Digitization in the media and entertainment industry has empowered businesses to have unprecedented access to data on their customers. By using big data analytics, entertainment companies have been able to gain detailed insights regarding not only their customers but also their systems and processes.
The most pre-eminent players in the media and entertainment industry, such as Netflix, Amazon, Hulu, and Disney, have already been leveraging big data as part of their operations to enhance the customer experience. Hulu, for instance, has been known for using analytics for purposes like content acquisition and recommendation.
Similarly, many other entertainment companies have been using big data and AI analytics to enhance their offerings and streamline their business processes. As a result, the media and entertainment industry as a whole is gaining massive advantages.
How big data analytics is making media companies competitive
Attracting and keeping customers engaged are the biggest challenges faced by media and entertainment companies across the world. By using big data analytics, businesses have been able to overcome their challenges and achieve higher business outcomes such as:
1. Increased customer retention
Media companies like Viacom18 have been using big data analytics to ensure viewer retention during break slots between program segments by identifying the right times to place commercial breaks. As a result, they have been able to retain viewership even during commercial breaks to drive significant revenue for themselves as well as advertisers.
Similarly, other media companies are using big data analytics to drive similar initiatives aimed at improving customer engagement. A well-known example of this is YouTube, which uses big data and machine learning to predict the kind of video recommendations that would keep users on the site for extended periods.
2. Effective media investment decisions
Media streaming platforms need to ensure that the content (movies, TV series, music) they are investing in will be successful among their audiences and deliver an adequate ROI. To assess the potential success of different media assets and projects, media companies are using big data analytics. The most popular example of this is Netflix’s investment in an American version of the British Show, House of Cards using insights gained from big data analytics.
By ascertaining the potential success of the show, Netflix made a considerable investment that paid off huge dividends. Similarly, leading media company Warner Brothers. has invested in predictive analytics technology to predict the success of movies. The company is using this technology to guide its decisions when investing in new movie ideas.
3. Precise ad targeting
Advertising revenue is a major source of income for media streaming and entertainment companies. To ensure that they show the most relevant ads to different users based on their demographic information, media streaming companies like NBC use big data analytics for ad targeting and audience segmentation.
As a result, these companies are delivering greater ROI to advertisers by helping them reach their ideal target audience. By combining big data analytics with machine learning, online streaming platforms like YouTube improve the relevance of the ads displayed to their users.
4. Detailed performance analysis
Network media companies are using analytics information in the form of language-based reports to understand the performance of their different channels and media assets. With the help of this analytics information provided by research bodies like the Broadcast Audience Research Council of India (BARC), businesses get real-time insights into the performance of their shows with respect to their competitors and make improved strategic decisions.
To refine the insights delivered through analytics, these media companies are using reporting automation powered by natural language generation. As a result, they are able to convert insights into action quickly, achieving better channel performance.
On the whole, the incorporation of big data analytics by media and entertainment companies is enabling them to provide high-quality entertainment to clients while ensuring better business outcomes for themselves.
Romil Shah is an AI enthusiast with considerable experience across varied technology domains, primarily Natural Language Generation (NLG), and Blockchain technology. He is passionate about technological innovation and more importantly its real-world applications. His work within the field has brought about constructive conversations and explorations around AI and its extended use in businesses.