5 Ways Big Data Analytics is Influencing Media and Entertainment Business

Since the past few years, there has been an increasing focus on data-driven digitization. Its effects can be realized in almost every industry, including the media and entertainment industry. Today, the role players in the media and entertainment business are facing a tough challenge to exploit new business models that allow them to create and distribute their content effectively. This is because millennial consumers (the major consumers of media) demand flexibility and high availability of content. They are not bound to their television sets anymore, instead, they are trying to access content anytime, and on any screen of their choice. As a result, the media and entertainment businesses are relying on data analytics more. Why? Because it helps them in many ways. This post explores how big data analytics is shaping the media and entertainment industry.

1. Understanding What Audiences Want: Earlier media content was delivered in limited formats, and in preset time slots. Today, the viewers have a choice to select from formats such as on-demand, live streaming, pay per view, subscription-based, etc. As most of the content is delivered through various digital channels, the media houses have a choice to collect, analyze, and interpret the user data efficiently and effectively.

The data sources such as ratings, searches, viewing history, reviews, device data and location, log files, as well as social media sentiment, enables them to understand the customer behavior, and their preferences. For instance, Netflix interpreted the humongous amount of viewership information to conclude that political fiction dramas were favored by its consumers. Thus, it secured a right to broadcast the most favored political drama House of Cards by outbidding its competitors like HBO. Similarly, over the years, YouTube has interpreted several vital statistics to deliver users what they like the most. These interpretations allowed them to learn what videos viewers like the most, what devices they used for streaming their favored videos, the duration for which the particular video was viewed, etc.

2.  Optimizing the Content Scheduling Across Various Media Platforms: Until a few years ago, there was a huge gap between the distributors and consumers. However, the evolution of various digital media platforms has changed it all. Today, it has become easier for a distributor to approach his potential consumer directly without any intermediary.

The social media networks have helped distributors to create personal connections with the consumers. Connecting with consumers through scheduling of media streams is helping media companies to maximize their profits. For instance, in 2013, prior to the release of Chennai Express, the movie-related tweets generated more than 1 billion expressions, whereas tweets with relevant hashtags generated more than 750 thousand expressions during the 3-month campaign period. As a cumulative result of various big data analytics sources, and marketing, the film created several new records, which remains unchallenged till date. It was perhaps the quickest film enter into ₹1 billion club.

3. Increasing Customer Retention: Increasing customer churn is a big concern for media companies. Most consumers today resort to social media reviews before viewing a particular web series, movies, reality shows, or music programs. With the fast evolution of the Big Data, it has become easy for the media companies to design tailored strategies to attract and retain their consumers. For instance, by leveraging different sources of data sets, these companies can easily understand consumer’s likes and dislikes. They can use this information to tailor attractive subscription and pricing packages to retain them.

4. Exploiting New Models of Monetization: Big Data analysis is allowing businesses to identify and exploit new revenue sources. How? By helping media companies to exploit the interests of their customers. For instance, The Weather Channel (TWC) has exploited big data analysis to its best. Over the years, it has utilized big data analysis to understand customer’s buying behavior in various weather conditions. This understanding has helped it create a marketplace where sellers can easily promote their products. Now, half of the TWC earning from advertising comes from a big data analysis.

5. Allows Better Targeted Advertising: It is a well-known fact that media and entertainment companies thrive on advertising. All these years, the advertising was purely conducted on the basis of assumptions. However, today businesses are harnessing big data to understand the customer preferences. It gives an in-depth insight into what customers would like to watch at a particular time. This visibility helps them position their advertisements in specific time slots for higher conversion.

Although social media platforms and YouTube provides a better data for targeted advertising, still TV attracts attention. In May 2017, Fox confirmed that digital viewers and TV viewers tuning its content will be able to see the same advertisements. These advertisements will be selected on the basis of Video Quality Score by MOAT – a platform developed by Oracle. In addition to Fox, NBC and several other leading companies have already started using MOAT.

Due to all the aforementioned benefits, big data analytics is slowly becoming a choice for various media companies and entertainment businesses worldwide. It creates an ecosystem where a customer takes a center stage and becomes a king. After all, the success in the entertainment industry entirely depends on user-experiences that it delivers.