A Paradigm Shift Awaits The Media And Entertainment Industry

A Paradigm Shift Awaits The Media And Entertainment Industry

The media and entertainment industry is awaiting a paradigm shift in the coming years. For many years, this industry was about sending information/entertainment to readers / viewers / users at a moment they thought appropriate (think the TV channels). The broadcasting planning was made based on historical analyses and what the Chief Editor deemed best for the audience. With big data this is all about to change. Not only will advertising fundamentally change within this industry, also what shows, series or movies are developed when and for whom as well as the evaluation of those activities are changing rapidly.

In order to achieve this, media and entertainment organizations should start building detailed 360-degrees profiles of their audience. They can use a vast amount of different data sets when building these profiles. Behavioural analytics can be used to discover patterns in (un)structured data across consumer touch points, giving organizations better insights in the different types of customers they have. Consumer patterns derived from data such as demographic, geographic, psychographic, and economic attributes will help organizations better understand and approach their customers. Sales and marketing data such as campaign information, Point of Sales data and conversion data will provide organizations with accurate customer data information. All can be used to increase customer retention and acquisitions, grow upselling and cross-selling opportunities, increase online conversion and improve the entertainment experience for the end user. When users also connect their social profile, the media and entertainment organization can obtain a true 360-degrees view of their viewers / readers.

These profiles can be used for several reasons. First of all, revenue derived from advertising can be increased because those organizations with such detailed customer profiles are able to offer very targeted advertising that is more relevant and thus more expensive for the advertiser. Advertising can become multi-platform (think second screen advertising via tablets during series or shows on television). It will also enable those organizations to better understand what their audience is looking for. When they start data mining all the data, it will give valuable insights, including nuances, what the audience really wants. This information can be used to build new products around existing shows or to develop new series, movies or shows.

Big data can also be used to understand whether a movie or a series will be a hit before shooting it. Historical data about different shows such as when a user pauses, forwards, rewinds, replays or stops a TV series provides valuable information. Combined with the detailed (social) profile of the person watching as well as many different tags related to a series or movie created by viewers and there is an extremely valuable data stream that provides insights whether or not a series or movie will be a success. The best example here is Netflix that bought “House of Cards” based on thorough data analysis of their 33 million users. All that data even allowed them to outbid other major players like HBO and AMC. In addition, the data showed Netflix that a significant part of their users were watching marathon-style, so Netflix decided to go against all traditional ideas and release the season of “House of Cards” all at once.

Finding the secret messages in the data that the audience is unknowingly broadcasting is key for the media and entertainment industry to outperform peers: in what phase of their lives are their viewers now, what to they think is important, what are they looking for, what do they recommend to whom and why, what motivates and inspires them, what are they watching and how do they respond to it via social networks etc. This kind of data, which is really generated at any point of contact via all channels, enables media and entertainment organisations to understand viewers sentiment in real-time. All the collected information can be used to deliver a personalized TV experience via TV set top boxes or smart TVs, where content is recommended based on the user’s profile.

In addition, it can be used to optimize multi-channel ad campaigns. Consumers are consuming media on multiple devices at the same time. Optimizing ad campaigns across multiple devices will strengthen the message of the commercial. With big data it is possible to understand which consumers use a second screen, where and when and deliver the right message via the right channel.

The sport industry is of course a great example how they leverage the experience for viewers with big data and with second screens. During the past three Grand Slams of this year, IBM enabled viewers to watch every available statistic about their favourite player, vote for players etc. Their program, Australian Open, is a real-time statistics and data visualisation platform that leverages their predictive analytics technology. The mobile application provided detailed live statistics to the viewer while watching the game on television. A great way forward for the viewer and it is only a matter of time before we will see such tools also for series or movies.

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Image Credit: Surkov+Dimitri/Shutterstock
Dr Mark van Rijmenam
Dr Mark van Rijmenam

Dr Mark van Rijmenam is The Digital Speaker and available for (virtual) keynotes in-person or as avatar or hologram. He is the Founder of Datafloq and Mavin. Van Rijmenam is the author of the three best-selling management books, including The Organisation of Tomorrow, which discusses how AI, blockchain and analytics turn your business into a data organisation. He holds PhD in management from the University of Technology Sydney on how organizations should deal with Big Data, Blockchain and (Responsible) AI and he is the publisher of the ‘f(x) = ex‘ newsletter read by thousands of executives.

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