#research_process

• 01 •

How do I focus on the right problem when I research?

Health and well-being is an enormous problem area—eating is only part of it. The more I researched over the internet, the more I felt lost. I couldn't figure out what is supposed to be the "correct" answer for a healthy eating pattern since the answer varies based on different research studies. This made me realize that I needed some professional help. So, I decided to do a series of interviews with experts in eating: the nutritionist. These interviews helped me understand the science behind everyday eating much more efficiently and drew my attention to the young adult group—they seem to be less caring wether their eating habits are healthy. Tap the box below to see the highlights from the interviews.

“People don’t (really) care why they eat something healthy, they just want it done... The age of having sicker diseases is getting younger. We live longer but with more disease.”

“Many people skip their lunch meals because they don’t want to lower their energy level in the afternoon...adding snacks or having smaller meals with more frequent can really help that.”

“How to tell people eating healthy is simple? If you buy food properly and cook at home, it will be much cheaper and healthier. The thing is how do people educate themselves on what is healthy."

• 02 •

A survey helps me target my audience

After I interviewed nutritionists, I had a much better idea about my target audience and a narrower direction to move on, especially when Zeina Amhaz mentioned “we live longer but with more disease.” Young adults started to catch my attention. I’m very familiar with this group of people as a young adult myself, but I can not say that every young adult has the same exact habits as me. So, I did a short survey to see if some of my assumptions were true. The result turned out pretty insightful. Most of the people who filled out my survey said they are busy with school life and usually skip meals, especially breakfast.

Survey Result

#research_findings

• 01 •

information is overwhelming

There are tons of different diets that you can find online. For example, If you search for plant-based diets online, you probably can find at least 20 different ways how you eat healthier in terms of having more vegetables. However, based on my user research, only 1/4 would commit to a specific diet. The majority would prefer to eat whatever they like or want

• 02 •

current products are facing a very specific audience

If you take a look at current dietary support apps, you will find that most of them are mainly designed for weight control, specifically weight loss. For example, Noom, a popular dietary support app, is mainly focusing on the audience whose goal is weight loss. Users like my size who are looking for dietary advice are totally excluded from using the product.

Existing weight control apps

• 03 •

building new habits is inherently hard

A behavior change always requires a lot of time and effort, as well as repeating actions. This process is inherently boring. Also, whenever we want to change something about ourselves, our expectation is pretty high. We want to see changes right after we start. But the reality is, the change might be almost invisible in the beginning. And will raise rapidly after the valley of disappointment. Even though it takes almost the same amount of time for a complete change, many of us would quit when we couldn’t pass that point.

#assumptions

In the first step of ideation, I mapped out assumptions based on the knowledge I've learned so for from research and categorized them by the topics (image [01]). Then I valued the assumptions in a Risk Map (image [02])and marked the assumptions that are unknown and highly risky.

Here are the two assumptions that I found to be most unknown and worthy to develop further hypotheses and prototypes.

• 01 •

Making healthy eating less overwhelming will help people form better eating habits

• 02 •

Making healthy eating more fun will help people form better eating habits

[01] Categorized Assumptions

[02] Categorized Assumptions

#proposals

• 01 •

How might we increase the quality of daily meals for young adults who live alone and are usually busy working?

hypothesis 1.1

I believe that building a smart cookware system operated using mobile phones for busy young adults will help them cook more at home and therefore eat healthier.

hypothesis 1.2

I believe that auto-generating simple recipes based on preference for young adults will help them be more comfortable about cooking

hypothesis 1.3

I believe that a planned menu based on preference will help young adults not skip meals

hypothesis 1.4

If preparing and making food is simple and quick enough, people will more likely to cook at home

• 02 •

How might we encourage young adults to make healthier decisions in eating?

hypothesis 2.1

I believe that a gaming experience that assigns people doable tasks along with a reward system will help people eat healthier

hypothesis 2.2

I believe that a virtual creature who can visualize the exaggerated consequences based on people’s eating choices will help them eat healthier

#prototype_01

I started prototyping with Hypothesis 1.3 (I believe that a planned menu based on preference will help young adults not skip meals).

1.1.1

Ask a pair of good friends to write down a meal plan for a week for each other. Record how much each one of the testers follows the plan and how often each one skips a meal.

1.1.2

Ask the tester to fill out a meal plan form. The form includes two parts: one is a meal history of the past week, and the other is a meal plan for the following week.

1.1 Feedback

• The three-meals plan is typical but may not be applied to everyone.

• What exactly the “plan” would look like? It feels hard to make decisions about what to eat in a week

• I don’t really want to spend such an amount of time on doing this plan

• What if I just don’t want to follow?

1.2.1

Ask testers a few questions about their preference for breakfast/a.m. a meal and help them make decisions for choosing breakfast. The tester will receive a relatively healthy breakfast that I order on food delivery services for the following 3-5 workdays.

1.2.2

Fill out a history form of what did you eat for the last five days. Assign testers a doable task that help them improve their eating habit just

1.2 Feedback

• It might be good if I can record each meal as I go since it takes time to recall every single thing I have had.

• I didn’t notice that I wasn’t as healthy as I thought.

• Sounds like a pretty doable task
takes• Bias: try to ask people out of network to test• The motivation for finishing the task isn’t clear

reflection

Here are some key insights from the first round of prototyping:

• There are gaps between perception and action

• People maybe react more actively if the task is assigned by their loved ones

• People tend to collect achievements while they are gaming

After I finished testing these two quick prototypes, I became much clearer about what I wanted to deliver in this project. I don’t want this product to add anxiety and pressure to the users since my target community is young adults who are already stressed. The product shouldn’t be like forcing them to do something they don’t enjoy and interpreting their original daily routine. Instead, it should encourage users to eat healthier smoothly and blend in with their current behavior. The user experience should be cozy, relaxing, cheering, and supportive.

#prototype_02

How can I make this (eat healthily) process more fun and engaging?

With this question in mind, I shifted my focus from Hypothesis 1.3 to Hypothesis 2.1 in the second round of prototyping—I believe that a gaming experience that assigns people doable tasks along with a reward system will help people eat healthier.

User Journey Map 1.0

2.1

1/ Take care of this creature by eating healthily yourself

2/ See if it can survive based on what you ate the past five days

3/a Blooming? You earn $5 from me!

3/b Dies out? You have to pay me $5

4/ Continue the game for the following week

Initial sketch on the creature

2.1 game system

This is a virtual creature that helps visualize unhealthy choices about eating. It will reflect the choices you made for eating: it initially has 5 petals as its HP; the petals will fall off when you make any unhealthy decision (the HP change is listed in the chart); when all petals fall off, the little creature will die.

HP changes when there is an unhealthy decision made

The creature has different emotion when it loses petals

2.2

1/ Take a photo, and your meal is auto-captured using a build-in algorithm

2/ There will be a time range set for each meal based on your sleep data

3/ After collecting three drops, the flower will bloom under different conditions and be recorded in the calendar garden

2.2 game system

The creature, instead of having 5 petals initially (like in the 2.1 game system) and losing them when there is an unhealthy decision made, will absorb the energy drop and grow different kinds of flowers at the end of the day: it will bloom a golden flower if you have been super healthy today; bloom a regular flower if you have been maintained in good condition; the flower cannot be fully blooming if you need to improve the food choices; its flower will wither if you have been super unhealthy today.

• Golden Drop = very balanced nutrition super healthy meal

• Clear Drop = Enough nutrition relatively healthy meal

• Muddy Drop = unbalanced nutrition food (e.g. meat only)

• Contaminative Drop = allergic/unclean food

• Empty Drop = Skipping meals

• Pink Drop = Happy meal but it’s junk food

Energy Drop Ststem

2.3

1/ Briefly interview testers about their daily routine, eating preference, and health goal for the following couple of days

2/ Ask the tester to draw a random shape at least for three days (it will be their eating companion)

A. Daily

B. Weekly

3/ Send reminders for meals with their elfin in a different emotion. e.g. hungry; hangry; starving

4/ Ask testers to send their meals

1. Photos

2. Text

3. Food delivery screenshot

5/ Their elfin will act differently based on the level of the healthiness of their meals

6/ By the end of the day, the tester will grow a flower that can unlock a flower collection, and get a cheer-up sentence

7/ They will collect different energy drops based on what they eat

2.3 game system

The creature’s reaction and energy drop system stays the same: react based on your choice of eating and grow different kinds of flowers at the end of the day. Different energy drop represents different score: the most unhealthy meal is scored as the lowest, and the most healthy meal is scored highest. If you eat on time, you will get the energy drop with its full credit; if you don’t eat on time, the value of the energy drop will be cut off by 40%. The average score for the day will determine what kind of flower you get at the end of the day.

2.3 feedback

• The creature's reaction stimulates curiosity and expectation

• Emotional connection works pretty well

• Think more before making choices for eating

• The reminder didn’t really follow the daily routine of the tester that well

• If there is a delayed reminder, it might also delay the tester meal.

• Be more aware of the nutrition balancing

• Knowing there is a person seeing all the daily meals felt a little pressure

Flow Chart

1/ Briefly interview testers about their basic information, daily routine, eating preferences, and health goals for the following couple of days

user journey map 2.0

2.4

1/ Briefly interview testers about their basic information, daily routine, eating preferences, and health goals for the following couple of days

2/ Assign them a light-hearted challenge that based on the brief interview

3/ Ask the tester to draw a random shape within one stroke using the Notes app

4/ Send reminders for completing the challenge with their elfin in different emotions. e.g. hungry; hangry; starving

5/ Their elfin will act differently based on how well they have performed in completing the challenge

6/ The tester will grow a flower which can use as credit to buy special product

➺

#tabemon

#context

#challenge

#solution

#initial_research

#research_process

#research_findings

• 01 •

information is overwhelming

• 02 •

current products are facing a very specific audience

• 03 •

building new habits is inherently hard

#assumptions

In the first step of ideation, I mapped out assumptions based on the knowledge I've learned so for from research and categorized them by the topics (image [01]). Then I valued the assumptions in a Risk Map (image [02])and marked the assumptions that are unknown and highly risky.

Here are the two assumptions that I found to be most unknown and worthy to develop further hypotheses and prototypes.

• 01 •

Making healthy eating less overwhelming will help people form better eating habits

• 02 •

Making healthy eating more fun will help people form better eating habits

[01] Categorized Assumptions

[02] Categorized Assumptions

#hypothesis

Based on the two assumptions above, I came up with the following hypotheses. These hypotheses would help me brainstorm the solution.

• 02 •

• 03 •

• 04 •

• 01 •

• 05 •

• 06 •

#proposals

• 01 •

How might we increase the quality of daily meals for young adults who live alone and are usually busy working?

• 02 •

How might we encourage young adults to make healthier decisions in eating?

#prototype_01

1.1.1

1.1.2

1.1 Feedback

1.2.1

1.2.2

1.2 Feedback

reflection

#prototype_02

User Journey Map 1.0

2.1

2.1 game system

2.2

2.2 game system

2.3

2.3 feedback

user journey map 2.0

2.4 game system

feedback 2.3

2.4

#initial_research

#final_design