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How Big Data is Revolutionizing the Entertainment Industry

The leading on-demand music Service, Spotify, big data analytics to collect and analyze the data from its millions of users to provide better music recommendations to individual users. In another example, Netflix used big data analysis and released the season of
“House of Cards” all at once based on the data of 33 million users. The team of Lady browses through the listening preferences and sequences of users and optimizes the playlists to create maximum impact at the live events. Big data analysis around the social media buzz is being used widely in Hollywood to predict the box office success and effective strategies are formed based on the social listening to position the movie more favorably.

Undoubtedly, big data is playing a big role in the music and entertainment industry.  Let us see how –

Personalized Recommendations

Based on the usage patterns across channels and platforms and an in-depth analysis of viewership on social media platforms, the entertainment companies are using big data analysis to personalize the delivery of media to the consumers. The usage tracking allows them to identify the top products or artists, revenue bifurcation by region, album popularity etc. All this information is used to forecast the income and understand the customers at a far detail level to deliver a more personalized experience to every consumer. The “collaborative filtering approach” used by the big data recommendation engines is able to predict the consumer’s preferences by leveraging the data available from other users with similar characteristics. 

Better Streaming

Music companies are gathering data from various social media channels about the artists like title, duration, genre, match it to individual preferences, and using a recommendation engine, are able to provide a personalized list to the listeners which matches their taste. In real-time as well, as the listeners give more feedback, the recommendations are made based on the changing tastes using real-time data analysis.

Multi-Channel Ad Campaign

Today, consumers are consuming content on multiple devices at the same time. Studies show that, on an average, each person owns two to three different devices. Big Data analysis allows companies to optimize their ad campaigns to show relevant ads across multiple devices and reinforce the message of the commercials. Big data analysis allows companies to understand the use of the second device by the users, the content consumption, and usage patterns across devices.

Create Differentiated Experiences

Creating differentiated experiences help organizations in connecting better with their audiences. By capturing and analyzing consumer feedback across different sources such as social media, blogs, websites, etc., organizations can deliver the right content, at the right time to the right person. Such unique experiences can help them in getting a better mindshare of the consumer.

Predicting Movie Success

Gone are the days when the movie industry used to rely on certain trends or traditional wisdom and intuition to predict the success or failure of movies. Instead of relying on these not-so-accurate and less reliable methods, today, the industry is leveraging data mining and analysis, to formulate a new and more reliable method to accurately predict the success and failure of movies. This is achieved through careful analysis of various factors such as – potential customers and their interests in the movie, their influence on others, study of other movies released during the similar times in past, engagement to trailer launches, overall social media buzz, public forum comments, past performance of the movies by the same cast, Production Company or Director, type of story etc.

In the rapidly changing and dynamic media and entertainment industry, companies are heavily relying on big data analysis to understand the evolving needs of the consumers and then create delightful experiences for them and turn them to loyal and profitable consumers.

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