SSENSE - a pioneer in the luxury e-commerce space, has been continuously serving its loyal customer base with great selection, thoughtful articles, and it’s famous free 2-day shipping. In online-retail, high return rates are one of the biggest persisting problems, so we’ve devised a new feature to try and help SSENSE stay on top of this highly competitive market:
A new feature that uses generative AI to analyze all customer purchase/return data to make size recommendations for users
research
One of the biggest problems in the retail-clothing industry is the returns, with about 20-30% of all purchases returned, and even higher for luxury and designer items. Studies show that incorrect clothing size is the #1 reason for online returns, and minimizing them would not only decrease costs and customer frustration, but also increase profits from more successful sales and happy customers
Problem
I used 2 main methods of research. One to see the context of the luxury fashion market, and the other to dive deeper into the minds of people who buy clothes online
Research
Competitive Analysis
User Interviews
Competitive Analysis
Strengths
focus on connecting independent boutiques with customers
has more selection in niche brands
Weaknesses
has inconsistent sizing guides
niche brands have less sizing info
Strengths
has brick-and-mortar stores for try-ons, returns and exchanges
robust sizing guide, with comparative sizing to other brands
Weaknesses
only has comparative sizing to popular/bigger labels, not niche brands
has less selection of smaller brands
Strengths
popular recommendation and styling services for users
robust sizing chart, hand measuring each item in each size
Weaknesses
no comparative sizing
no model sizing information
After analyzing competitors and seeing the context of the market, I conducted interviews with 5 people of various ages, backgrounds, and interests in fashion
User Interviews
Key questions include asking about personal experiences and preferences with:
How much clothing they purchase online
Favorite online shopping experiences
Brand loyalty or experimentation
Clothing sizing methods they use and/or prefer
Research Takeaways + Insights
Despite brands delivering more robust size guides and charts, users still report incorrect sizing in orders. The pain point is still there, and user frustration is driving them to either stay with familiar brands or shop less
Besides physical measurements, people trust blogs, reviewers, and influencers in terms of item sizing for brands they’re not familiar with. Users are more willing to trust someone who’s opinion they value, often researching the item and it’s sizing before purchasing
Relative sizing is helpful. Users say that the most helpful features for sizing are the height/weight of the model, and also comparisons to other brands. By having a reference that they’re familiar with, they can make decisions more confidently
People are hesitant to purchase more expensive items if there are shipping costs, return shipping, or a very strict return policy. Retailers that have free shipping/returns see users that experiment more with new labels rather than buying familiar brands
There is no industry standard for size charts or sizing tools. Each retailer has their own methods, from hand measured charts to comparative sizing, but the inconsistency has seemed to leave users confused and frustrated
analysis
Personas
With our research, we’ve come up with 2 perspective customers: one who just wants the clothing buying process to be quick and easy, and another who is very particular and wants to be as detailed as possible. We need a solution to satisfy both the average buyer and the meticulous veteran
As a retail customer, I need a more accurate and reliable way of identifying the correct size and measurements of clothing online, so I can spend less time returning and re-ordering items and have a more satisfying experience
POV
How might we more accurately communicate clothing measurements to customers so they will be able to understand and identify their correct size?
How might we compile customer purchase and return data into an easy-to-use sizing tool for customers so they will be able to benefit from previous customer experiences?
How might we show in more detail an example of a clothing’s size on models to customers so they will be able to understand the measurements better and choose their desired size?
HMVs
Solution
By compiling and analyzing customer purchase/return data, we can build an algorithm to determine a user’s best size using relativity - the most accurate and trusted method of sizing. Using generative AI, not only will this prediction be faster and more accurate because of real-time data, as more purchases are made the algorithm will learn and be more precise
ideation
In order to organize the ideas before designing the wireframes, a ranking was made to help prioritize which features we would include in the first iteration
Feature Set Prioritization
Generative AI Size Recommendations
Detailed Model Sizing and Measurements
Customer Size Passport
Purchase and Return History
Hand-Measured Size Chart
Customer Size Reviews
360-Degree Model Pictures
Community Forums
Social Media Posts and Reviews
Task Flows
#1: Using the GenAI Sizing Recommendation Tool
Users start at the homepage, pick an item, and the sizing tool will recommend a size based on customer purchase and return history
#2: Updating the Personal Size Passport
Users can access their personal Size Passport in their account and edit size preferences for any brand they like
Users can access their personal Size Passport in their account and edit size preferences for any brand they like
early wireframes
User Flow 1: Using the GenAI Sizing Recommendation Tool
home page of the SSENSE app
after clicking an item, it lands you to this item page, with an “add to bag” and “add to wishlist” button
swiping up on the item page gives you more item info, including materials and manufacture information, here we added the GenAI sizing tool
at the GenAI tool, it gives you a size recommendation based on your purchase history as well as other customers who have bought the same size, and you can add to your bag or wishlist
your shopping bag, with the prices and a checkout button in the bottom
User Flow 2: Updating the Personal Size Passport
home page of the SSENSE app
profile page, with wishlist, order history, and menus for notifications, account settings, and also our Size Passport
in the Size Passport menu, we have 3 boxes for brand, item category, and size
once you add a size, you get a small confirmation, and you can continue to add more or you can click back to go to your profile
testing
This test will be conducted by 5 participants, and they will be selected from the previous group of interviewees in the research phase so they will be familiar with the project and objective
Test Plan
Objectives
Observe efficiency in completing tasks
Observe how users navigate the design
Evaluate ease of use
Identify problems for revision
What is Success?
Users don’t need additional hints to complete the task
Users can complete the task in a timely manner with little or no errors
Overall rating out of 5, for ease of use and design
Results + Key Takeaways
Tests were done with low-fidelity wireframes, and the lack of pictures with the minimalist style of the website threw some people off. For people who were familiar with SSENSE had no problem, however
Testers mentioned that the sizing feature is something they’ve never seen before, and would be really helpful if implemented. And also that it fits in very well with SSENSE’s current sizing chart
Some testers were concerned about items that fit oversized, or if brands change fits between seasons
Iteration
Based on usability testing and user interviews, we focused on these points for the next iteration:
cleaner wireframes for easier navigation and less confusion
tested with multiple groups: those with experience using SSENSE, and those who did not
final product
Introducing
A brand-new, easier way to shop for clothes online! No more stressing about ill-fitting clothes and remembering sizes!
Tired of waiting for your new clothes to arrive, only to find out they don’t fit?
Smart Sizing is SSENSE’s latest feature, using Generative AI to process all customer purchase and history data to recommend you sizes for brands you aren’t familiar
Having trouble remembering how all these different brands fit? What size you bought last?
Also introducing the Size Passport, your very own sizing catalogue, where you can record sizes for your favorite brands, and help Smart Sizing learn more about you and what you like!