Despite the fact that the sale of used furniture online has skyrocketed, clutter still remains an issue in American homes, with 1 out of 10 Americans renting offsite storage. To further exacerbate this issue, the landscape of secondhand e-commerce is shrouded in distrust.
Popular online marketplaces lack the tools to ensure good-faith sales, purchases, and experiences. With only so much text and media to assess an item, how might we accurately portray used furniture pieces to wary customers?
Designer Prototyper Researcher
March 2022 - August 2022
Rentable is an app and service which allows renters to view and rent used furniture from other people. Using 3D scanning, furniture owners can scan their furniture, and post to our application. On the other side, renters can place these 3D scans into their homes using augmented reality (AR). Once a piece pairs well with their space, they can rent it from the furniture owner for an agreed upon amount of time. This way, furniture owners can easily gain a feel for new furniture, and lessors can reduce clutter in their homes.
After Effects Blender Figma Illustrator Photoshop Premiere Pro Unreal Engine 5 Zoom
3D Modeling 3D Scanning Augmented Reality Game Engines Literature Review Product Design Rapid Ideation Rapid Prototyping Qualitative Interviews
Rentable is a mobile app that allows furniture owners with spare furniture to 3D scan and upload their pieces for interested renters to investigate (using AR) and rent.
3D scan your piece.
Too much furniture in storage? In addition to pictures, set up a listing with an accurate 3D model of your piece, using our in-app 3D scanner (using LIDAR technology).
Tag your damage
If there are any imperfections, tag them on your scanned 3D model. By tagging minor damage, you are establishing credibility with a potential renter, who wants to know what their product has been through.
Upload your piece.
After editing your description, view how your product will look to potential renters. Then, just upload!
View your piece in 3D...
Look around your 3D model to spot any defects, investigate the dimensions, and view the piece in various lighting conditions.
...or investigate it in AR!
Scan your room and place the piece using AR to see how it interacts with your space. You can then move it around or add more pieces to complete the look.
Check out, sign, and wait!
Designate which dates you want to rent the furniture for and agree to the furniture owner’s contract conditions. One of our delivery people will inspect and pick up the piece to deliver to you! At the end of the period, our delivery people will bring it right out!
We conducted a competitive analysis review of popular secondhand e-commerce sites, which include:
Facebook "Buy/Sell" Groups
This was done in order to assess the current state of the online secondhand e-commerce landscape. Aspects we reviewed and compared include (and are not limited to):
Finding 1: Photography Guidelines can be wildly different.
Photography guidelines for used items are scattered and divided amongst the sites. They range from nonexistent (especially when specific to furniture) to loose advice to near-professional studio guidelines.
Finding 2: Terms used to describe Furniture Condition are vague.
Words like “New” or “Used” are usually not enough to capture the state of one’s piece of furniture, and these terms are often not specific to furniture, being used to describe other items such as clothing or electrical appliances.
Finding 3: Mobile and desktop platforms are rarely, if ever, unified.
For the same site or application, features in one platform will be absent in another, leading to major confusion when switching to another device.
It's really shitty to have bought something and to have it put into the space to then only learn at that point like, ‘Okay, yeah, it fits.’
We conducted qualitative interviews over Zoom with renters, buyers, and sellers who have rented/bought/sold secondhand furniture within the past year.
From various survey posts we made on several websites (I posted on Instagram, LinkedIn, and Nextdoor), we managed to get 9 interview participants from 216 participants. I moderated and took notes during the interviews.
What we were trying to gain from the interview was an understanding of trust in secondhand markets, the requirements for a successful purchase, and a renter's/buyer's overall search-to-purchase journey.
Myself and my teammate Madison conducting an interview over Zoom.
Our interview consisted of four parts:
A semi-structured interview which delved into trust and success for buyers.
A walkthrough exercise where participants used their preferred e-commerce platform and looked for an item of their choice.
A card sorting exercise where participants sorted listing aspects by priority.
A sketching activity where participants sketched their “perfect online listing.”
Some of the activities we had our participants do (click to see).
From the interview, we sorted through each 60 minute interview and synthesized our information by doing the following.
We affinity diagrammed quotes from our interview into major findings groups.
In our card-sorting activity, we did quantitative analysis by placing values on listing element ranks.
Through the sketches, we reviewed which aspects participants decided to draw and talk about.
Affinity diagramming the quotes from our interviews on Figma.
Insight 1: Trust has to built. Sellers are “guilty until proven innocent,” and must prove that they are reliable to buyers.
Buyers look for cues of seller credibility—mutual friends, ratings and reviews, and seller transparency—that make a seller more trustworthy and mitigates risk.
Insight 2: If it looks too good to be true, it probably is. Exposing an item’s imperfections signals that a seller is trustworthy.
Stock and photoshopped images are easy to identify and are deemed deceptive. Buyers are willing to tolerate mild damage and imperfections—as long as they know about it upfront.
Insight 3: More really is more. High-quality photos and detailed information make the furniture feel real and ownable.
Detailed and accurate information including dimensions, condition, aesthetics and materials help buyers imagine the item as their own and how it will interact with their entire space.
Myself and my teammates making a used-furniture buyer's journey map on the whiteboard.
HOW MIGHT WE
more accurately portray and describe furniture to make it easier for buyers to envision how a piece of furniture interacts with its anticipated environment?
Based on our insights, we tried to go for the solution with the most impact with realistic amounts of effort.
To create a solution, we focused on addressing our research insights. Our solution needed to:
provide credibility to the receiver.
provide avenues to show imperfections on the furniture.
provide as much information about the furniture as possible, including dimensions, material, and condition.
We came up with 60 ideas in order to address the issues behind ascertaining trust while shopping online for used furniture. We found several themes in our ideas: furniture renting, furniture flipping, AR, 3D scanning, AI, third party expert.
We then grouped our ideas into two groups: features and business. We then decided on furniture renting (to address America’s clutter problem) as our main business idea, and decided on the features that would make it in; AR, 3D scanning, and AI. We believed that:
AI would help provide additional credibility to the furniture owner through style matching and defect detection.
3D scanning would provide a realistic model that lets one view or represent defects.
3D scanning would also provide details about the size, material, and condition of the used furniture piece.
We aligned on our pillars: our application must be easy-to-use, trustworthy, and stress-free.
Me and my group-mate Madison discussing ideas.
Some of the ideas we created during our ideation phase.
We then made hypothetical storyboards to conceptualize our furniture renting idea, especially in which features potential users might be interested in.
Hand-drawn storyboard (done by me) of the Rentable (at this time called Renterior) experience.
There were 3 aspects that we needed to test for our application: 3D scanning a piece of furniture, placing that object in AR, and the flow of renters and lessors.
We used a variety of 3D scanning applications, such as Scaniverse, Polycam, and 3D Scanner app. We wanted to see what the process entailed and the issues that might arise for the average person. We scanned multiple types of furniture, such as chairs, sofas, and tables.
Madison scanning some furniture with Scaniverse.
AR prototype, done in Unreal Engine 5.
We then prototyped furniture placement in AR. I was able to get a working demo created in Unreal Engine 5, which allowed one to place a piece of furniture onto a flat surface using their phone.
Based on our investigations and preliminary prototype user tests, we formed some initial findings:
Certain gesture inputs were way too similar in AR (such as pinch for scale and pinch-spin for rotation, leading to accidental inputs).
The instructions given to us were not super clear (especially when it came to scanning underneath the furniture or setting up proper lighting conditions for scanning).
We addressed these concerns in our app design by:
Adding clear instructions at the proper parts of the flow (so as to not add too much clutter as was often the case).
Adding a radial menu for 3D model interactions in AR (accessible by double tapping, a flick in a cardinal direction would be a clear command as opposed to holding or pinching).
Clear instructions and easy-to-use interfaces were the key to making a painless 3D scanning and AR experience.
User Flow for Renters and Owners
We created a flowchart on possible user actions using our app, especially in our key aspects for our final artifact.
The screens, menus, and buttons used in our app. From this we made high fidelity screens for our prototype for user testing, which detailed the core aspects of our application.
Test our prototypes with our intended users.
Given our 3 month timeframe, we did not have the time test our prototypes with our intended users. Our next step would be to test our Figma mockups with furniture buyers, owners, and renters to critique our app, and to test the ease of 3D scanning and AR using 3D scanning apps and our AR mockup.
Create a more in-depth business and logistics model.
We focused more on the service and app feature side of the app during our 3 months of prototyping a solution. As for the logistics and business model (such as transportation methods and the pricing of furniture for profitability), we touched upon those aspects based on existing services, but recognized we didn't have the time to flesh them out. Also, it isn't in the scope of our expertise; we would ideally find someone with knowledge in supply chains and business to help build upon these aspects.
Create a solution that’s accessible for your target audience.
A key portion of our service was LiDAR scanning, which only a few phones have at the moment. Although we envision a future where this technology is more commonplace, we still need to provide an avenue for people who currently are unable to use it. Thus, we also allow users to upload photos to their listing, which can serve in place of a scanned 3D model.
Understand the technology behind your product to figure out how users can utilize it.
Our service uses a lot of emerging technology, such as LiDAR, AR, and AI. Instead of hand-waving our services as "technological magic," we researched each technology by reading multiple papers to really understand how they worked, and in what situations they would be useful.
Test your user research methods; make sure user testing activities are accessible.
During our user tests we did multiple activities where we observed the users. For these activities we used software which were familiar with us (such as Figma and Miro), whereas our non-designer participants would be confused on how to use them (and had to make accounts as well). In the future we would use tools that were more accessible.