Yarn is a set of laundry tools that is re-imagining the humane laundry experience.
User Experience Design,
UI Design, ID Concept
2022; 14 weeks
Figma; ProtoPie; Arduino;
Adobe Ae/Pr/Ps; Fushion 360;
Olilo Ye (Research; Ideation; Testing; UX/UI Design; Industrial Design)
Brenna Liu (Research; Ideation; CMF Design; Industrial Design)
We believe that every moment of life is worth enjoying. People shouldn't be distracted or stuck by a cumbersome experience. We want to set everyone free by designing a new generation of laundry systems to make the laundry process effortless and worry-free.
The activity around washing may sound simple but it’s actually quite complicated.
The clothes themself have blocks of symbols communicating how they need to be treated. That is reflected by different sets of completed icons and symbols on the surface of the machine.
In addition to icons and symbols there is a large amount of modes on the washing machine, most of which will not be used by the user during the laundry. All of these designs are intended to make laundry easier and more efficient, but they don't work as well as they should. Therefore, we designed yarn to challenge this situation.
In this phase, we collected secondary data on user opinions, behaviors, and the market.
Also identified what we want to learn from the users.
We interviewed 5 target users to learn their laundry habits, usage of laundry modes and functions, perception of fabrics, usage of laundry supplies, laundry sorting habit, laundry expectation, attitude and handling of stains, and trust in laundry tools.
Users have a very high learning cost for various washing modes. This has increased the user's guessing time and uncertainty in the laundry process.
Users have limited trust in washing machines, especially when it comes to dealing with stains. The more stains on clothes, the less trust users have.
The wash label system does not effectively communicate to the user how the clothes should be washed, while ignoring the information the user really wants to know(Color Bleeding / Fading Level).
men always use the same wash program and ignoring the washing instructions.
women use three or less wash program.
“There is no explanation of what these modes mean, and I rely on my guesses and experiences when I use them. In general, to reduce the risk, I only use modes that I’m already familiar with.”
-Interviewed Users
Users have a very high learning cost for various washing modes. This has increased the user's guessing time and uncertainty in the laundry process.
Users have limited trust in washing machines, especially when it comes to dealing with stains. The more stains on clothes, the less trust users have.
The wash label system does not effectively communicate to the user how the clothes should be washed, while ignoring the information the user really wants to know(Color Bleeding / Fading Level).
The main role of a washing machine is to deal with everyday dust; users do not have confidence in the machine to handle details or stubborn stains.
Users have a very high learning cost for various washing modes. This has increased the user's guessing time and uncertainty in the laundry process.
Users have limited trust in washing machines, especially when it comes to dealing with stains. The more stains on clothes, the less trust users have.
The wash label system does not effectively communicate to the user how the clothes should be washed, while ignoring the information the user really wants to know(Color Bleeding / Fading Level).
of the people can identify washing signs correctly.
women use three or less wash program.
“When I wash a new cloth, I hand wash it to make sure it doesn't lose color and damage other clothes.”
-Interviewed Users
With the insight we got from previous research, we are gradually specifying our user personas. We want to reach more users by designing for users with special washing needs or scenarios. Therefore we have chosen these two personas, Henry and Cora, also indicate two main user groups for our system: people who wash precious or premium clothes and people who wash a large amount of clothes.
Henry Carson
Freelance Photographer
Laundry Type
Middle-premium Cloth
“It takes efforts to taking care of clothes.”
He sees clothes as a representation of his self-identity, which drives him to buy more middle-premium clothes. They are not cost-effective for dry cleaning, but the washing machine may destroy them.This made him cherish these clothes and wear them only when it‘s important.
Goals
-“Less Effort, Better Result.”
-Maintain the cloth in it’s highest performance.
-No harm to clothes & wash out dirt.
Cora Lucas
HR Director
Laundry Type
Large amount of baby/Kids Clothes
“Hope my children to be able to wash their own clothes.”
She always chooses fabrics that are easy to clean, don't lose color, and don't require extra care for her kids, which can make her laundry easier. Kids put on a fashion show every day, which leads to mountains of clothes to clean every week. Sometimes mistakes inevitably happen in the process. She made decent guesses based on all the knowledge and information she had, but choosing a laundry mode was still confusing.
Goals
-Convenient.
-Use and leave interaction.
-Serves as an assistant in the laundry workflow.
The activity around washing may sound simple, but it’s actually quite complicated. Getting it right requires certain skills and knowledge about stains, fabrics, laundry solutions, laundry settings, and so much more.
In order to reach our goal, we have broken down the bigger problem into multiple smaller How Might We questions in the current user journey.
The HMW problem has successfully expanded our perspective. Several rounds of brainstorming around these problems were conducted within our team.
Humanized way to communicate laundry preferences
Eliminate uncertainty and guessing in the laundry process
Building trust in washing machine's capability to handle stains
Minimize efforts for laundry categorization
For the ideas belonging to the four design goals, we deconstructed them into detailed functional and informational elements. These elements were further built into a preliminary information architecture.
During this phase, we conducted two rounds of usability testing with 10 users. With the help of participants' feedback, we iterated our prototype three times, from low-fidelity sketches to the final design.
The following pages are mainly showing part of the iteration on two key flows(Laundry Setting Flow & Stain First Aid Flow), if you want to learn iteration on all flows, please shoot me an email(zexi_ye@outlook.com).
Through usability testing we realized that because many new concepts were introduced in the new laundry system, users were not sure if they understood the meaning of these unfamiliar concepts correctly and were hesitant to make a selection.
We added an onboarding process to give users an idea of the new concept before starting to use it. We also placed multiple icon buttons next to related functions so that users can get an explanation if they are unsure of their understanding.
The distinction between the 3 modes of laundry(Valet Laundry, Laundry Presets & Manual Mode) is not obvious enough for users to clearly feel the benefits and drawbacks.
Adjust the interface of each mode according to their scenario of use.
- Valet Laundry: The user expects the laundry task to be transient posture(comes and goes), in which efficiency comes first.
- Laundry Presets: Users have the need to do laundry according to certain routine in their lives.
- Manual Mode: User have the need for taking total control of the washing machine.
The next gen laundry system that
enable the humane laundry experience.
The Keystone Product
Yarn contains two design systems for the mobile side and the washing machine interface side. In this process, we pursued consistency in cross-device operation while taking into account the characteristics and usage scenarios of different devices.
As we interact with real users, we are learning more and more about what they expect their laundry experience to be like, but the limited time frame has allowed us to implement only some of the key features, so next step we will:
1. Refine and iterate on some minor flows:
Continue to iterate and improve the features related to clothes sorting and improve the interface on the laundry basket.
2. Extend to more use cases
For example, designing models that can be operated even by children.
3. Statistic study on user test to validate this concept.
Turn the screen sideways for better experience.