How Netflix is leveraging their data

8

October

2017

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Netflix is well known of topics such as ‘long tail’ and the disruption of the entertainment industry by switching to online streaming. Though, these advantages were both temporary competitive advantages. For instance, firms like Amazon and HBO are using the long tail and online streaming as well. This is because both are very easy to copy and implement in a company’s value chain. Even though the competition is fierce and the competitive advantages are gone, Netflix remains to keep themselves in the lead. This year they reached the milestone of 100 million subscribers (Gensler, 2017). But how did they managed to keep competition behind? The answer to this question is: data in combination with a two-sided market!

Netflix already has a new way of being competitive. Netflix has been collecting data since they were sending DVDs by mail, because of the amount of data they collected during all these years they know their customers extremely well. Netflix doesn’t just use the data to make your own customer experience better but, also use it for collaborative filtering. This means Netflix uses data gathered from groups with the same kind of taste to help other customers to find the content that is most likely to delight them. For this reason, almost 75 to 80 percent of everything you watch on Netflix comes from their personally tailored recommendation system (Grandoni, 2013).

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Data further helps Netflix to make better content investments. Netflix evaluates new content on a lot of factors, including things like genre, title, actors. This gives Netflix an indication of the value of a show. This even works better for sequel series, about which Netflix already has a lot of data. With this data Netflix can justify the spending on a show to a high degree. This also helps them by making the decision if they want a show exclusively for themselves (a Netflix original), for a fixed fee or variable costs per view (Gallaugher, 2016).

Besides the advantages of data, does Netflix also make use of a platform. With on the one side the producers of content and on the other side the consumers of content. The platform is closed, only Netflix decides what kind of content is published on it. In case Netflix is willing to open its platform to suppliers of content it will directly compete with for example YouTube. Because Netflix wants high-quality content is it not likely it is willing to open its platform. As a consequence, this gives suppliers of high-quality content a great bargaining position with respect to Netflix (there are just a handful of suppliers). For this reason, Netflix started to produce its own content (Gallaugher, 2016).  Till now, the ecosystem of Netflix worked well, but in the long run the lack of providers of high-quality content will be a difficulty for the platform. The time shall learn if the gathered data will be a competitive advantage in the future or whether it will be a temporary competitive advantage just like the long tail and the switch to online streaming.

 

 

Gallaugher, J. (2016). Information systems: A Managers’ guide to Harnessing Technology. V5.

Gensler, L. (2017). Wall Street is raving about Netflix and Its stunning subscriber growth. Retrieved from: https://www.forbes.com/sites/laurengensler/2017/07/18/wall-street-applauds-netflix-content-subscriber-growth/#603d2f684455

Grandoni, D. (2013). Netflix’s new ‘my list’ feature knows you better than you know yourself (because algorithms). Retrieved from: http://www.huffingtonpost.com/2013/08/21/netflix-my-list_n_3790472.html

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Artificial Intelligence, the other side of the medal

21

September

2017

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Several companies like Google, Facebook and Spotify are using AI. I personally think we still have to understand why these companies use this kind of technology and who benefits from it. After reading several articles about how AI is helping to cure cancer, combat terrorism and solve many other problems. I want to show the other side of the medal of the usage of AI.

 

Facebook, for example, is currently using AI for several purposes. After successes such as facial recognition and DeepText (a text understanding engine), Facebook is currently developing a system which can generate recommended responses for Facebook messenger (Kaput, 2017). These great AI functions can save time for consumers and optimize their experiences. But on the other hand, Facebook uses AI to control the content you get to see, and they use this ability to keep your attention to their website (Higginbotham, 2016).

 

One of the things we have to keep in mind is that Facebook is a commercial organisation which has maximizing profits as the main goal. Facebook is making money by selling advertising space on their platform. The advertisers want people to see their advertisements and to click on them. Thus, Facebook wants people to spend as much time as possible on their website. To achieve this Facebook uses AI which generates exactly the content you want to see. As a result of this, you spent plenty of time at their website and they earn money by mostly wasting your time. Facebook is competing with others for people’s attention, YouTube for example.

 

The competition for people’s attention resulted in a new economic phenomenon; ‘the attention economy’. The attention economy treats human attention as a scarce commodity. This means many companies will compete for your attention. With this attention, companies try to persuade you to buy or do things they gain from.  People like Tristan Harris –an entrepreneur who sold his company to Google- think that tech companies can almost design your life in the nearby future.

 

This made me (and people like Tristan Harris) think about the true purpose of technology. Because when I think about the purpose of technology I think we need technology to help us to do the things we want to do, but just in a better/easier way. In other words, technology needs to help us to achieve things and not slow us down or steer us in a direction we don’t want to go. So, for what kind of purposes would you use technology in your professional career?

 

Kaput, M. (2017, February 7). How Facebook uses artificial intelligence and what it means for marketers. Retrieved September 20, 2017 from: https://www.marketingaiinstitute.com/blog/how-facebook-uses-artificial-intelligence-and-what-it-means-for-marketers

 

Higginbotham, S. (2016, April 13). Inside Facebook’s biggest artificial intelligence project ever. Retrieved September 20, 2017 from: http://fortune.com/facebook-machine-learning/

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