In fact, I wouldn’t be at all surprised to see a “Big Data” movie or three in development at this time. When the folks in Tinsel Town get their mitts on it, Big Data will probably jump to the silver screen as a sequel-ready action-adventure property. My guess is that it will feature Matt Damon as a morally conflicted data scientist and Zoe Saldana as the hotshot Hadoop administrator who helps him mine the social cloud to uncover some terrorist plot. Or whatever.
Big data has already arrived in the media and entertainment (M&E) industry’s internal operations, and it’s growing its footprint, as this recent article makes clear. The authors state that the studios have long relied (with mixed results) on Monte Carlo analysis to predict movie box-office numbers, TV ratings, and other metrics of audience demand. They also discuss the wide range of M&E applications that use data science to estimate the bottom-line return on content-centric projects over their economic life cycles.
For starters, the major studios are making an aggressive push into social listening analytics for more nuanced, real-time prediction of audiences for theatrical releases. In addition, M&E companies are using advanced analytics to predict film revenues in follow-on distribution channels (e.g., DVD, cable, online, international); attribution analysis to gauge the impact of diverse marketing channels, programs, and messages on audience turnout; microsegmentation analysis to finely tune their marketing campaigns to every niche of their target audiences; and geospatial analytics to tailor film-distribution schedules by country, region, and city. The studios are even using the latest, greatest big-data tools to predict who’ll take home the Oscars this time around.
In a very real sense, you could argue that the data scientists who produce these statistical models are shadow Hollywood “players.” Their models and the insights they generate sit around the virtual table that decides which M&E projects get financed and greenlighted for production. Though the article doesn’t state it as such, there’s no denying that studios are probably using these models to shape the helpful advice they freely dispense to producers, directors, and other creative personnel–you know, the “what you’re proposing won’t play in Peoria” dictates that warm the hearts of folks in the professions that receive the Oscars.
Considering how fundamental Web TV, social media, and other digital channels are to M&E’s evolving revenue model, we’re likely to see data science and big data play an even stronger role in the creative process from now on. The bumper crop of real-time customer-sourced big data coming from these channels (what they tuned to, what they tweeted about it, etc.) makes it instantaneously clear which properties have immediately stroked a responsive chord in their target audiences vs. which have fallen flat. The studios would be remiss if they didn’t factor this dynamic audience research into the continuing fine-tuning of every aspect of the content, its delivery, and its marketing.
The creative artists who scream that this emerging approach is strangling the creative process will increasingly find their backs against the wall. Some will respond by vilifying big data as some sort of fascist force that’s ruining Hollywood. But others will embrace big data analytics as providing a useful resource to help them guide their projects toward successful delivery and maximum audience impact.
The net impact of big data on the M&E creative process won’t be all good or all bad, in spite of Hollywood’s love for painting everything in shades of black and white.