Case Study – StreamTV Streaming Guide, Recommendation Engine, and Social App

Project: Build an app with best-in-class personalization for streaming content search, discovery, and social sharing.

Background

As most people will tell you, the overwhelming amount of content available via streaming services makes it difficult to find something to watch.  It’s the modern equivalent of “300 channels and nothing to watch” on cable TV.  There was once a statistic that people spent approximately 45 minutes search for content on NetFlix and then left without watching anything.

We set out to create an app where users can search, discover, and track relevant TV shows and movies across all their streaming services in addition to a social space to share, discuss, and recommend content to their community via internal chat, friends, and friend groups.

Project

This was a relatively straightforward app build using Agile methodologies.  As Fractional CTO for StreamTV, it was my job to manage the project from top to bottom.  I drafted the technical requirements document, worked with the designer on the initial set of designs, hired the development team, selected the tech stack (Figma, AWS – S3, E3, DynamoDB, Firebase, React, React Native, JavaScript), created the project plan, and managed the project through an everchanging set of requirements and deadlines to our soft launch.

New requirements as we were in development included:

1. Livestreaming – Our owner, a film production company, wanted to be able to livestream from film festivals, premiers, etc.
2. Game show – We were developing a game show similar to HQ Trivia to drive the loyalty program.
3. Daily spin – Also for the loyalty program, a daily spin to instantly win promotional prizes or points.
4. Watch parties – A feature to synchronize viewing across multiple accounts and devices.  The challenge here was that since we were not able to integrate directly with the streaming services, we had no idea the state of playback was within their apps.  We came up with some innovative ideas on how to synchronize and centrally play and pause the content.
5. User ad management – Users could earn loyalty points by selecting if and how many ads they wanted to watch prior to playing the content.

We did hit the soft launch date with a robust enough set of features, mostly content search, discovery, and tracking.