Pictures used above are from these designers: Ettore Sottsass, Giorgio Ceretti, Oki Sato/Issey Miyake, Gae Aulenti, Gio Ponti, Gaetano Pesce
Refurnish Team
Mir Sung and I are both Cognitive Systems students at UBC and part of the same Brainstation BootCamp cohort in spring 2020. Given that this project stemmed from this course, we were limited with our time working on this project. If we had more time I would have liked to conduct user testing with a bigger sample and add one final round of testing as I will explain later. This stemmed from his expertise in online marketplaces and my passion for furniture design! Overall, my project partner and I were very happy with the experience we gained on our first design project and enjoyed the collaboration with other students in class!
Despite the current dire state of furniture waste (f-waste) recycling, there are still ways in which many are attempting to give their unwanted furniture a second home, through online marketplaces like Craigslist, Kijiji, Facebook Marketplace, etc. However, these online marketplaces often have the reputation of being unsafe, inconvenient, and littered with choosing beggars and no-shows. As such, we wanted to explore how we could create a centralized application where unwanted furniture can be recycled properly or find its new home.
User Research
To best understand potential users we interviewed college students, recently married couples, furniture retail designers, showroom representatives, and anyone who would be moving in the near future. We asked about their occupation and age, and their experiences purchasing online and with online marketplaces. We prepared questions to expand on depending on the answers we received.
We asked questions such as:
From the interviews, we learned that having a target user in mind can bias our judgment and can sometimes hinder good design. For example, we learned that a subsection of target users - furniture retail designers and showroom representatives - did not actually have a need for the application. In their case, once their client has finished choosing the furniture they would like to choose, the designers return the unwanted furniture to the original retail store.
Among the college students we interviewed, the biggest frustration in purchasing/selling second-hand furniture was the lack of transportation to pick up or drop off the furniture. Another concern was the lack of security between buyer and seller. Therefore, we kept in mind that security and convenience were the biggest issues for which we needed to design.
Summary
With the architecture in mind and set, we decided on the features that would put convenience and security first.
Convenience
Security
By using POP for our first round of testing with paper prototypes, we found several issues in our chat feature as well as our categories/filter option in our user feedback.
Results and feedback:
The chat function was confusing for the users. We had attempted to streamline the purchasing process with the built-in chat function; however, users were confused during this process. From this experience, we learned to keep things as simple as possible for the users and let the user's behaviour speak for itself.
When considering filters versus categories to narrow down searches, we chose categories. However, the users felt that when browsing for items the use of filters made more sense. In particular, the use of checklists for the selection of categories was also unintuitive.
Wireframes and Prototypes
Buyer - Purchase Task
Buyer - Purchase Task
Recycling Task
Seller - Uploading an Ad
The results of our final test:
100% of participants completed all three tasks
However, a prompt was needed for 2 participants to complete purchasing through chat.
The qualitative data derived from the user interviews pointed to a concern for the floating icons and whether they would interfere with the postings behind the icons.
As this was a project stemming from a course, we were limited with our time working on this project. If we had more time I would have liked to conduct user testing with a bigger sample and add one final round of testing,
Selected Works