Have you ever wondered what led Netflix to invest around $50 million for each season of the ‘House of Cards?’ Or how Chennai Express broke the Box Office collection record in 2013? The answer to all these is advanced data analytics.
The media industry is increasingly leveraging analytics to predict audience sentiment, woo the new audience, and retain the existing audience. Be it OTT media service providers like Netflix or Amazon prime, or the film and music industry; marketers are using advanced analytics and machine learning to generate a pull for their content.
As technology, social media, and analytics become available to the media industry to leverage the power on the Internet; we look at six ways in which media and entertainment industry is using the power of analytics:
Generating targeted content
Data-driven decisions are the future of media and entertainment industry. With the huge amount of data available for analysis to draw inferences, predict customer preference, and decide on what will work – the industry is no more dependent on intuition to make a series or a film work. For example, Netflix claimed that while they invested on the series House of Cards, they already knew it would be a hit – thanks to the viewership data that helped them analysis viewers’ habits over many millions of show views.
Optimizing scheduling of content
Big data gives the power to media houses to collect data from diverse sources and understand customer preference – be it the type of content, the time, or the device used. Using advanced analytics, they can then optimize the scheduling of content. For example, on a local holiday, broadcasters can stream popular movies, or more home-oriented content during afternoons.
Optimized scheduling is not only limited to general analysis, but a more detailed prediction based on browsing history, weather conditions, or time of the day.
Considering the massive amount of data that the media and entertainment companies generate daily, analyzing it to gain insights into the popular genres or preferred time is not an easy task. However, if appropriately interpreted with a good recommendation engine, the data can increase user engagement manifold by providing an effective recommendation.
Media and entertainment companies are increasingly using machine learning and advanced analytics tools to analyze viewership data in real-time and provide relevant recommendations to the audience.
Thanks to big data, analysts have a better understanding of the consumption behavior across multiple platforms. With advanced segmentation and complete customer views, companies can micro segment customer to personalize ads. Targeted ads will ensure that the right people view the right ads, increasing the click-through rate, thereby increasing conversion rates and ROI.
Retaining and wooing viewers
Data gives insight into why viewers subscribe or unsubscribe to a channel. Media and entertainment companies can use the viewership data to device the best product and promotional strategies to attract new viewership and prevent churn of existing viewers.
Finding newer sources of revenue
Considering the ever-changing equation of customer preference and new technology, it is essential for media and entertainment companies to explore new sources of income continually. Advanced analytics can help companies do that – identify additional sources of revenue apart from advertising or partnerships. For example, companies can create a proprietary platform using their exclusive data and earn revenue from advanced advertising.
While the media and broadcast industry has always primarily relied on data in the form of ratings, viewership, TRPs, etc. to measure success, advanced analytics has taken it a step further. By analyzing real-time data from multiple sources, predictive analytics is now not only helping them measure success but also strategize future.