Netflix, it seems, has the magic formula that has raised the company valuation to over £124 billion. It has passed Disney as the most valued media company on the planet. Some of its additional victories include:
- A 93 percent retention rate compared to Hulu’s 64 percent and Amazon Prime’s 75 percent
- Having 151 million subscribers
- Making wildly successful original TV shows and movies
- Identifying what their audience wants
So, what’s Netflix’s secret? The answer is big data and analysis. To be more precise, the secret is how Netflix collects this data and how it implements data analytics models to eke-out customer behaviour and buying patterns. The information Netflix harvests is transforming the entire entertainment industry.
1. Data Analytic-Savvy from the Beginning
The Netflix company was formed in 1997 as a subscription mail-order DVD business. It became so popular that a 90s icon, Blockbuster Video, went out of business. Netflix was already using technology to get ahead, namely “predictive analytics.” The company’s software engineers created algorithms to steal away those high-demand blockbuster movies to less well-known titles.
Netflix’s House of Cards became a roaring success because Netflix algorithms showed that it would be a success based on:
- The subject matter
- The appeal of the acting and directing talent
- Remnant fans of the original British version of the show
2. User-Interaction Data May Be an Internal Programmatic Marketing Infrastructure
Interactive stories began to show up on Netflix in 2017. Black Mirror: Bandersnatch allowed viewers to choose the plot lines by using their remote controls. Not only did most viewers enjoy this new gimmick, but Netflix was gathering user-interaction data concerning what plots work best with specific audiences, engagement information, and product-placement opportunities.
3. Big Data Analytics and Netflix
Big data analytics is a complex process that examines large and varied data sets, also called big data. Organisations can mine this information and use machine learning projects, predictive modelling, and other advanced analytics applications.
Netflix uses this type of data to analyse and improve the user experience. The information that Netflix wants about its users include:
- When you viewed the show
- Which device did you use to watch the show
- When you pause a program
- Portions of shows that get re-watched
- Does the viewer skip the credits
4. Personalised Video Ranker
Netflix orders the whole Netflix collection for each member profile in a customised manner. The same genre row for each member has a selection of videos chosen based on prior content.
Bill Franks, Chief Analytics Officer, International Institute for Analytics, said in 2018:
” I can say that no changes in Netflix’s products are not tested and validated, and we do not test just to test. If we do not believe it will improve, it will not be tested. We have 300 major tests of products and dozens of variations within.”
5. The Similarity Algorithm
Based on the fact that you watched one video, you are more likely to view another similar show. Netflix uses this to its advantage. Anyone who has recently binged a show knows the “what now?” feeling once the show is complete. Netflix knows that by immediately showing someone a similar show or movie, they are more likely to keep that person engaged in the moment. The similarity ranking feature is not personalised, but it does provide a good guess of what an individual viewer might like.
6. Netflix Digs Deep to Please their Viewers
This large company uses information such as:
- How much time their viewers spend watching Netflix
- What times of the day/week you watch Netflix
- Which content do you fast forward through
- Which material do you view repeatedly
- What titles do you watch on Netflix
All this data helps Netflix understand what their users want and how to retain its viewers.
7. Netflix and Artificial Intelligence
In 2018, Netflix was saving $1 billion a year through the use of AI. It improves its algorithms and reduces human intervention in programming decision-making. AI is used to:
- Auto-generate and personalise thumbnails
- Assist in location scouting for pre-production of movies
- Edit movies post-production
- Improve streaming quality
8. Netflix Doesn’t Have to Bother with Pilots
“Pilots” are the first episodes of an episodic series. Before now, pilots gauged the audience’s reaction and allowed the show’s producers to decide if they will get the most for their investment. Now, Netflix has changed all that. Netflix data analytics show the likelihood of the show’s success or demise before it is even created. The numbers speak for themselves – Netflix’s show success rating is 80 percent.
Want to Understand How Big Data can Revolutionise Your Business?
Whether we are talking data analytics or business intelligence, it’s the data that goes into it that is only as smart as the people who are using it. In the case of Netflix, as well as your business, you are in an age where data analytics and BI work together to make business decisions impactful.
The difference between business intelligence and data analytics is:
- Data analytics is geared more toward future trends and predictions
- Business intelligence helps individuals make decisions based on past data
One of the major mistakes that companies are making is attempting to adopt new technologies too quickly across their entire enterprise. The current population has generated 90 percent of the data in the world within the past two years. Businesses that are adopting BI need to know that they must understand their problems first. Then they must create a hypothesis on the ways BI can solve these issues. And, they must remember that it is all about the process.
Invite your board, IT department, and your C-suite to a meeting. Target one problem at a time. Create a plan of action. What’s important for your stakeholders? What data is necessary? Build key performance indicators that everyone can support. Turn data into action. Once you have organisational support, think about what software you need.
Netflix took action and look where they are now. Let us know how we can be of service.
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