Role: UX Designer
Date: May 2016
to the world where plus size fashion meets virtual reality.
Create a personalized online shopping experience that helps users make informed decisions.
Elu is a made-to-measure company that focuses on helping alternative and plus size women make clothing to their personal measurements. Their current MVP is run off of Shopify.
plus size friendly
As the fashion industry currently exists, plus size clothing is limited in style and variety in the store. Meanwhile, online shopping can be risky, particularly for users who don’t have standard guidelines or sizes.
AI & virtually possible
Elu's goal is to make the dress buying process less intimidating for alternative and plus size women. Their solution is to build a platform that offers personalized style suggestions and a virtual fitting room.
How do you get to know someone through AI?
Our client's goals were to help users find the best fit and style online, like an online personal shopper. My question was, how can you get to know someone – such as their preferences, comfort levels, and personal goals – completely virtually? Additionally, how do you give the a good suggestion that they'll be proud of?
Q1: "Why is it so hard to make plus size dresses?"
Despite how enormous the fashion industry is in America, why is it so hard for plus size women to find good looking clothes that fit their body? In other words, why is this problem a problem in the first place? To begin our research, we sought to answer this question. Our first interviewees were two fashion designers, from who we sought to understand what happens behind the scenes when designing a dress, both for style and for business. What did we find?
Fashion design isn't actually about fashion,
it's about sales.
Many companies rely on one “standard” model to determine the shape of their clothes. The “standard” model is simply the company’s best assumption on what a standard size looks like. Additionally, certain clients (ie department stores) cater to specific body types. This dictates what the designers are asked to create, therefore influencing what ends up on the racks in stores. Due to the specificity of certain designs and silhouettes, plus size is therefore often unconsidered as their body shapes vary greatly from person to person.
Q2: When people are shopping, what do they care about the most?
Our second set of SME interviews included two Customer Service Associates.
Our goal was to identify the tricks and tips of the industry, giving us insight into the psychological processes when buying a dress. A few of our questions included strategies these associates have employed, most commonly asked questions by customers, moments where customers need the most help and input, and extra incentives that have helped close a deal. Turns out...
People want affirmation and conversation, not a sales pitch.
Give a customer options, help them make a decision. If a customer is ever unsure about something, help them figure out what they can wear it with, how it will wash, and how an item can be accessorized. This greatly increases sales and buyer confidence, which often leads to very happy results.
Q3: What's it like, buying a dress?
For this final question, we asked fashionable women who have shopped for dresses. Our goal was to understand their shopping habits, goals, frustrations, and differences between shopping in person and online. We also asked for examples on their most recent purchase and how they were able to make a decision, honing in on how our users’ perceptions of themselves influence their expectations and decisions when purchasing a dress.
"If I were to buy something it would probably be because I saw it on Instagram."
"A bad experience is when you feel like you have no options."
"I have a picture in my head and finding that picture is hard."
People dream in lifestyles
Social media and real life context leads to inspiration. In particular, people depend on seeing clothes on other models in lifestyle images, helping them gauge quality, fit, and comfort from an image. Social media plays a huge role in this. People rely on seeing clothes in context on a website, but it drives them to shop when they see the clothes on people they identify with on Instagram and social media.
good CUSTOMER SERVICE and conversation IS KEY
Users feel a lack of options not only in the quantity of clothes available, but in their understanding of ways to wear them. By helping users through the process, either by answering their questions, giving them a second opinion, or showing them versatility, the customer can feel more confident about their purchase and overall experience.
PEOPLE THINK IN terms of RE-CREATION, NOT CUSTOMIZATION
Users try to match what they see in the media to the clothes that they buy in the store. People often end up buying clothes they loved looking at, but don’t know how to dress for themselves. Having these type of images is crucial in developing the user's relationship to the clothing they are attempting to purchase.
THE COMPETITIVE LANDSCAPE
Moving forward, we looked at our competitors. This helped to identify opportunities for Elu in the made-to-measure industry. Our list was compiled of companies that tailored to plus size style, custom fit clothing, and personalized shoppers. In the left column, we listed features that were important to our customers and to Elu's business goals.
The importance of social media: Whether it was in customer reviews or featured on the homepage, every company we looked at had Instagram feeds on their website. This validated our insight from our user interviews, helping to push the importance of this feature with our client.
The scarcity of user reviews: User reviews, particularly those with images, were especially important to our clientelle because of the their specific body shape. When sizing goes up, structure and cut becomes unique. Our users needed more information than the average user to feel like they were making an informed decision. If Elu could leverage this feature, they could stand out from their competitors.
The lack of personalized style suggestions: There were no personalized style suggestions that catered to plus size customers. Trunk Club and Stitch Fix, personalized stylist websites, did not have options to choose above a size 18. This validated Elu's business concept to show a need in the marketplace for both stylish and personable plus size clothing.
Defining Our Audience
Combining our research, we created two personas that embodied the goals and frustrations of our users. With each persona is a problem statement, unique to their own journey. This is important as we later identify the personas into two phases, each addressing a specific stage in Elu's business.
- ・For clothes to fit as they come
- ・Create a wardrobe that is versatile for work and going out
- ・To continue building her personal style
Our Fashionista wants to find a fashionable dress that fits her body type, but stores don't offer enough options to cater to her personal style, and the online experience is ambiguous and risky.
- ・ To learn what clothes make her look and feel good
- ・ Understand how to make fashion work for her
- ・ Become more confident in her style choices
Our Fashion Seeker needs a way to find fashionable dresses that fit. She doesn't know her body type and hasn't explored her style enough to feel confident in what she wants.
two personas, one strategy
Looking at our research, we recognized that our two personas spoke to different stages of Elu's business plan: the first stage is to establish their presence and business model, and the second is have AI and VR built into the experience. With Elu still in the early stages of their AI and VR development, we felt that our best efforts was to help improve their MVP. By creating this small roadmap, we identified the value for tech in the fashion industry that Elu would be able to address as they establish their market.
Our Phase 1 persona is the early adopter. As an experienced user, she knows what to look for and how to make decisions. The best Elu experience for her is to focus on easy onboarding, strong images with comprehensive product descriptions, easy information gathering, and strong business policies.
Our Phase 2 persona is much closer to Elu’s desired demographic. Our Fashion Seeker finds the AI and VR helpful for decision making. The value of tech for users like her is to help them make better, more informed decisions.
These design principles helped us embody Elu's meaning and purpose for the user and directly responds to our problem statements. Overall, we wanted our users to feel supported and empowered in their journey shopping online.
We set our own tone, we empower, and we lead. We're making the future now.
We're not a website that dictates your style, but asks you what you want, just like a concierge would.
Show, don't tell. We're visually forward and highlight the confidence of older women that know fashion and know it well.
We're willing to make statements, be bold, and be professional.
II. prototype & test
Ideate: 3 prototypes
The first part of the prototype phase is to wildly ideate different solutions to our problem statements. Our goal was to test if our users enjoyed the platforms, were comfortable with certain tasks (such as various virtual fitting room experiences), and to validate our client's overall business concept. We each made sure to differ on the following three features.
Elu had an extensive list of custom measurements necessary to make a dress (12 measurements total). In addition, Elu had a plethora of resources available to help the process. Our challenge was to make the measurement process as least intimidating and work heavy as possible.
customize your dress
We wanted the experience of building and customizing your own dress to be a delightful experience. This included the dress picking process, the potential for virtual reality, and the look book experience.
We tested a variety of questions to see what users felt like were the most comprehensive, helpful, and insightful. We also tried a variety of ways for users to access the quiz — is it necessary or is it optional?
Prototype A focused on highlighting social media and customer reviews for social proof of Elu's product. Their virtual integration featured an avatar-based fitting room with 360 degree rotation. Lastly, their quiz focused on asking event-based questions to help users specify a style preference.
Prototype B focused on allowing the user to play first, input details later. This meant that seeing the dresses was easily accessible by lookbook, but personalized details were uncovered once the user made a profile. They also integrated an in-person tailoring feature, where users could find local tailors to help take measurements. Prototype B also tested user willingness to download a third party app to access the VR fitting room.
Prototype C focused on creating a fashion forward layout with lifestyle photos to inspire customers and build brand trust. This directly linked to dresses that each model was wearing, to help stimulate the user's imagination. The quiz integrated "Pro Tips" with personalized suggestions and style pairings. Questions aimed to gauge the user's comfort level, while encouraging them to consider new fashion styles. The layout also featured an easy step-by-step process to help users through a input heavy customization process. Lastly, Prototype C tested AR technology to gauge user interest in a realistic image of themselves in a virtual dress.
User Testing Insights
“Even though you wouldn’t be standing like that... just seeing yourself is helpful.”
Sometimes, low tech is better than no tech. Users appreciated the fitting-room experience, but were unsure it would be accurate. Those who were less familiar with shopping online found it helpful.
Having fun builds a conversation with the product. Quizzes, in particular, are exciting and helps builds familiarity. Users feel more confident in purchasing a dress after the quiz.
"I like this because the models look like real people. You see different body types."
A variety of real and lifestyle photos are crucial. People sought 3 types of photos: models with a similar body type, lifestyle photos, and real customers. Photographs help users imagine themselves in the product and gauge quality and fit online.
refinement: best of the best
"What do you like?"
To help users make the right decisions, we engage them. By asking our users their preferences, it helps bring conversation to our platform. This establishes a connection to our brand and our product.
Learning is Empowering
In our quiz, we ask our users for their preferences first, but always give them a pro tip later. This "pro tip" is our avenue to helping our users make informed decisions, without telling them what to do.
Our lookbook feature had lifestyle images that helped users gain context on how clothes could be worn. Additionally, it helped spark imagination, interest, and relatability.
Real User Photos
Images of other real customers gave our plus size users a large boost in morale. Not only did our users trust the photographs more, but it helped them find dresses to customers more similar to their body shape.
In our final prototype, we included all three versions of our 3D technology for furthur testing: 3D app download, 2D image capture, and an AR avatar. The avatar was the most accessible and ranked the highest in user interest.
Still Under Construction
However, without full access to the developed technology, our VR suggestions were inconclusive. While our studies suggested an avatar based approach, we suggested furthur testing as their technology developed.
Over the course of 2.5 weeks, I'm extremely proud of my team for creating a wireframe that would help shoppers confidently buy dresses to their fit and taste. However, if I were to move forward with this project, these are the following two subjects I would want to tackle next.
Elu's dress making process can be extensive. It would be beneficial to continue testing our CTAs to optimize user engagement and direction through A/B testing. Additionally, I would want to continue improving the step-by-step process for the best user flow to purchase.
Our quiz features questions that tailor to personal preferences, but the recommendations by the AI have yet to be developed (only suggested). To truly test AI in the real world, I would have loved to dive deeper and follow through with beginning to end purchases.