Everyone knows Netflix is using data you provide to improve upon your overall experience. Things like recommended movies and categories that are unique to your profile are their attempt to prove to you that they have a pretty structured system that understands your tastes given enough information.
Here are some fun ways that Netflix is using this data that we find rather impressive:
It is impressive how accurate their recommendations have become, on top of which, how agile they are. When watching a show of a specific genre, it’s great to see what will be recommended next and under what category it falls.
New Netflix Original Content:
Think the success of House of Cards was random? Lo and behold, the masters of big data went far above and beyond normal market research when deciding to produce this Emmy award nominated series. As The New York Times reported, Netflix made a lot of the casting decisions based heavily around current popularity in their existing content. They dove deep into the question of “what sort of content does our audience want?”
Making Their Data Easier to Understand Internally
A good marketer will always understand how to interpret trends, and in some capacity, the numbers behind those trends. However, not all marketers have the understanding of the underlying tech behind this analysis. Netflix has put a keen focus on making tools for this research as easy to understand as possible.
Virtually everything else:
Did you know that every time you rewind, that is tracked? How about where you log in from? And perhaps what time of day you spend most of your time streaming? Well, it turns out all this changes how Netflix makes decisions to present it’s content to you:
Some fun statistics on what is being tracked (source: Gigaom):
- More than 25 million users
- About 30 million plays per day (and it tracks every time you rewind, fast forward and pause a movie)
- More than 2 billion hours of streaming video watched during the last three months of 2011 alone
- About 4 million ratings per day
- About 3 million searches per day
- Geo-location data
- Device information
- Time of day and week (it now can verify that users watch more TV shows during the week and more movies during the weekend)
- Metadata from third parties such as Nielsen
- Social media data from Facebook and Twitter