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Big Data and the Future of Entertainment Part 1

Shake off some of that Labor Day rust by checking out the first part of a Q & A with Mike Smith and Rahul Telang who are the authors of Streaming, Sharing, Stealing: Big Data and the Future of Entertainment. Their book is about how big data is transforming the creative industries, and how those industries can use lessons from Netflix, Amazon, and Apple to fight back.

How has the rise of data analytics (and Big Data) transformed entertainment and leveled the playing field?

Before the rise of Internet-based platforms, it was extraordinarily difficult to interact with customers as individuals. For a century, the only data entertainment firms could observe about their customers was the behavior of broad segments of the population—18-24 year old white males, for example—but they had no way of connecting with these consumers individually. And even if they could have observed the behavior of individual consumers, there was very little they could do with this information given the limitations of their broadcast distribution channels and brick-and-mortar sales channels.

The interactive nature of online channels has changed all that. Companies like Amazon, Google, and Netflix don’t think about their customers in terms of broad demographic characteristics. They are able to use their data and their platforms to understand individual customer preferences. This, combined with the ability to control what content is shown to customers based on those preferences, and the natural “winner-take-all” nature of many online markets, have given these new platform firms a great deal of market power.

And they have used this power to change the way content is consumed by the audience, and change the business model for content distribution. This puts the platform companies in an even more powerful position as consumers adopt and adapt to these new distribution models.

How have online sales channels like Netflix and Amazon shifted consumption of traditional blockbusters or “hits”?

Prior to the Internet, entertainment channels could only distribute a small number of products. Movie theaters, radio station playlists, and even bookstore shelves were all limited in terms of the number of movies, songs, or books they could sell. This meant that markets for entertainment were dominated by a small number of “blockbuster” products.

Online markets don’t face the same capacity constraints that existed in brick-and-mortar distribution channels, and the data show that consumers’ tastes are far more diverse than what they can find on linear television channels or in traditional brick-and-mortar markets. So, when Amazon allows its consumers to choose from millions of books in print, or when Netflix provides on-demand access to tens of thousands of shows, the data show that consumers find a lot of value among the obscure titles that weren’t stocked on the old distribution channels.

Some people in the entertainment industry are concerned that big data could harm the creative process. Do you see this happening, or feel something else is at play?

Using algorithms to replace storytellers would be bad for the creative process, but that is not what’s happening. Netflix didn’t use big data to influence David Fincher and Beau Willimon’s vision for House of Cards. Instead Netflix’s on-demand platform and their ability to find just the right audience for specific shows gives storytellers a level of creative freedom they wouldn’t have had in the traditional broadcast television model.

This is likely to enhance the ability of great storytellers to tell great stories. In fact, original content on Netflix and Amazon has won numerous industry awards for creativity. And stars like Kevin Spacey find the experience of working on such original content transformative: Spacey noted his role on House of Cards as “the most creatively rewarding experience I’ve ever had in front of the camera.”

What makes today a pivotal moment in entertainment (motion pictures, television, publishing and music industries)?

So many things about the industry are changing all at once. Piracy, big data, long tail content, digital distribution platforms, and self-produced content are all playing a role in weakening the existing sources of power in the industry, and in creating new sources of power that are outside of the control of traditional leaders.

What will enable legacy companies to survive?

We argue that industry leaders need to do two things:

First, they need to embrace data-driven decision-making and a data-driven culture. Look at the transformation of Harrah’s Casino from a gut feel driven business to a data-driven one.

The challenge with making this transformation is that there are a lot of people in the business who worry that embracing data will hurt the creative process. We strongly disagree. We think a responsible use of data will actually enhance creativity and improve storytelling by enabling great storytellers to find their audience and by creating opportunities for them to tell stories that wouldn’t work in traditional channels.

Second, legacy companies need to invest aggressively in new digital distribution platforms to compete with companies like Amazon, Google, and Netflix. The investment Disney, Fox, NBCUniversal, and most recently Warner Brothers have made in Hulu is a great example of this. The Hulu platform allows these studios to gain direct access to customer data, and gives them the ability to create and distribute content based on the specific needs and preferences of their individual consumers.

The industry’s challenge is maintaining their commitment to new platforms like Hulu even as these platforms cannibalize sales in the industries’ existing distribution channels.

Stay tuned for the next round.

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The MIT PressLog is the official blog of MIT Press. Founded in 2005, the Log chronicles news about MIT Press authors and books. The MIT PressLog also serves as forum for our authors to discuss issues related to their books and scholarship. Views expressed by guest contributors to the blog do not necessarily represent those of MIT Press.