Bustle

Buztle is a event finding app that uses ML to help its users find activites that they would be interested in, and then" connects them with their friends who are interested in the same activities.

Project:

The goal of this project was to create a user freindly prototype for an event finidng mobile application that simplified the Users Experience with the app.

Objective:

The Process

1) The first step of this project was to review other applications such as Eventbrite and Meetup to see how users interacted witht them. Based of our observations, we found that there were too many options that were unrelivant to the users so the users lost interest quickly.

2) We had to create a persona and user story so that we could interact with the application. To find this out we used surveys to collect data on users that would use the product, and usablity testings with a simple wire-frame. From this we found:

Persona(example Change this):
User Story:

3) After brainstorming some ideas with alot of sticky notes, we found that the most user-friendly idea would be to use a tinder like card idea, that has an algorithem that takes in users data when they swipe left or right, and learns what their interst are. This way they wouldnt have to look through all the options. Also based off our Persona and demographic data we found, we beleived that most of the users in the age group would be tech savy enough to understand how to use the product.

4) The next step was to create a prototype for the Minimum Viable Product. For this I coded an iOS application via SWIFT that had views assorted in a stack, that allowed the users to swipe left, or right. It also allowed users to save events, and to create their own events. We decided to use Firebase as a back-end so that we could get a rapid working prototype up and running.

5) The last step I contributed to the product was to create usablity test to ensure that the product solved the problem for the users of too many unrelevant options. we found that it did solve the issue, button beacuase there wasnt a complete back-end our results were limited.