZANI's manikin will shape into their body type.
Virtual try on

Virtual Try On

Once a user is on a piece on a clothing site, SAZANI's chrome extension will pop up in the top right corner. Once clicked, a user can start trying on the piece. SAZANI reads the data on the site, e.g., the clothing piece's measurements and material and will compare it to the users.
User Interface

If I was working on this today, is there anything I would change? 

Absolutely! One of the most exciting aspects of learning design is its ever-evolving nature. As my skills grow and adapt to new trends, technologies, and approaches, I find myself rethinking how I approach projects. If I were working on this today, I would refine the visual design of the final prototype to ensure a more polished and cohesive look that aligns with the user’s expectations. I would incorporate more interactive elements to enhance engagement and usability. For instance, when a user hovers over the size recommendations, a popup could appear, dynamically suggesting the size we recommend based on their preferences or previous inputs. This added interaction would provide users with instant, actionable insights, making the experience more intuitive and personalized while demonstrating the functionality in a more compelling way.