We performed an in-depth analysis of users and genres to highlight the trends in behaviour at different times of day. Then we separated the users into groups based on our findings, with takeaway statistics that would allow the company to monitor trends, tailor their streaming catalogue and choose how much to spend to match advertising to the different sets. We subsequently created a recommendation engine that combined multiple strategies to ensure each user was shown a portfolio of content that matched their likely interests, increasing their engagement with the platform and growing loyalty.