Duration: 16 weeks (1.24.22 - 5.9.22)
Type: Individual
Role: Design, research
Tools: Figma
Research paper  (18 pages, written for Secondhand Fashion history and theory class taken with professor Heike Jenss.)​​​​​​​
I completed this semester-long project in my Major Studio 2 class in the Parsons MPS Communication Design with guidance from professor Lynn Kiang. The assignment was to design an experience around a topic of our choosing, and I decided to focus on secondhand fashion because I love vintage and thrift shopping, I am passionate about sustainability, and I believe there is significant room for growth and innovation in the secondhand fashion industry. 
Over 16 weeks, I researched my topic, conducted exploratory interviews, created low and mid-fidelity prototypes, conducted user testing, established a minimum viable product, created system and journey maps, applied a lean branding strategy, and created a high fidelity prototype. 
The result of my work is The Loop, a mobile application that promotes a circular economy by allowing secondhand stores to input and track information about their inventory, while shoppers can search and browse inventory across stores near them.
Below is the interactive high-fidelity prototype. To learn more about the app and my process, please read on!
Here are some statistics about the environmental impact of clothing production that inspired me to focus my project on secondhand fashion:
Sources: earth.org 2015, Roadrunner Recycling 2021, Bloomberg 2022.
Sources: United States Census Bureau 2021, Yangzom 2021.
Because the secondhand fashion market is growing rapidly and secondhand shopping is a good way to consume clothing more sustainably, I decided to focus on the following research question: 
I began with the following research methods:
Primary research: Read articles and academic papers on the history and theory of secondhand fashion and circular economies.
Observational research: Visited stores such as The RealReal and Reformation to see how they were using digital technology in their retail strategies.
Analogous research: Examined other industries such as the food industry to see how it has been revolutionized by digital technology.
Competitive research: Studied and used other secondhand platforms and retailers. (I had already used Poshmark, Depop, and Ebay for both buying and selling prior to this project.)
For exploratory interviews, I spoke with 6 subjects ages 20-26 about their general shopping habits, secondhand shopping experiences (varying from extensive to none), and decision-making while shopping. I focused on Gen Z and millennials because they have played a large role in the recent surge in the popularity of secondhand fashion, they have been heavily shaped by the rise of digital technology, and they are the ones who will be shaping the future of retail.
I put key insights from these interviews onto sticky notes, color-coding them by topic. From there, I created an affinity map by grouping individual insights in order to detect common trends and pain points.
From this research, I found that some people avoid shopping secondhand because they feel it’s less convenient than new or online retail, it’s inefficient and time-consuming to find what you are looking for, and it’s less trustworthy than new or online retail.
This is partially because brick-and-mortar secondhand stores require a lot of digging and the inventory is often unknown, while with online shopping, information about secondhand items is scattered across platforms. This information is usually crowdsourced which can be inconsistent or inaccurate, and it can be hard to tell what items will be like in real life.
These findings led me to refine my research question:
Next, I sketched out some prototype ideas with my peers:
From there I developed 5 low-fidelity prototypes, which I user tested then refined into 3 mid-fidelity prototypes.
I tested these prototypes with 8 users ages 20-25.
Following the usability testing of the low-fidelity prototypes, I created an affinity map that allowed me to compile insights, which informed the direction I took with the mid-fidelity prototypes.
Following the usability testing of the mid-fidelity prototypes, I created another affinity map that allowed me to compile insights, which allowed me to combine the most successful aspects of my prototypes to determine my minimum viable product.
I defined my minimum viable product to be a mobile app that helps stores input and track information about secondhand clothing in order to make it more accessible to shoppers.
This app can be used by any secondhand store that chooses to opt in to The Loop, thus democratizing this business and turning competing stores into collaborators because by participating in the ecosystem, stores would improve the overall experience and improve sales for all participating stores. 
It also promotes a circular economy, as people who bring in their unwanted clothes would receive store credit to use towards other items in the ecosystem, and once an item enters the ecosystem, its information would be forever stored in the database via QR code tag.
Below is a sitemap illustrating how the retailer and consumer sides work and connect:
Here is a map outlining the journey of a first-time customer whose point of entry is bringing their unwanted clothes to a participating store to consign into The Loop for store credit:
First they would bring their unwanted clothes to the store, then the salesperson would create an account for them and input their items in to the loop. Then, the customer would receive store credit. 
They can browse inventory in-store or in-app, use their store credit towards other clothes in The Loop, and bring them back when they no longer want them, and the cycle repeats.
This map outlines the journey of a first-time customer whose point of entry is browsing The Loop app because they are interested in shopping for secondhand clothes in stores near them.
The customer would download at the app from marketing or word-of-mouth, browse and search to find the items they want, then create an account to add items to their wishlist.
They would then go to the stores to buy the items from their wishlists, and bring them back when they no longer want them. They would get store credit for bringing items back to The Loop, and the cycle would repeat.
This map outlines the journey of a salesperson in a participating secondhand store whose job is to input items customers bring into The Loop, and update the status when items are sold or cycled back in.
For my high-fidelity prototype, I decided to mostly focus on the retailer side of the experience, so I will go into more detail about this journey now.
I kept the branding relatively minimal in order to allow the app to highlight the images of the clothing, and also to evoke The Loop’s core feelings which are effortless, sustainable, and fashionable. The app is mostly greyscale with a green accent for important action items and success states.
The three main features of the salesperson side are searching store inventory, inputting items, and scanning labels. Although the app is relatively simple, salespeople would most likely receive training before using it.
To input an item, the salesperson follow these steps:
1. Sew on a QR code label identifying the item as part of the loop. (The salesperson would have a device like a sewing gun specifically designed to quickly and easily complete this task.)
2. Take photos of The Loop label, care tag, materials tag, brand and size tag, front and back, and 2 close ups. (The app walks the salesperson through this process.)
3. The app auto-generates information about the item type, brand, size, color, materials, and care instructions, by analyzing the uploaded images. This saves the salesperson the time of inputting these manually. 
4. Manually enter the item’s condition, and the app auto-generates a price point based on the condition and other information about the item. The AI-driven pricing not only provides fairer pricing estimates, but also makes the job of a salesperson easier.
5. Review and edit the listing before adding the item to The Loop, where customers would be able to browse inventory from the app.
Sew on label
Sew on label
Take photos
Take photos
Generate item info
Generate item info
Add item condition
Add item condition
Review + finish
Review + finish
If a customer buys and later brings back an item that is already part of The Loop, the salesperson would be able to:
1. Scan the label to see the previously uploaded information about the item.
2. Update the condition of the item.
3. Add additional photos if necessary. (If the salesperson marks the item as worn, they would be prompted to select the signs of wear and upload additional photos to make sure the listing is up-to-date and accurate.)
before marking the item as back up for sale in The Loop.
Scan The Loop label
Scan The Loop label
Update condition
Update condition
Add photos
Add photos
Here is a preview of what the consumer side would look like. Shoppers would be able to:
1. Browse items in stores near them.
2. Search for items available in stores near them.
3. View details about items including condition, location, garment history, and styling suggestions.
Here is the interactive prototype of The Loop once again:
Below are my reflections on the project:
Given more time, I would user test my prototype with people who work in secondhand stores, and I would strengthen the branding and visuals of the UI.
I would also build out edge cases such as if information is unavailable or needs to be manually edited, and I could even build out the consumer side to include features such as onboarding, wishlists, and the capability to reserve items.
Through this process, I learned that people prioritize convenience, efficiency, and trust when it comes to shopping, and that they are interested in low-risk and eco-friendly ways to try new styles.
Thank you for reading, and please don’t hesitate to reach out to zhana437@newschool.edu if you have any questions or feedback!

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