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Big Data Is Going To Save The Film Industry, Too

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star trek into darkness movie theater

As we approach the critical summer box office sales period, there's no doubt the media industry has experienced a fundamental shift. 

We’ve evolved from business models fueled by analog content and scarce distribution to a digital world of empowered consumers who are increasingly in control of where, when and how they consume content.

This has been a gradual but unrelenting shift for every segment of the industry, from studios and televisions networks, online news outlets, marketing and advertising firms, to cable companies.  The result is that the “digital era,” which was boldly launched with the introduction of the Internet, is now behind us and a new “connected consumer era” has arrived.

Now, media and entertainment organizations must go beyond ‘being digital’ in order to keep pace with this fast evolving environment. They need to develop strategies that build new value on top of their digital production and multi-channel distribution plans. To do so, firms will need to understand their audience and their behaviors in a much more nuanced way, applying “social intelligence” to communicate directly with consumers via social media. This requires taping into the bi-directional flow of communication and data that was not possible just a few years ago.

The important shift is that consumers aren’t just consuming content on their smart phones, tablets and PCs—they are publishing information as well. Social media outlets such as Twitter, Facebook, LinkedIn and blogs are creating a tornado of consumer feedback that has the power to change every aspect of the industry; what brands prosper, how movies are produced and marketed, how TV shows are offered, and where and when ads appear.

This new well of limitless data can supply insights into how a new single will place on the music charts, how a book will rate on best-seller lists or whether an upcoming movie will soar or flop and who in the audience are the likely consumers and key influencers.

With this new ‘data’ conversation comes the ability to understand what consumers want and what they recommend—what inspires their choices and what motivates them to act, or to recommend that others do so.  As users comment, make purchases and share information, data is generated with every click, screen touch or comment.

However, social media coupled with the ability for consumers to navigate, search and access content anywhere, at any time and on any device, is enough to leave media organizations dizzy with data. Now comes the challenge of deriving value from all this data, not just in terms of reading and aggregating what is being said, but in analyzing the data to understand and better connect with consumers.

Advanced analytics software is the key to helping companies reach the right consumers with the right products and services and using the right messages. Then, linking this ‘engagement’ data with ‘transaction’ data, media companies can develop a clear picture of what is really happening. 

Recent projects completed by IBM and the University of Southern California Annenberg Innovation Lab highlight the possibilities of using machine learning and natural language processing capabilities to comprehend consumer sentiment from the unstructured human language data flowing from Twitter and other sources.

Social sentiment analysis makes it possible to distinguish between positive and negative opinion, and even distinguish irony, or snark from sincerity – on any given topic – sports, movies or retailing.  Analyses on the Oscar race, Thanksgiving Box Office, the World Series, the Super Bowl, movie trailers, to EuroVision in France, have proven the possibilities.

This capability goes beyond just identifying pop culture trends, or buzz, it puts CMOs in the driver’s seat with the insight to change the course and outcomes for their business.  Today’s chief marketing officers accept that traditional segmentation is no longer sufficient as traditional advertising is now intertwined with new digital forms.

This nuanced view will provide a foundation for new revenue models; models that are built upon a multi-channel approach which involve listening across platforms, understanding the unique preferences, desires and usage patterns of consumers and communicating back in a relevant, compelling manner. Additionally, this new approach will require an evolution from a focus on audiences to a focus on consumers and the many touch-points they have with your enterprise.

For firms in the Media industry, the path to future success lies in the data – the ability to combine static and real-time data, to blend transaction and human language data, in an effort to find the patterns and linkages that can transform the entire business.

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