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The Netflix moment for online courses

The Netflix moment for online courses

Over the last two decades, Netflix has been quietly transforming the entertainment industry with data. It uses complex analytics to answer high priority business questions. Compared to Netflix, online courses are still in the dark ages. Could they benefit from having access to similar real-time actionable insights?

Netflix has been a data company longer than it has been a content producer. The company has tirelessly collected and analysed information to build lucrative markets where none previously existed. These insights have allowed it to grow into the largest worldwide streaming network. Today, the service has 204 million subscribers. Total revenue came to $25 billion in 2020, up from $20 billion in 2019.

But before Netflix started producing original programming, the company spent a lot of time developing its recommendation software.

Every time you log on to binge-watch your favourite show, Netflix collects a lot of data on your engagement with the platform. Using these insights, the company’s analytics team has created a set of algorithms that can learn your taste and suggest the perfect title from the platform’s growing catalogue.

Netflix knows its customers well. If you are watching a series, the company can zoom out and see the show’s overall completion rate for their entire viewership. If, for example, 70% of the viewership complete all the seasons, where did the remaining 30% end up?

Where was the cutoff point for these users?

How big of a time gap was there between when viewers watched one episode and when they watched the next?

From asking these questions, Netflix can understand engagement at a deep level.

In the above example, if Netflix saw that 70% of viewers watched all seasons available of a cancelled show, that may provoke some interest in restarting it. From the data provided, managers can be confident that viewers will watch the new season.

Online instructors don’t have access to such privileges. They are pining for their Netflix moment.

Given access to real-time data about how learners interact with their courses, an instructor would decide which content to develop. Such analytics would give instructors a clear advantage over those who run on intuition or “what feels right”.

Here are some events that instructors would be interested in tracking:

  • When do most learners pause, rewind, or fast-forward content
  • Which parts of the content do learners replay often
  • What day of the week do most learners watch content on
  • What time of the day do most learners watch content at
  • Which devices do most learners use when watching content
  • What is the general browsing and scrolling behaviour of most learners

With such analytics, instructors can find answers to questions such as, “how do I help learners complete at least 80% of my course?”.

Instructors can start by looking at data within the actual online course. Where are the peaks and troughs in interest? From there, it is relatively straightforward to consider the characteristics of these individual scenes to figure out what learners like and don’t like.

Unfortunately, most platforms do not offer this depth of analytics.

For instructors, this can make scaling content delivery a burdensome task. There is zero real-time visibility into the actual behaviours of learners. It is a missed opportunity for online instructors who want to use this data to infer their learners’ preferences and create better courses.

We hope that this will change one day.

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References

Patel, N., 2013. How Netflix Uses Analytics To Select Movies, Create Content, & Make Multimillion Dollar Decisions. [online] Neil Patel. Available at: https://neilpatel.com/blog/how-netflix-uses-analytics/ [Accessed 12 February 2021].

Vanderbilt, T., 2013. The Science Behind the Netflix Algorithms That Decide What You’ll Watch Next. [online] Wired. Available at: https://www.wired.com/2013/08/qq-netflix-algorithm/ [Accessed 12 February 2021].

Damini, J., 2019. Black Mirror: Bandersnatch is Netflix’s Trojan horse to profit. [online] The Verge. Available at: https://www.theverge.com/2019/1/2/18165182/black-mirror-bandersnatch-netflix-interactive-strategy-marketing [Accessed 12 February 2021].

Popper, B., 2016. How Netflix completely revamped recommendations for its new global audience. [online] The Verge. Available at: https://www.theverge.com/2016/2/17/11030200/netflix-new-recommendation-system-global-regional [Accessed 12 February 2021].

Iqbal, M., 2021. Netflix Revenue and Usage Statistics. [online] Business of Apps. Available at: https://www.businessofapps.com/data/netflix-statistics/ [Accessed 12 February 2021].