Netflix is the undisputed king of streaming entertainment, with over a hundred million subscribers. Its low churn rate of 9% and massive use of big data analytics have helped it become the world’s leading entertainment provider. In addition, its recommendation system is responsible for influencing over 80% of the streamed content on its platform.
What makes Netflix different from other streaming platforms?
The company’s impressive growth has led its market cap to reach $83.27 billion as of May 2022.
- Netflix enjoys a high retention rate as compared to other streaming services
- It creates wildly popular original shows and movies
- The content is tailored to the audience’s expectations
The secret to Netflix’s success is its ability to collect and analyze massive amounts of data. This allows it to improve its customer experience and make informed decisions. Its use of data analytics has allowed it to transform the entertainment industry.
6 Ways Analytics Helps Netflix Grow
Powerful analytics tools can process up to terabytes of data to produce valuable information. Netflix’s success is due to its ability to make informed decisions and improve its customer experience.
Here are the top six ways how the media giant leverages data analytics.
1. Personalized movie recommendation
Netflix collects information about your viewing habits, including the date and time you watched a show or movie. This data can be used to recall you based on the device you used to manage the show or movie. It can also be used to rate what you watched. Netflix also keeps track of what movies and shows the users watch to analyze various aspects of their customers’ behavior, such as their viewing habits. This data is then used to create a personalized viewing experience for each customer by offering the most relevant content for each individual.
2. Auto-generated personalized thumbnails
Netflix generates thousands of video frames from an image or show as a starting point to generate various thumbnail images. It then ranks these images according to their likelihood of being clicked based on users’ characteristics who are similar to them. For example, one possible reason users are more likely to click on specific images is that they are more likely to like certain actors.
3. Trending now ranking
While Netflix uses personal data to customize its recommendations, it also uses this data to analyze and predict what shows will be popular in the future. This is done through its “Trending” section, which shows the most popular programs on Netflix.
This data helps Netflix make programming decisions and analyze the programs currently on its service. It also allows them to extrapolate which programs to renew and which ones to drop. Then, with the help of real-time data, it can quickly make informed decisions.
4. Marketing optimization
Netflix uses big data and analytics to create custom marketing programs for its shows. For instance, it used this data to promote “House of Cards.” So, if you watched a lot of shows that were focused on women, you would get a trailer that featured the main female characters, while if you watched a lot of content directed by David Finch, you would get a different one. Before it released “House of Cards,” Netflix knew precisely how many people would watch it and how they would receive it. This helped it avoid spending time and resources promoting the show.
5. Content similarity ranking
People watching one video makes them more likely to watch another show. This allows Netflix to identify which shows and movies to recommend based on their characteristics. It also helps users keep up with what’s happening at the moment. Although the feature is not personalized, it can provide a reasonable estimate of what a viewer might like.
6. Predictive and prescriptive analysis
Predictive analytics is a kind of data mining that uses gathered data to make predictions based on the actions of individuals. Netflix benefits from predictive analytics by using it to predict its users’ viewing habits. For example, it uses data collected from its users to determine what movies they’ll watch next. Data points such as time of day and the number of pauses during a movie selection can also be used to generate a predictive algorithm.
Prescriptive Analytics focuses on the present by considering the various factors that will affect the future. It helps Netflix focus on identifying the factors that will influence customers’ purchase decisions. This method is then used to make timely recommendations.
Key takeaways
The success of Netflix is attributed to the company’s ability to collect and analyze data. Data analytics is more than just numbers from the past. It lets companies like Netflix make informed decisions and maximize ROI by analyzing and reporting on various data sets.
It’s essential to ensure that the right and apt techniques are used to derive the most value from the data. With the support of Business Intelligence experts, enterprises can rightly and efficiently identify and forecast the needs of their customers.
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