OFT PKR (pronounced “outfit picker”) is a mobile app that recommends clothing items and outfits to users based on their personal style, size, and budget.
Project Details:
Product: Mobile App
Duration: 1 Month
Role: Product Designer
Client: Designlab (educational)
Tools: Figma, Figjam, Microsoft Word, Microsoft Excel
Responsibilities: Understanding User Needs | Conceptualization & Ideation | Usability Testing & Iteration | Implementing Accessibility & Inclusivity  
The constant pressure to keep up with ever-evolving fashion trends, while staying true to one's personal style and maintaining a sense of body confidence, has become a considerable source of anxiety for users. Many individuals face the daily challenge of selecting outfits due to a lack of confidence in their personal style or body size, leading to a struggle in determining what to wear.
OFT PKR recognizes and addresses this critical need to develop a user-centric solution that can alleviate the stress of choosing outfits and enhancing their overall fashion experience, by suggesting outfits with links to buying each clothing item that is based on a user’s personal style, size, and budget.
View Prototype
Research Goals
Research Methods
Competitive Analysis
User Interviews
User Personas
Competitive Analysis
The initial phase of my research involved conducting a thorough market analysis to identify competitors and their unique strategies. My primary areas of focus encompassed digital outfit organization apps & a styling service.

The insights gathered provided a valuable foundation for shaping the design approach, including the type of interface that would be most efficient at organizing style options.
User Interviews
By engaging in a comprehensive interview phase, I delved deeper into participants' pain points, motivations, and behavioral patterns. To cultivate a richer understanding and extract valuable insights regarding user preferences and expectations, I deliberately selected individuals who are interested in their fashion appearance.

The carefully crafted interview questions were strategically designed to unveil users' desires for a outfit picker app.
Number of Participants: 10 people
Method: 1 on 1 virtual calls & Google surveys
Participants: Users who are interested in their fashion appearance
Affinity Map
Our aim is to uncover patterns and traits among interview participants, gaining insights into the unique needs of our target audience. Customized questions enable a deeper understanding of features that could fulfill individual requirements.
1. How clothes fit their body is very important to users
2. Social media has a strong influence on users’ styles, this includes friends and celebrities profiles
3. Users’ friends have a strong influence on users’ styles
4. A lot of users like having a relatively basic, casual, and comfortable style
5. Users want to improve their style
6. Users are confident and care what they look like
7. Users get dressed based on occasion, mood, weather, or activity
8. Users like a variety of trends
9. Users are not interested in spending a lot of money
10. Users struggle with clothing choices
11. Users like convenience

Point of View Statement to
How Might We Question
# 1 Style Improvement
I’d like to explore ways to enhance users' personal style, recognizing their ever-evolving sense of self and the desire to be creatively inspired.
How might we push users’ personal style, while still keeping to their usual aesthetic?
How might we figure out a user’s personal style?
#2 Efficiency
I’d like to explore ways to assist users, especially those who struggle to efficiently choose or buy an outfit, in streamlining their outfit selection process.
How might we make choosing an outfit as easy as possible?
How might we make choosing an outfit enjoyable?
#3 Fit
I’d like to explore ways to demonstrate to users, especially those who do not conform to the typical body size standard, how clothing pieces fit on their unique body size.
How might we include the various body sizes in our app?
How might we have users input their body size into our app?
User Personas
Basic Betty
Neha is a newly graduated engineer who now has the time and money to be able to explore her personal style and invest in her closet.
Busy Bee
Charlotte is a busy corporate worker who knows her personal style but does not always have the time to go shopping or pick out outfits for herself.
Task Flows
Theses task flows serves as a visual representation to identify potential areas for improvements, if any.
Create a Profile
Receive Outfit Recommendations
Low Fidelity Wireframes
Having amassed sufficient information, I embarked on crafting preliminary low-fidelity concepts.  Presented below are several preliminary screens:

When on-boarding users include their measurements so the app can select clothing items that fit their actual body size.

When on-boarding users are able to set a budget for each type of clothing so the items suggested to them are more attainable.

A personal style quiz in included in on-boarding where users select what they love/hate from a range of styles, colors, patterns, and brands.

Once a profile is created, the main page shows recommended items, trending brands, and influencers' outfits available to buy.

On this page, the app suggests a set of outfits for the users to review and either buy or save. They are able to swipe through options.

Users are able to save clothing items on this app, so they are able to go back to items they are interested in when they are ready.

Moodboard to Style Tile
High Fidelity Wireframes
After several rounds of iterations I created a user interface that reflected the brand’s image, while also creating a user experience that was specifically tailored for each individual user. Presented below are several of the screens:

Profile Summary

After a user is done creating their profile, but before they are allowed onto the app, there is a profile summary to remind the user what they had selected, with the option to edit, if needed.

Ask Page

I created a feature where users are able to ask for specific types of outfit recommendations, whether for an event, trip, or season. Once a request is written, AI would then show you some of its suggestions.

Outfit Picker

Users are given a set of outfit recommendations, where they are able to swipe on the individual clothing item and thus mix and match to their preference, if desired. If users want more details about a clothing item or the option to buy the item, all they need to do is click on the image.

Likes Page

Users are able to save clothing items for later and come to this page when they are ready to buy them. The item's brand and price is noted on each item.

UI Component Library
Usability Test Overview
Research Goals
Evaluate how easy task flows are accomplished, such as

1. Create a profile
2. Ask for specific outfit recommendations
3. Ask for general outfit recommendations
4. Find “liked” items

Evaluate how much time it takes for users to complete each task flow

Analyze any challenges users faced while completing each task flowReceive feedback on UI

Success Metrics
1. Users are able to navigate platform and complete tasks with little to no errors or confusion

2. Users are able to complete tasks in under 5 minutes

3. Users are satisfied with their experience

4. Users want to use this platform again

5. Users want to share this product with their friends

100% Success Metric
Final Product
View Prototype
Next Steps
Incorporate a size chart within the measurements screen during onboarding, ensuring that all users can confidently and accurately input their measurements for a comfortable fit.

Integrate a "Select All" button for item selection during profile creation, while still affording users the flexibility to individually modify their choices on each tile.
Additional Features
"Liked" Outfit Recommendations
Create outfit recommendations based on users’ liked clothing items

"Buy All"
Implement a "Buy All" feature that enables users to purchase all items within an outfit through the app, even if they originate from different online stores. This not only streamlines the purchasing process but also accommodates users who may face technical challenges.
End to End App
In essence, I crafted an app that is meticulously customized to cater to the distinct preferences of each user, ushering in a new era of inclusivity in an industry that has long grappled with narrow beauty standards. The prevailing norms within the fashion realm have inadvertently excluded a vast majority of individuals, failing to resonate with their diverse body types and personal outlooks. By conceiving this app, we've ushered in a transformative experience, empowering users to seamlessly navigate the fashion landscape without a hint of alienation. Through tailored recommendations that seamlessly align with their unique body sizes, individual mindsets, and budget considerations, we've succeeded in dismantling the barriers that once hindered their sense of belonging.
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