Duration
6 weeks
Roles:
UX and Research lead, UI Designer, Project Manager
Tools:
Figma, and Vibe codings
Overview
Thai Bites is a mobile app helping Gen Z backpackers with food allergies and special dietary needs to communicate their ingredient customization needs to Thai street food vendors. The app is a final product concept proposed to Lonely Planet, a travel guide company who was looking for new products to help them break into Gen Z travelers market in Thailand.
Measurable impacts
Thai Bites was tested, and met with a lot of support showing a considerable demand for the product in the market, as well as indicating potential to increase the likelihood of
The beginning
The project started when Lonely Planet is seeking new ways to enter Gen Z travelers market in Thailand…
After we talked with lonely planet, who hoped to stay relevant in the new gen z market, we have identified the business, and product requirements from their side to help shape the overall direction of the project.
Business-aligned values:
“Non-sticky" meaning, does not make users addicted to their phone.
“Utility based” Helping people solve a problem, not just providing contents.
Discovery
We observed & talked to 33 Gen Z backpackers to find their most common issues in Khao San Road…
Our Team went through a series of semi structured interviews with Gen Z backpackers in Khao San road which is an area famous among the target group in Bangkok, Thailand, regarding how they eat their way around Bangkok when traveling, as well as their general eating habits and concerns.
Interview synthesis showed that most pain point mentioned were related to food which sums up to…
We turned food-related insights into criterias, and assess the current food products available
A deeper look into the players of the food space, most food apps are either online ordering, recommendation system and focus only on just translation. There is no apps that actually helps people order food when actually eating outside in real life, especially helping them to customize their Thai made-to-order street food order. This represents a business and product opportunity.
The research leads to a problem statement…
Travelers lack a tool to filter Thai made-to-order menus by dietary needs and communicate their orders in Thai to street food vendors
Define
Distilling our insights into personas, dividing our personas based on different eating habits
Picky Patricia aka our main persona!
"if I can clearly communicate my needs to the Thai vendors, I would not be so stressful every time I place an order!"
Context:
Patricia is a vegetarian and has peanuts allergies. She often struggles to communicate her dietary needs to Thai street food vendors.
Job to be done:
Patricia needs to properly assess the menu, search for the ingredients, pick the most suitable before trying to communicate it the vendors
No - Restriction Sam
"I only know Pad Thai and mango sticky rice! I kind of want to try new things, but I do not know what they are."
Context:
Sam is eager to try new food and has no dietary needs. But every time he goes into a Thai made to order restaurant, the menu is so confusing, he can't place an order.
Job to be done:
Sam needs a way to inquire more about dishes in english, get personalized recommendation so he can pick what to try
Conservative Charlie
"I am skeptical about eating Thai street food. I am afraid I can’t handle the spice! I would rather eat fast food."
Context:
Charlie is afraid to try new food, especially Thai street food because if his personal allergies, fear of flavor disappointment and hygien concerns.
Job to be done:
Charlie needs a way to overcome his fear of trying new food, and verifying his skepticism to make sure everything is safe to eat as well as match his flavor preferences.
How might we?
How might we help Picky Patricia to communicate their dietary needs to local Thai made-to-order food vendors effectively?
Setting up North Star Design Principles before designing by combining business-aligned values with users' truth
Combining the requirements from Lonely Planet which is what the business wants and inights from our research phase which is what users need, we formed our actionable principles that guide every product decision.
Design
We started to brainstorm sitemaps, and user flows, aiming to minimize screens numbers and steps as much as possible
My core contribution to this stage is to ensure the number of the pages in the sitemap, and the user flow fully cover the whole journey and included the needed information to reflect the actual insights we got from the research.
We brainstormed the MVPs, did the wireframes and hi-fi, before building up the hi-fi prototype through vibe coding
We already got the basic user flow, and key main sitemaps which already gives us ideas on the basic MVPs needed to run the app, however, we decided to use the north star principles and key pain points and behavior of the travelers to further hone the MVPs to ensure the best experiences for the users.
After wire framing the screens, we eventually narrow down to 5 key main features that answers to the pain points of the users which includes:
Initially, we build out the prototype in Figma, tested it with the users. Later, after figma make rolled out, we decided to come back and try building it up again using Figma make tool. Our limitation is the AI scanning feature which can not be developed through vibe coding. Therefore, we pivoted to making the users scan through a fake menu, and give them suggestions based on their allergy profile instead. Check out the real prototype here.
Delivery
Going back to Khaosan road to test our prototypes with Gen Z Travelers
The testing methods consisted of giving a task for the users to place an made-to-order street food before and after using the prototype, and afterwards they went through an after-task interview, and did a System Usability Scale survey, as well as Net Promoter Scale survey.
Most testers displayed a need for Thai Bites, as they can relate to the problem that Thai Bites is trying to solve.
Summarizing user insights, and next steps
Some of the most frequently mentioned issues in the interviews includes:
Key interview findings & Actionable Insights
The same dish can have different recipes and ingredients in different restaurants
There is no feature for the food sellers to communicate back to the users
Next Steps
We turned the insights and feedbacks into features to consider in the next iteration…
Reflection
Key learnings & Appreciations
Self reflection
Research is key, but how we present findings and designs matters too. Tailor presentations to the audience, and prioritize communication and cultural understanding, especially in a diverse team. Listening without judgment is essential, especially when working with people from different backgrounds.
The team
I deeply appreciate my talented teammates, Jackie from Taiwan, Samson from Nigeria, and Rick from Myanmar, for their invaluable contributions to this project, making it one of the projects we have ever done. Special thanks to Irene Preya, Co-founder of Irene and Anton, for her supervision and support during the whole process.
