Which insights could we gather?
What prevents our users from spending less time on choosing and more time on enjoying? We decided to explore this further by doing deep interviews.
This is what we found out:
1.Firstly, one of the major interference is not finding relevant content fast enough. Meaning that we are spending a lot of time on scrolling through irrelevant content that we won’t engage with.
2. Secondly, and most interesting discovery was that we don’t consume the same content every time we log in. It differs between parameters such as, time, day of week, location, device, etc.
Which lead us to our main insight:
How can Netflix, recommend something that the user wants to see, before they even know they want to see it?
Netflix need to figure out which content is the most relevant content for the specific user. Every time he or she logs in.
We started by looking at existing data points that we could use such as, geolocation, time, weather-data, device, voice recognition etc. Netflix could recommend the best and most relevant recommendation based on these data points, giving the user a better experience.