TapTip app helps users with tip calculation and educate them about American tipping etiquette.
*This project is currently paused due to COVID-19-related retail business closures and travel limitation in the U.S. after launching the MVP.
I have been living in the U.S. for about 6 years. Most people might assume I know everything about American culture since I have been living here that much period. However, I still question a lot of things, and tipping etiquette is one of them. The country, South Korea I came from doesn’t have a tipping culture at all.
I sometimes struggled and felt awkward in a certain tipping situation since I had a lack of experience. So, I thought it would be very useful if there is a tip calculator educating travelers, international students, and foreign workers in the U.S. about American tipping etiquette. So, I gathered another designer and developer. We have been remotely collaborating TapTip app since.
People from different countries are not often sure tipping convention rates as well as whether to tip or not in a wide range tipping situation in the U.S. They need to learn a tipping etiquette and relevant cultural education for a seamless tipping experience.
The largest challenge going into this project for our team was scope in a timeline and technical limitation, so we had to be incredibly resourceful with where we focused our time. With that in mind, we agreed the priority was to focus on MVP features that users need for beta testing.
Tipping culture around the world
We wanted to see if there is enough market opportunity. We discovered that most countries in East Asia and the south pacific area don’t have much of a tipping culture. We decided to scope people from those countries. It was very interesting because other continents tend to share similar tipping customs.
Narrow the target audiences
We wanted to check if there would be enough numbers of users who are in the U.S who come from those east Asia and the south Pacific area. I researched which countries sending the most people to the U.S. We found out that most east Asian countries, China, Japan, South Korea, and Taiwan, are on the list. This validates that there are potential users for our new product. Since our target audiences come from most emerging countries, we decided to make the android app which is the most popular in those countries.
Concept Validation & User Research
We wanted to validate if this conceptual idea applies to the audiences from those countries, China, Japan, South Korea, and Taiwan. With that said, we conducted a Google form survey with key questions on 67 people from those countries to get the quantitative data. Then, we synthesize and analyze information to get some insights so we can generate ideas base on it.
We found out that many people, such as travelers, international students, and foreign workers want to understand American tipping etiquette and they would use the app if it educates them.
Tipping Scenarios Optimization
We figured out the 4 tipping areas, which are Restaurants, Transportation, Hotels, ETC base on the data we got from the 67 users. We optimized the top 4 services user picked under every 4 areas.
Base on the quantitative data from the survey we did with 67 people, we created 2 hypothetical key audiences who represent our target users. This gave some opportunities to see what they need and what challenges they are facing in the tipping situation in the U.S.
MVP & Feature Prioritization
Base the insights from the user research, we synthesized our findings and generated some ideas for key solutions
1. Suggestion of tipping convention rate depends on service category and quality of service
2. Education about American tipping etiquette and relevant information
3. View in other currency
4. Split the fare (restaurants)
5. Geo-location popup to get the sales tax depends on region
Once the new user opens the app, they walk over location permission and quick tutorials. The geo-location permit helps automatically embed the sales tax on the tip calculation depends on the user’s region. Then, a user goes through the quiz and then input the subtotal of the service, and then it brings the tipping amount conventions on the different types of output pages reflected from various tipping scenarios.
Also, the user can change the tip amount by moving a slider. If a user wants to learn more about the tipping etiquette of the service, they can go to the Tips for Tips page. Also, the user can share the tipping etiquette with other people by sending the text including tip info.
We applied 6:3:1 color rules base on the dark theme for more sufficient color contrast.
60% Dark Gray, #121617
30% Gray, #1E2223
10% Money Green, #00FFB4 (Accent)
This rule improves the legibility specifically for this type of heavy number-driven design (There is proven research). Sufficient color contrast between foreground and background helps the user to read the numbers easier. Also, carefully designed the outlined- iconography to get along Montserrat font for the overall design consistency.
We have 2 quizzes (main category + subcategory) to offer the right solution to achieve the user’s goal depends on the service they use. This prompts the landing screen so the user can start using the solution easily and quickly. We had an AB testing between the current 2 by 2 card quiz and accordion style. We end up selecting the style below since the users think it’s straight forward and easy to understand.
Quiz 1 (main category) & Quiz 2 (subcategory)
Quiz 2 (Transportation, Hotels, Etc.)
We have 3 different types of output pages depends on the scenarios. The type A includes the price summary, split the check, and the suggested tip amount slider. This only corresponds to the restaurant category.
Type B & Type C
Type B has the tip amount range module. This corresponds to Cafe, Takeout, Valet Parking, House Keeping, and Front Desk.
Type C has the suggested tip amount slider. This corresponds to Buffet, Taxi, Uber, Shuttle Bus, Limo Driver, Hair Dresser, Nail Shop, Home Delivery, and Tour Guide.
Simple user flow and the intuitive interface designs improve the seamless tip calculation in a wide range of tipping scenarios.
The user can adjust the tip amount by moving the slider and learn relevant tipping etiquette
Our next goal is monetization from the app. We are researching possibilities for opportunities. There is a number of things we try to add like viewing exchange rates with a preferred currency, tip etiquette for the different countries, and etc. We are keeping all the processes recorded as well so that we can use the strategy and method for future iterations and other projects.