Location-based social media app that automatically detect events based on user activity.
App, API, Design
iOS, Android, Node, AWS
Daily active users / Total users
Around the time that Facebook reached one billion users, more niche location-based social media applications like Bubble Social and Yik Yak entered the market. Bubble Social aimed to fill the gaps that bigger social media giants could not. Bubble Social believed that being able to identify the people around you would keep users interested for longer, especially if those users were local celebrities or influencers. Bubble Social teamed up with Watchovr to build a groundbreaking scalable mobile app that would take on location-based media.
To build this app we knew that there would be many moving parts. These were the components of the app that we knew we needed:
We first launched the application on iOS. We figured that the best platform for our rollout was likely the platform that dominated US college campuses.
Following two versions of the iOS app, we found a developer who could essentially replicate what we had built for iOS on Android.
During this process, we had been developing an API that powered the iOS and Android apps. One of the particularly interesting parts of the API was user popularity ranking. Not dissimilar to high school popularity, Bubble had figured out a way to rank users based on their connections and the quality of those connections. Then, at events, a “bubble” would pop up on the public map that would show the sum of all of the users at that event: effectively revealing where the party was at.
Bubble was able to automatically detect events starting based on user activity as large numbers of users clustered in an area of unusual activity. Users were able to rank themselves against each other and compete to be the most popular at UCF, a groundbreaking feature that we felt was the app's calling card. Indeed, it drew organic engagement to the app in droves.
Bubble was a hit at UCF.
At the peak of the app’s life. there were 4k total users and 1k daily active users, comprising about 7% and 2% of the student body respectively. Our users were utilizing the app to find new friends, locate live events, and better understand their popularity on the UCF campus.
Unfortunately, after an investor pulled out on $250k of seed capital, our team's morale was decimated and the app slowly burned out as the team shrunk due to the letdown from the investor.
While we ultimately decommissioned the app, we learned so much about building, scaling, and marketing an app.
The final ecosystem was about 300,000 lines of code. But with all of the versions combined—the total number of lines was closer to 1 million.
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