The Project

This was a two-and-a-half week project that had me working with a group of two other General Assembly students to explore new feature additions for Move Loot, a rapidly growing used furniture buying and selling startup in San Francisco. We worked directly with Move Loot and presented our design solutions and prototype to them at the end of the project. 

What is Move Loot?

Move Loot is a San Francisco-based startup that aims to be the easiest way to buy and sell used furniture. Their business plan is simple: Move Loot picks up your old furniture for free, stores it in their warehouse, takes high quality photos, and posts the pieces up for sale on their website. When your items sell, you get 50% of the profit.

Move Loot's Business Goals

Move Loot is doing a great job serving one type of user right now. This person is someone who doesn't want to spend much time on the site browsing, and just wants to buy some furniture and get out.

Based on initial research they'd done, Move Loot came to us with a few ideas for exploring features that cater to a different type of user who values research and item quality. These included ideas for style finding, collaborative shopping, and expert advice. To verify the reasoning behind their ideas we needed to dive into their research to better understand the user and how the ideas would affect them, and align on a problem statement.

The Problem We Identified

Our Solution

How did we get there?

Move Loot's Research

Move Loot came to us with a large amount of user research completed. This included insights from a user survey, 10+ user interviews, and three high-level personas.

Synthesis

In order to bring our own fresh perspective to the data, we performed our own affinity mapping and mental model exercises based on the existing research (essentially synthesizing Move Loot's synthesis) and were able to verify a few of their conclusions.

Among the insights we gained:

1. There's discomfort and uncertainty when buying used furniture online.

2. People enter the shopping process with an open mind.

Our Additional Research

We also did our own research in order to better understand Move Loot's users and supplement the data we already had. This involved 5+ user interviews and a competitive analysis of retailers we determined were competitors to Move Loot.

Interviews

Among the insights we gained from talking to users:

1. People are interesting in getting input from people close to them.

2. Clear return policies build trust in users hesitant to buy used furniture online.

Focus on the Persona

With the research synthesized, we were able to better understand the most important persona for Move Loot's business growth, named Brianne.

Important insights about Brianne:

1. She is a young mother who is budget conscious, but still wants quality pieces that will last a long time.

2. She can become unsure of how certain pieces will fit into her current style.

3. She spends a lot of time compiling research, which costs precious time when items sell out quickly.

4. She likes to have input from her husband Ryan, but sending him a list of links to various pages of furniture is frustrating and time consuming for both.

5. She is worried items won't look like they do in the site's photos when they are delivered.

Sketch / Test / Iterate / Repeat

We individually made rough sketches of our initial solution ideas that included explorations of collaborative shopping flows, interactive style finders and expert advice portals. This process was extremely valuable in getting our ideas visualized on paper and in the open.

We were then able to come together as a group and combine the best-received ideas from our sketches and create a paper prototype for user testing.

Insights from Testing

Testing with the paper prototype revealed a number of insights that we were able to bring to our next iteration, a medium-fidelity digital wireframe.

For example, our more complex collaborative shopping features were met with confusion from a the majority of testers. This enabled us to scale down those features in the iterations leading up to our high-fidelity wireframe and focus more on enhancing the contextual shopping and research organization aspects of our design solution.

The Solution We Presented

Consolidated Styles and Scenes

Shoppers can browse specific styles of furniture and easily access Move Loot's scenes, which show pieces arranged into rooms like one would see at a furniture store's show room.

Contextual Shopping

Interactive scene views provide context let shoppers hover over items for more detailed information.

Personalized "Loot List" Slide Tab

Shoppers now have an effective way to organize their research, star their favorite items and styles for reference, and see personalized suggested products, all available without leaving their current page.

Next Steps

Further Exploring Collaboration through Notes

In our current design, people are able to share notes on items in their Loot List and the receiver can view them. But what if the receiver wants to comment back without making a Move Loot account of their own? One idea for exploration includes a shared collaborative shopping landing page where a user can leave comments without logging in.

Expert Advice

In our interviews people almost universally talked about getting feedback from people they know before seeking expert advice. Because the project was completed over two and a half weeks, this led us to place the expert advice idea on the back burner and focus on other problems we found to be more important to users. However, I still believe this is a topic with lots of potential to pursue based on the primary persona's pain points and positive comments from people we interviewed.