Inspiration
Deciding on a movie to watch or resturant to eat at doesn't seem like that big of a problem at first glance. But a 2017 study that polled 2000 Americans concluded that the average American couple speends 132 hours a year deciding what to eat. Furthermore, the average Netflix user spends an average 18 minutes trying to decide what to watch.
This app aims to decrease those numbers substansially.
What it does
This app allows two users to swipe on movies or restaurants in order to help couples/partners decide.
How I built it
The app is built natively, using Swift. It uses Firebase as its backend, and uses the Google Places API to pull in location data, as well as Reelgood's internal api to pull in Netflix data.
Challenges I ran into
The biggest challenge was pulling in Netflix's data. They do not have a public api so I had to reverse engineer's Reelgood's internal one. Since there is no public documentation for it, using it was very tedious.
Accomplishments that I'm proud of
I'm really proud of the minimalistic UI. I am really a fan of simple, minimal designs.
What I learned
I learned a lot about how to use Firebase as a backend. I had some previous experience but never with an app of this extent.
What's next for Findr
Implementing machine learning in order to show movies/restaurants that a user is more likely to swipe right on more quickly.
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