The late 20th and the 21st century has witnessed a revolution due to the arrival of the internet. The media & entertainment industry has been on the frontlines in this revolution. The way in which people used to consume entertainment has completely changed. Consumer preferences have shifted from sourcing entertainment from cable TV to the newer OTT (Over the Top) services which provide more customized services according to people’s tastes and preferences. The media & entertainment industry is forecasting a growth of 4.4 growth rate percent compounded annually. So what is the reason for this massive growth? Hyper-personalization. The highly personalized, customized, and niche market that OTT platforms like Netflix, Amazon, etc have created for themselves has changed the shape and structure of the whole entertainment industry.
The secret sauce behind the success of these OTT platforms (specifically Netflix and Amazon Prime) is the personalization of the content being provided. They are able to push the right content to the right people at the right time which has been achieved through data analytics. OTT platforms rely a lot on data analytics techniques & platforms to keep track of the activities of their subscribers. The streaming cycles/habits of the subscribers are observed and tracked and the data collected from this is used to provide recommendations to the customers. This algorithm helps to personalize the type of content that the customers receive from the OTT Platforms.
Further, the data collected also incentivized production houses to produce content according to the preferences & choices of the users. Data analytics provides valuable insight regarding the type of content that is in demand by the viewers, and thus the company can accordingly decide upon its strategy for production. Netflix has reportedly stated that they were sure of the success of the show “House of Cards” during production because the creative direction of the show was inspired by data itself.
Data analytics allows companies to predict consumer behavior in long term too and outside of streaming. Many streaming platforms utilise predictive modelling to create personalized playlists/ suggestions automatically according to the listening/ streaming patterns of the consumers. Advertisements are the biggest sources of generating revenue for a streaming site may it be Netflix, Youtube, or Spotify. By understanding consumers’ needs, behavior, and activity pattern across various platforms, hyper-personalized advertisements can be presented to them which induces purchase of the product.
Art and Science have traditionally been 2 distinct domains for a long time but the usage of data analytics, Artificial Intelligence, and Machine Learning (ML) techniques have bridged this gap. The whole entertainment industry has now begun to understand its importance. Earlier, this was restricted to only OTT platforms but now traditional avenues of entertainment also are focusing on data analytics to improve the chances of success for their projects. Thus, this blend of art backed by science is here to stay but it remains to be seen the extent of innovation and scope that can be brought about in this hybrid field.
 |
Kshitij-Barua, PGP Batch Indian Institute of Management Ahmedabad |
