We first did secondary research and a few user interviews to determine the project focus.
Through user interviews we learned that people often have recurrent transactions such as monthly rent, phone bills etc. The repeated transactions can be payments or requests. So we concluded the typical payment/request workflow as shown below, and decided to use AI to make the process more efficient.
There're also other findings inspired us for more specific design ideas:
Through the interviews, we discovered that people often have transactions like rents, phone bills, utilities etc. on a regular basis. This inspired us to allow user set reminders on their own.
We don't have the actual log data to identify the most common purpose for transactions on Venmo. But based on our interviews, the No.1 reason for Venmo transactions is paying friends for food. This align with a study we found online, which shows more than half of the top 15 emojis in Venmo are food or drinks. This inspired us to specifically design for payments at restaurants.
Interestingly, we discovered that people often use the same comment message for transactions, especially emojis. And they find typing the same amount and description once and once again annoying. This inspired us to design the suggestions for amound and comments.
We asked users about using AI to make suggestions, and discovered that people more tolenrance for error if the system is suggesting requests, ranther than payments. This inspired us to design different forms showing different levels of intrusiveness while making suggestions.
This project is about practicing a method to apply AI on simplifying workflows. We successfully identified the workflow with potentials and iterated to find the right way for adaptation.
Due to the short time of this project and the educational purpose, we couldn't do thorough research to validate the user value of our idea. We also couldn't do enough user testing on the adapted workflow. So if given more time, I'd focus on these two part more.