Aery

Overview

How might we help young people customize their living space for comfort when they are at the start of their careers?

Aery is an end-to-end home customization service based on both pre-owned and brand new furniture and items. It makes home customization easier for constantly moving young adults, enabling them to focus on living their best life at home.

The platform’s AI recommends combos of pre-owned or brand new items that fit users’ needs and limitations. Users can make changes to and visualize the combos in a 3D playground, and then place orders from the platform. When moving out, one can simply sell the items back to the Aery to save the troubles of getting rid of them in other ways.

This project was for Strategic Innovation in Product/Service Design, a course that's part of the SVA MFA Interaction Design program.

team

Sophia Deng, Yuan Chen, Frank Gong, Kevin McElroy (Fjord)

timeline

Sept-Dec 2019 (15 weeks)

Key roles

Research, synthesis, ideation, prototyping, UI/UX design, final presentation

Explore the problem space

Homeownership downturn

Millennials and Gen Z aren’t buying homes at nearly the rate of previous generations.

What are their true aspirations and obstacles to home ownership? What might help them achieve their ambitions?

To have a quantified understanding of this phenomenon:

“The homeownership rate among millennials ages 25 to 34 is 8 percentage points lower than baby boomers and 8.4 percentage points lower than Gen Xers in the same age group”*

*Millennial Homeownership - Why Is It So Low, and How Can We Increase It?

Insights from interviews and desk research

Among the interviews with 16 renters and homeowners, we noticed some recurring topics that resonate with our desk research. We grouped some of our findings under 4 categories:

Preferences

When choosing a place to live at, young people values proximity to work location, personal space, being able to work at home, and being close to their community.

Modifications

People do want to customize.

Homeowners have more advantages on this point. But maintenance is a hassle.

For renters, moving furniture is troublesome.

Besides, People are into IoT facilities. High-tech is a trend.

Mobility

The young generation has distinct and independent personalities.

They are not settled. They plan on moving around to follow career opportunities.

Having a family can impact their decision to buy a home.

Homeownership

Most of them are still renting.

Their financial situations prevent them from getting a home. They might get support from their family.

Most just have a vague plan on saving up for a house.

Buying a house is seen as an investment.

However, the home buying process is a pain.

Narrow down the scope

Home customization

The current renting experience

Since renting has been the major form of accomodation for young adults, we were seeking opportunity areas in the current journey. The transition period from the old space to the new one stands out as a big source of pain points. We hence decided to tackle the area of home customization during and after moving.

Narrow down the target user group: urban young professionals

Entry level
workers
~80K
Age-range
22-
30
Move frequently
Unmarried
Living in
urban area
Career-oriented

Feel the pain. But why?

Our target group does want to enjoy a personalized home.
What is stopping them?

We found the root in the traits of the life stage they are at:
young professionals lack money and time, and are too mobile.

A new problem statement

How might we...?

Shape the solution

A smart way to customize

Ideation

After a brainstorm session, we voted on a few ideas that we thought interesting and promising (votes marked with green dotes).

User flow

We then combined those ideas to come up with one single user flow:

3 versions of wireframes

To not limit ourselves, we made 3 different sets of wireframes separately to explore the best structure and medium of the solution.

Learn from user testing

We showed 10 people the wireframes to get some feedback. There are 3 key takeaways:

01. Needs confirmed

The current features meet people's needs. They thought this would be a useful tool to decorate their new living space according to their needs and preferences.

02. platform Medium

The web platform is preferred over a mobile app. This is also backed up by statistic evidence (US shoppers save big-ticket online purchases for desktop).

03. Shorten onboarding

The users think the onboarding process is too long. We wanted to capture different aspects of the user' needs altogether in the original design, but it might bore the user before they finally gets to start using the product. We hence decided to shorten this stage, and gradually learn more about the user laster on as they uses the service.

Unified information architecture

Market research

What other services are out there?

While we were shaping our solution, we looked at other home-related services in the market, and compared our solution with a few main competitors.

We believe our product has great competitiveness in personalization, while also maintaining advantages in other aspects. Our price would not be the cheapest, but is still within an acceptable range; this also enables us to keep higher levels of product and service quality.

Final product

An end-to-end home customization service based on pre-owned furniture

Intro video: Aery

Major sections

Reflection

Successful, but can be better

Worked well: Needs met

This is a successful project in the sense that it well addresses the initial prompt we were given, and people see practical use in the features according to the feedback.

This housing trend that young people rent temporarily instead of buying will continue, which is a promising opportunity for our product to expand. We hope it can bring an easy aesthetic lifestyle and sustainability to a global scale.

Could improve: Reach a wider audience

It would have been better if we could interview a wider range of Gen Z and millennials.

The people we could talk to were all from our own network as a result of lack of resources. This is a biased representation of our target audience in terms of education, job, gender, and race. We shaped our target user according to what they are like, because we have a  limited understanding of people we could not reach.

This can be a next step for us: to validate whether our solution works for the groups that we couldn't reach, and see if we can make it more inclusive without compromising the basic user experience.