Data analytics is a game-changer. This sentence may seem hyperbolic, but it is true.
You can’t comprehend the magnitude at which certain companies were able to leverage their business just by manipulating and analyzing data.
Netflix is perhaps the best example of it.
Netflix’s revenue increased modestly to $7.87 billion in the first quarter of 2022. It is presently regarded as the world’s most valuable corporate/media company, surpassing even Disney.
Their insane customer retention!
And how do they achieve it?
By leveraging Data Analytics, and by tracking everything that a user does, Netflix has been able to modify its content, and its placement, in a way that maximizes user retention.
Customer retention and data analysis strategies
Customer retention is the process of engaging customers and persuading them to use the service or purchase the goods.
This may appear to be a simple approach at first glance, yet many consider it to be the most effective tactic utilized by any media firm. But Netflix made such good use of it that its subscriber retention rate is exceptionally high and continues to rise over time.
Because of its more successful TV episodes and movies that have grabbed attention and a large number of views, Netflix has jumped well ahead of its competition. This has aided in the growth of subscribers. Netflix has been more successful in recognizing customers’ or audiences’ genuine interests.
How does Netflix do that?
As you see, the process of customer retention starts with customer interaction. Netflix has digitized its 151 million subscribers’ interactions. It collects data from each of its users and uses data analytics to better understand subscriber behavior and viewing trends. It then uses that information to make personalized recommendations for movies and TV episodes based on the subscriber’s choices and likes.
The collected data is the key to strategy making. It guides the team to understand every vital piece of information and the timing and type of content, along with the information via movies or web shows, they provide to the customers, and what they like.
With the help of data analysis, they are even able to produce likable content that grabs customers’ attention easily.
The impact of customer data on content
Again, customer retention and getting more customers, or viewers in the case of Netflix, is the way to gain more profits and scale up the business.
See, content is of no use if viewers do not like it. There is no use in giving them a dose of action when they want to see romance.
Likable content creation is one of the most fundamental reasons why Netflix is so far ahead of its competition. “La Casa de Papel,” “Orange Is the New Black,” “Sacred Games,” and “BirdBox” are examples of the high-quality shows and films it produces.
These performances have gotten a resounding reaction from audiences all over the world, resulting in a constant increase in subscription rates. One of the main reasons they succeed in creating better content is that they use data and analytics to understand what their audience wants to see.
Data and analytics are also used to improve core operations and establish new business models from the ground up. Netflix is the most notable example. Netflix has made effective use of consumer data to improve its recommendation engine and provide a better user experience. Not only that, but with a market capitalization of more than $160 billion, Netflix has eclipsed Disney as the world’s most valuable media corporation.
How to use data and analyze it for profit.
Data collection is critical for any business or organization. Consider Netflix, which has 221 million users. It would be a monumental undertaking to analyze the characteristics of so much data from so many clients. Netflix takes the data it collects, turns it into insights, results, or visualizations, and then offers TV episodes and movies based on the tastes and interests of its users.
Can you guess how many Netflix subscribers there are? Netflix members totaled 221.64 million up to the end of FQ1 of 2022. Netflix has reached a new milestone, though; it has surpassed the 200 million subscriber mark in 2020.
How did it achieve such brilliant results? Here’s how.
Netflix keeps track of how a user interacts with and reacts to a TV show or a movie. If we go deeper, we find that it collects the following information: –
- The time and day at which the user watched a piece of content.
- The device on which the content was viewed.
- Is the viewer able to resume watching the show after pausing it?
- Does the consumer watch a complete season of a TV show in one sitting?
- If they do, how long will it take them to binge-watch it?
Netflix’s recommendation algorithm accounts for more than 80% of the content streamed by its members, resulting in a $1 BILLION profit from client retention.
On a side note, you can learn how to do all of this too. Data Analytics is simple enough to understand, if you have the right mentors. Check out this mentorship programme on Data Analytics by a Microsoft certified data analyst.
Furthermore, Netflix has ratings that viewers provide for the content they watch, the number of searches they conduct, and the types of searches they conduct. The data gathered is sufficient to create a complete profile of a person, which is exactly what Netflix does.
It uses data analytics to create a comprehensive recommendation algorithm that recommends the best content to the user based on their likes and needs.
Of course, we can’t ignore the fact that Netflix suffers from a major problem that ails many similar OTT platforms.
The FREE-LOADER problem!
Many people, (including some who might be reading this) use shared Netflix accounts.
According to Netflix, around 40% of its subscriber base is the unpaid segment.
However, now that Netflix has accumulated a wide enough user base, it seeks to constrain its subscription service and add several layers of protection to prevent free-loaders.
The OTT platform also plans to launch a more affordable version of the platform which would be ad-supported.
What’s surprising is that Netflix is, but one of the many businesses in the world that significantly leveraged themselves using Data Analytics.
Google, Meta, Apple, Spotify, and so many other companies are still making use of your data to drive their business decision.
This truly exemplifies the fact that Data Analytics encompasses the huge potential for businesses all over the world.
Of course, to do so, you need to become good at it, and not commit these 10 mistakes that Data Analysts usually do.
Thanks for Reading!