Stylevue App: Redefining Online Clothing Shopping through Perfect Sizing — UI/UX case study
In this article, I’m going to talk about how me and Stylevue solved the biggest e-commerce problem which is the return of fashion products like clothes and shoes due to a fitting problem.
About Stylevue
Stylevue is an AI platform that helps enhance the shopping experience of its user by telling them the perfect size of their clothes and footwear so that the return rate can go down and the loss on returning the products should decrease. Stylevue partners with brands and lets them put Stylevue’s app option on their products which makes it easier for users to find the perfect fit and reduces returns
Story
Stylevue, a forward-thinking company dedicated to addressing the challenges of the e-commerce clothing industry, engaged me to design an app aimed at minimizing the high rate of returns associated with ill-fitting clothes and shoes. The primary goal was to enhance user experience and reduce financial losses for both customers and vendors by providing accurate sizing recommendations.
Understanding the problem space
1. The most significant challenge for any e-commerce seller in the fashion industry is product returns.
2. Statistics reveal that the fashion e-commerce sector experiences one of the highest return rates, sometimes touching 30–40%, a figure that starkly contrasts with other categories.
3. The most common cause of returns is due to a product not fitting (62% of returns)
4. This is because the lack of standardized sizes across regions globally is one big reason for this. For example, a size 10 in the US is a size 14 in the UK, and a size M in the US is a size L in the UK.
5. The National Retail Federation reports that for every $1 billion in sales, the average retailer incurs $165 million in merchandise returns.
Inefficient size selection leads to high return rates in the Fashion e-commerce market which causes financial losses for vendors and inconvenience for customers.
Design process and challenges
My design process was as follows
1. Initially, I engaged in discussions with the stakeholders of Stylevue to understand their business model and the precise problem they aimed to solve.
2. Subsequently, I conducted competitive research and identified a gap in the Indian market. Despite India ranking among the top 10 countries in terms of online shopping usage, no similar solutions were found locally. Therefore, I analyzed strategies employed by international brands to address similar challenges.
3. Following thorough research, I iteratively designed multiple versions of each flow, holding frequent meetings with stakeholders to refine and finalize the most effective solution.
1. Splash Screen Flow
While Shopping online, users often encounter confusion regarding sizes, leading to potential returns and dissatisfaction.
Understanding user psychology, I recognize that size consideration typically follows product images and pricing evaluation. Hence, placing the size guidance card after the pricing section ensures it aligns with users’ natural browsing flow, enhancing the overall shopping experience.
2. Clothes Size Checking flow
Users need to determine the correct size for their purchases, as sizes can vary between brands and regions. To address this, Stylevue developed an AI-based solution. Users provide basic information such as height, weight, age, and gender, followed by physical measurements. To enhance accuracy, users can optionally input sizes from brands they commonly wear. The AI then calculates the most accurate size recommendation.
a. Question Screens
Users begin by answering basic questions regarding their physical attributes. This data enables the AI to provide precise sizing recommendations.
Now one problem arises, there is a possibility that users don’t know all the information correctly about them and the AI will show the results based on the answers they have given
So to solve this if the user feeds the AI with the size of the brands they wear normally then the AI will be able to calculate the accurate size
Now there is a possibility that the user doesn’t wear any of the brands mentioned then in that case user can easily skip this part and see the final screen
b. Size Screen
The AI analyzes the provided information and delivers the most accurate size recommendation to the user.
Challenges
After presenting the solution to stakeholders, budget constraints necessitated the postponement of integrating features such as “Live Demo” and incorporating products on models. These elements were temporarily removed from the scope.
Learning
Reflecting on this experience, I’ve come to realize the importance of proactively clarifying the stakeholders’ financial parameters from the outset. It became evident during our initial meeting that there was a possibility of being tasked with incorporating a comprehensive set of features without due consideration for budgetary constraints. In hindsight, I should have diligently inquired about their budgetary allocation beforehand, allowing for a more focused approach in prioritizing essential features within their financial scope. This oversight led to a loss of time for both parties involved.
c. Female Size Flow
The female size flow mirrors the male size flow but includes additional female-specific measurements such as bra size, waist size, hip size, and shoulder size.
3. Shoe Size Checking flow
This app also assists users in finding the right shoe size. Similar to the clothes size checking flow, users input relevant information about their feet, and the app provides accurate size recommendations.
The screens are as follows
The process commences with basic inquiries regarding the user’s foot dimensions and shape. Subsequently, the app presents sizes that closely align with the user’s specifications, ensuring a seamless fit.
4. Login flow
Now the user can check the size before purchasing anything but the problem arises that the user has to mention all the details again and again to get the perfect size which can make the user frustrated and can leave the app
So, to streamline the user experience, a login/signup feature was implemented. Users can create accounts to store their information, eliminating the need to repeatedly input details during subsequent visits.
Additionally, users can access sections such as “My Wardrobe,” “My Silhouette,” and “Clear all info” to manage their data efficiently.
a. My wardrobe
In the “My Wardrobe” section users will find all the information they provided during the purchase of any particular item
For instance, when a user intends to purchase a top and utilizes the application to ascertain the appropriate size, upon creating an account, the app automatically stores the user’s inputted data within the “My Wardrobe” section. Consequently, upon subsequent visits to procure another top, the application seamlessly presents accurate size information.
b. My Silhouette
There may arise instances where users need to revise the information they have provided. In such cases, they can conveniently access the “My Silhouette” section to modify any details as needed.
c. Clear all info
After clicking on this user can delete all the information there is on the app
Impact
As the app was recently launched, data on its impact is not yet available. Updates on its effectiveness will be provided once sufficient data is gathered.
And that’s a wrap
This project reinforced the importance of understanding stakeholders’ requirements and constraints early in the design process. By prioritizing features effectively and optimizing available resources, we can deliver solutions that address key challenges in the e-commerce industry.
You can check out the app here on https://stylevue.ai/
For any query, you can find me here on My Website
