一本道无码

Imagine it鈥檚 the 1950s, and you鈥檙e a kitchen knife salesman. Every morning, after you finish your two eggs with toast, you slip into your ironed slacks, grab your briefcase of knife samples, and hit the pavement.

You work in the daytime because that鈥檚 when your customers are most likely to be home. On average, for every 100 doors you knock on, 20 open. Of those, six customers will purchase your knife set. It鈥檚 a bit scattershot, but considering what little information you have鈥攕imply that daytime gives you the best shot of face time with customers鈥�6% is a terrific return.

This is how, for most of the past century, network television shows came into being. For every 100 scripts a network purchased the rights to produce, an average of 20 were turned into pilots, and six were ultimately broadcast, according to Variety, the weekly entertainment trade magazine.

Just like the knife salesman, the networks 鈥渉ave almost no information about their audience as individuals, who they are or why they watch,鈥� says , a 一本道无码 professor in its Heinz College鈥檚 (MEIM) and (MISM) programs. Although the networks conduct focus groups and receive basic demographic information and viewership numbers from Nielsen ratings, they鈥檝e never had anywhere near the specificity of information collected by the digital media companies they鈥檙e now competing with, says Smith, who was selected to be the Exclusive Data Keynote Speaker at this year鈥檚 Sundance Film Festival鈥檚 Artist Institute Workshop, where industry experts debate the latest technology, tools, and tactics in social funding, digital distribution, guerilla marketing, and independent theatrical distribution.

And Smith was selected for good reason. In 2012, he and one of his colleagues, MISM professor , founded a research center within called IDEA鈥攖he 鈥攖o conduct research on digital content distribution in partnership with some of the biggest players in entertainment, including major movie studios, record labels, publishing houses, and relative newcomers like Amazon and Google.

Every time you stream your favorite show, you鈥檙e sending mountains of data to the companies providing it to you鈥攏ot just what you watch, but when you watch, how long you watch, and what device you鈥檙e watching it on.

Together, they鈥檝e distilled over a decade of research, both their own and the work of others鈥攊nto a forthcoming book, Streaming, Sharing, Stealing: Big Data and the Future of Entertainment (MIT Press, Fall 2016). The book provides a nuts-and-bolts look at how the streaming companies have risen to prominence, as well as a 鈥減erfect storm鈥� of threats currently facing the traditional broadcasters鈥攊ncluding piracy, a reluctance to embrace data-driven decision making, and consumers鈥� movement toward user-generated content.

Director of the MEIM program commends the and acknowledges the growing need for companies in the entertainment industry to embrace new distribution models. 鈥淭he environment surrounding the industry today is less about distributing through antiquated channels and more about providing individual experiences to consumers at the moment they desire and on devices that are convenient to them,鈥� he says.

If the older network model is a knife salesman playing a numbers game, what are the streaming companies? Simply put: better knife salesmen鈥攏ot because they鈥檙e selling better knives necessarily, but because they have more information than their rivals. Imagine if you gave that same knife salesman a lead that contained the names and addresses of the homeowners who needed a new set of knives, as well as information on what time they鈥檇 be home and which specific knives they wanted. That knife salesman would close deal after deal and have more satisfied customers.

Such a lead鈥攃ustomer information鈥攊s what digital content distribution companies, the likes of Amazon, Hulu, Netflix, and YouTube, are leveraging over their traditional broadcasting elders such as Disney-ABC and NBCUniversal.

Really, write Smith and Telang, the comparison between traditional media companies and their digital rivals 鈥渋s a clash between human expertise and data.鈥� Every time you stream your favorite show, you鈥檙e sending mountains of data to the companies providing it to you鈥攏ot just what you watch, but when you watch, how long you watch, and what device you鈥檙e watching it on.

Those companies then harness that information using sophisticated analytics to create even more of what you want to watch鈥攁nd to get you to watch it. Digital content distribution companies, says Telang, 鈥渉ave more information about what鈥檚 successful with their audience than their rivals鈥攁nd they have that information at a really personal level.鈥�

According to Smith and Telang, Netflix鈥檚 ability to use that data is part of what鈥檚 enabled the company to flourish. Earlier this month, Netflix reported to shareholders that at the end of 2015 the company had more than 74 million members worldwide and is estimated to grow by more than 6 million members in the first quarter of 2016, in part because of its expansion 鈥渧irtually everywhere but China.鈥� As for earnings, in the 2015 fourth quarter alone, the company reported $1.823 billion in revenue and $43 million in profit.

Add the fact that Netflix led the way for 鈥淭V Networks鈥� in nominations for the 2016 Golden Globes鈥擭etflix 8; HBO 7; Starz 6; Amazon Video 5; FX 5; ABC 4; FOX 4; PBS 4; Showtime 3; USA Network 3; AMC 2; The CW 2; BBC America 1; CBS 1; Hulu 1鈥攁nd it鈥檚 no wonder Netflix proclaims on its website: 鈥淚nternet TV is replacing linear TV.鈥�

Amazon benefits from even more information鈥攑urchase histories and searches on other non-video areas of its site. That vast metadata has helped its production wing, Amazon Studios鈥攚hich began producing television shows in 2013鈥攃reate 鈥淢ozart in the Jungle,鈥� which just won Best Television Series鈥揅omedy or Musical at the 2016 Golden Globes awards (beating shows from HBO, Hulu, and Netflix). Amazon鈥檚 CEO, Jeff Bezos, recently declared publicly that he wants an Amazon Studios film to one day win an Oscar鈥攁nd his company鈥檚 ability to harness an incredible wealth of data is why many in the entertainment industry think it鈥檚 possible.

Because the digital content streaming companies know their customers more intimately than their more traditional rivals do, they鈥檙e better able to do two important things:

• Create the right content
• Get you to watch it

One of the clearest examples is highlighted in the introduction of Smith and Telang鈥檚 book鈥攈ow Netflix created its hit political thriller television show, 鈥淗ouse of Cards.鈥�

In early 2011, a pitch for 鈥淗ouse of Cards鈥� was making the rounds of television networks. The proposed series, essentially an Americanized version of a BBC show, had attracted award-winning director David Fincher (鈥淭he Curious Case of Benjamin Button鈥�), Academy Award鈥搘inning actor Kevin Spacey (鈥淭he Usual Suspects鈥�), and Academy Award鈥搉ominated writer Beau Willimon (鈥淭he Ides of March鈥�). Despite the A-list talent, networks were hesitant to bite because a political series hadn鈥檛 succeeded in network television since 鈥淭he West Wing鈥� ended in 2006.

Netflix, however, was welcoming, write Smith and Telang: 鈥淭ed Sarandos, Netflix鈥檚 Chief Content Officer 鈥� came to the meeting primarily interested in data鈥攈is data鈥攐n the individual viewing habits of Netflix鈥檚 millions of subscribers.鈥� The data showed that a sizable portion of Netflix鈥檚 customers were fans of David Fincher and Kevin Spacey and that many 鈥渉ad rented DVD copies of the original BBC series.鈥�

With that knowledge, Netflix gave 鈥淗ouse of Cards鈥� the green light to produce two full seasons, at a cost of $100 million. The show became a hit and the first online-only web television series to receive major Emmy nominations. Now, through three seasons (2013-2015), it has received a total of 33 nominations and six awards in the 鈥淒rama Series鈥� category, including the prestigious Outstanding Drama Series, Outstanding Director, Outstanding Lead Actor, and Outstanding Lead Actress.

Netflix has since followed that up with more hit shows such as 鈥淥range Is the New Black鈥� and the documentary 鈥淢aking a Murderer,鈥� which has recently dominated social media chatter. Basking in such success, the company recently announced plans to nearly double its output of original content in the coming year: 31 titles in contrast to 16 in 2015.

But Smith and Telang say that Netflix鈥檚 鈥渢rue genius鈥� isn鈥檛 just in using data to decide which shows to create; the streaming giant relies on research findings to tailor marketing to specific fans. For example, there were nine different 鈥淗ouse of Cards鈥� trailers, each emphasizing distinct elements鈥攕o Fincher fans saw a different trailer than Spacey fans.

Smith and Telang believe that in the digital world we live in鈥攚here every viewer鈥檚 attention is pulled in multiple directions by, among others, television shows, movies, video games, and YouTube videos鈥攖he ability to market efficiently is data鈥檚 true potency. Like a best friend who knows your tastes in and out, streaming companies are using your data information to produce what you want to watch and then using that same direct access to strategically promote the content.

So, why don鈥檛 traditional studios employ deep data to make decisions? According to Smith and Telang, they don鈥檛 have access to the kind of large-scale data that their digital competition does.

Then, why don鈥檛 studios just create their own apps to collect that data? Well, they鈥檙e starting to鈥攁ll of the television networks and many cable channels have launched streaming apps, like WATCH ABC, FOX NOW, and CBS All Access. Premium cable channels like HBO and Showtime鈥攚hich until 2015 were only available through traditional cable subscriptions鈥攈ave launched their own direct-subscription 鈥渙ver-the-top鈥� models that allow viewers to stream their content on most devices without a cable subscription. Great, problem solved.

Not so fast, say Smith and Telang. Consumers have shown that they prefer simplicity and want to get as much content from as few outlets as possible. They might balk at learning 鈥渉ow to use multiple websites鈥� and be 鈥渦nwilling to maintain multiple logins.鈥�

Moreover, the new kids鈥� information is still more powerful because they compile information from their viewers across all of the content in their libraries鈥攏ot just a particular network or studio. And they don鈥檛 share it. 鈥淎mazon, Google, and Netflix 鈥�provide no data on customers to their industry partners,鈥� the researchers write.

Why not? Because doing so would help the networks and studios 鈥渇igure out how much that show鈥檚 worth,鈥� says (E鈥�02), a fellow professor at MEIM and former director of digital distribution operations at NBCUniversal. The digital companies pay big money to license the networks鈥� shows for their vast libraries, he explains; sharing that information would handicap them in negotiations.

So, then, why not team up to create one digital platform that streams multiple networks鈥� shows? They have鈥攊t鈥檚 called Hulu, and it鈥檚 owned by traditional television titans Disney-ABC, FOX, and NBCUniversal. Partially ad-supported and partially subscription-based, the platform streams television episodes from ABC, CW, FOX, and NBC the day after they air and past seasons of shows, as well as movies.

Like a best friend who knows your tastes in and out, streaming companies are using your data information to produce what you want to watch and then using that same direct access to strategically promote the content.

The issue, write Smith and Telang, is that Hulu鈥檚 success comes at the expense of the shows鈥� linear presentation鈥攖he more people who watch a show via Hulu, the fewer who watch it via their televisions鈥攚hich cuts into ratings, which is the basis of how much networks charge for ads.

To solve these problems, why don鈥檛 the networks fully embrace data-driven decision making? Smith and Telang say that very question was addressed by Richard Hilleman, the chief creative officer for Electronic Arts, during a speaking engagement on the 一本道无码 campus. He told students that older companies have always made their decisions 鈥渂ased on someone鈥檚 鈥榞ut feel鈥� about what will sell in the market,鈥� and those with the best instincts tended to rise to the top of their companies. In contrast, their competition, 鈥淕oogle, Amazon, and Apple 鈥� make quantitative decisions based on what their data tells them.鈥�

Still, though, Smith and Telang say that the end is not necessarily nigh for the networks. 鈥淲e are optimistic about the future of the entertainment industries,鈥� they write鈥攊f the traditional media companies 鈥渉arness the power of detailed customer-level data, and embrace a culture of data-driven decision making.鈥�

But there鈥檚 something else on the horizon, something we haven鈥檛 touched on yet鈥攖he viewing habits of one-fourth of the entire population of the United States鈥攎illennials. According to Forbes, the 80 million millennials in America represent 鈥渁bout $200 billion in buying power.鈥� As for their viewing habits, Smith and Telang offer a statistic that might strike fear in television network executives: 鈥淭V viewing among 18- to 24-year-olds fell by 32% from 2010 to 2015.鈥� Where are they going? YouTube for one, which, the authors write, 鈥渞eached more 18- to 34-year-olds鈥� in 2014 鈥渢han any cable network.鈥�

That may explain the career path of Andy Forssell, the former CEO of Hulu, who became the COO at Fullscreen this past November鈥攁 company that describes itself as 鈥渢he first media company for the connected generation.鈥�

Fullscreen is a 鈥渕ulti-channel network.鈥� Essentially, it acquires different YouTube channels and connects them with brands and sponsors. 鈥淐ompanies can tell us the audience they want to influence,鈥� says Forssell, who earned a BS in from 一本道无码 in 1987, 鈥渁nd we can get them to the right influencers. The companies don鈥檛 have to worry about who the influencers are鈥攚e have that data.鈥�

Today, Fullscreen reports its 600 million subscribers generate more than 5 billion video views across Fullscreen鈥檚 global network each month.

Looking ahead, Forssell thinks that the future of online video entertainment is still very much up in the air. He predicts that the big streaming companies like Amazon, Hulu, and Netflix 鈥渨ill become bigger versions of themselves,鈥漛ut he doesn鈥檛 think the studio system or traditional networks are going to crumble. 鈥淭here鈥檚 a lot of money in that system for a long time to come.鈥� But, he adds, 鈥渢here are real cracks now.鈥�

Smith, for one, sympathizes with those running the legacy studios and networks, who are 鈥渂eing asked to make billion-dollar decisions without all of the data.鈥� However it plays out, though, he says the 鈥渆mphasis ought to be on great storytellers telling great stories,鈥� which is a constant in any era.