Fit Finder
Customer Account App for Shopify merchants that allows customers to match the sizing of different brands they are familiar with to the merchant's sizing. This way they can find the best sizing for them.
PROJECT OVERVIEW
Timeframe
24 hours!!
Role
UX Researcher, UX/UI Designer
Tools
Figma, Sketchbook App
Deliverables
Live App, Pitch Presentation
Team
2 UX Designers, 2 Software Engineers, 2 Data Analysts
Goal
This solution, conceived during a 24-hour hackathon within a cross-disciplinary team, aims to improve merchant productivity and revenue by reducing customer confusion and increasing purchase confidence.
THE CLIENT
Shopify is a leading global e-commerce company, providing trusted tools for retail businesses of any size.
Has more than 2.1 million daily active users and more than 1.75 million merchants 👥
Recently released extensive capabilities for customer accounts (apps) 📱
Provides a safe and secure platform where developers can build app extensions using a provided component library, APIs, and design guidelines. 🔒
THE PROBLEM SPACE
Shopify merchants struggle to balance customer support with growing their businesses, as they currently spend too much time helping customers manage their orders.
Merchants want to put capabilities into their customers hands that will help them:
Cut down on the number
of support requests
for order changes
Increase sales and
have more returning
customers
Collect more personal
information to personalize experiences
Our 24-hour Challenge
How might we provide customers with a more seamless and reliable shopping experience so that merchants can focus on the productivity and revenue of their brand?
OUR APPROACH
Given the 24-hour time constraint, our cross-functional team, which included UX designers, data scientists, and developers, established an agile process to ensure effectiveness and highlight our best skills. We incorporated moments for collaboration, discussion, and independent work.
OUR RESEARCH
Quantitative Data
We dug deeper into the problem space and found interesting information that would guide our proposed solution.
50.3%
Mobile
E-commerce
More than half shopify’s ecommerce traffic is from mobile devices
33%
Apparel
Stores
Greatest percentage of
Shopify's stores are apparel stores.
26%
Clothing
Returns
Clothing is the most return
online purchase
75%
Reason
of Returns
Users mostly return items because they don’t fit properly
Qualitative Data
We also gathered user input and found that many reviews indicated that finding the right size was a major pain point.
“I would recommend going one size up because they are tight at the waist and get a little constricting after a day of wearing them.”
“Definitely runs small! I am a small normally and the M was even a bit short on me. I got a lot of compliments on the shirt though!”
“I highly recommend this top! I ordered a 10 and
a 12 just in case, but I think an 8 would have been perfect. I hate when things are too tight,
so the 10 was awesome!”
OUR TARGET USERS
The next step was defining who we were designing for. This way, two user personas: the Shopify Merchant and the Clothing Shopper.
Customers’ current journey
We also mapped the steps shoppers currently go through when buying a clothing item:
🔖
User purchases clothing item
👖
User disappointed in the fit of the product
🔀
User request return/exchange
📲
Merchant receives request and
fixes order
📦
Customer receives new item
And, what does this mean for the Shopify Merchant?
More time and money spent on returns/exchanges: This takes away from growing their business. 💸
Negative reviews: These deter potential customers and harm reputation. 👎
Decreased customer loyalty: Leads to fewer repeat customers and reduced long-term revenue. 📉
DECIDING OUR SCOPE
Since we identified that customers’ main pain point was disappointment due to clothing items not fitting, I proposed introducing our solution before the customer purchased the item.
😎 This way our solution aims to help customers find the right fit, thereby helping merchants avoid wasting time and resources handling returns.
👖
User finds
the right fit
🔖
User purchases
clothing item
😍
User is happy
with new clothes
🫰🏽
User leaves a
good review
and buys again
IDEATION TIME!
We started coming up with ideas that could help customers find their right fit. Some of the ideas we considered were:
A quiz to create customers’ fit profile
A video filter to try on clothes
A chatbot that helps customers choose the right fit
While we were getting a small snack, we came up with our definitive solution.
🥁🥁🥁
Fit Finder
Customer Account App that lets customers input a size from a trusted brand to receive a recommended size from Shopify’s merchant, ensuring a more accurate fit and enhancing the shopping experience.
THE EXPERIENCE
An actual Shopify storefront was used to implement Fit Finder, which was fully developed by our team.
Leveraging insights from past customer reviews, Fit Finder not only assists users in selecting the correct size but also provides information about how the product fits.
DESIGN IMPACT
So what’s the impact on Shopify and its merchants?
It prevents customers' order changes and return requests.
Allows merchants to allocate more time to increasing productivity and building revenue.
Greater customer satisfaction will lead to more returning customers and increased sales for merchants and Shopify.
NEXT STEPS
A lot was accomplished in 24 hours, and a proof of concept was delivered. Looking ahead to future development, here’s what’s next: 🐾
User Testing
Rounds
Engage with a diverse group of users to thoroughly test and refine Fit Finder, ensuring it’s intuitive and user-friendly.
Recommendation Model
Develop a robust recommendation model incorporating user reviews to provide personalized and relevant suggestions
Dataset of
Size Charts
Compile a detailed dataset
that includes size charts from popular brands.
Thank you for going through this case study!
Please feel free to contact me if you have any questions.