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BBC Uses Artificial Intelligence to Track Down New Audiences for 'Sherlock'

Parrot Analytics provides a new way to measure TV audiences, even when they're not watching TV.

BBC Worldwide

Viewers in Britain and the United States have been clamoring for the return of the critically acclaimed BBC series “Sherlock,” which debuts Jan. 1 with a special episode set in Victorian times.

But where else in the world might the British broadcaster find viewers for the contemporary interpretation of Sir Arthur Conan Doyle’s fictional detective? To sniff out clues, BBC Worldwide has retained Parrot Analytics, a New Zealand firm that uses artificial intelligence and data science to evaluate global demand for TV shows.

“Parrot suggests very very strong global demand, including in Germany, China, India and Singapore,” BBC Worldwide Executive Vice President David Boyle. “What’s most interesting are the countries with the highest demand but where we haven’t seen it come through in previous deals.”

Since the advent of television, programmers have struggled with measuring the audiences they already have, let alone predicting where they might be in the future. The industry’s traditional approach to estimating audience size — TV ratings — doesn’t count viewing across multiple screens, distributors and markets around the world. Measurement firms have been scrambling to fill in the gaps. The dominant player, Nielsen, plans to introduce a new total audience measurement for the U.S. early next year that includes online and mobile viewing. It also has partnered with Twitter to develop a separate rating that reflects social media conversations about TV shows. Specialized research firms such as Fizziology plug into Twitter, Facebook, Tumblr, Instagram and blogs to give Hollywood studios insights into online conversations about movies.

Parrot takes a different — and, it argues, more comprehensive — approach to evaluating interest in TV shows in markets around the globe. It creates a measurement called a “demand rating” that reflects interest in a TV show as expressed across photo-sharing sites like Instagram, online video sites like YouTube, social media platforms like Facebook, file-sharing sites and fan and critic blogs.

“If I want to express my demand for a piece of content, say, ‘House of Cards,’ I can stream it on Netflix or I can watch clips on YouTube or [post comments] to microblogging sites like Reddit, where 200 million people discuss TV content,” said Parrot Chief Executive Wared Seger. “You look at all of this and essentially you now have a truly ubiquitous measure that tells you how much demand there is for a piece of content.”

Parrot’s technology, developed by a team of data scientists and entertainment executives pulled from Sony Pictures, MGM Studios, the MIT Media Lab and Pukeko Pictures, uses pattern identification and contextual techniques to synthesize petabytes of data from 249 countries into meaningful information. The technology weighs viewer sentiment, evaluating just how obsessed people are with a show (“Liking” “Orange Is the New Black” on Facebook is less of a sign of true fandom than blogging about it).

 Parrot Analytics compares demand for the BBC’s “Sherlock” with Netflix’s “House of Cards.”
Parrot Analytics compares demand for the BBC’s “Sherlock” with Netflix’s “House of Cards.”
Parrot Analytics

“Not all fans are equal,” Seger said. “Some will talk about it, advocate for it. Others will be passive consumers who drop off after the third episode. Our demand metric takes that into account.”

Parrot’s demand rating is intended to help buyers and sellers of TV programs, such as BBC Worldwide and the New Zealand-based streaming service Lightbox, focus their global distribution efforts and inform programming decisions, like shifting the time or day a show airs when its TV ratings don’t line up with projected demand. Parrot is in active discussions with other studios, networks and streaming services, according to a source familiar with the matter.

The British broadcaster conducted extensive testing, with a number of BBC Worldwide shows in a number of countries, before agreeing to work with the nascent company.

“It took me six months of working through that detail and testing it and trying it out to feel confident enough to showcase it and promote it and advocate for it throughout BBC Worldwide,” Boyle said. “Most people don’t make time to properly investigate things like this and so they walk away too soon when they can’t get quick wins.”

Boyle is a believer in the power of data. He said the BBC’s consumer research in South Korea suggested strong demand for “Doctor Who,” the long-running series featuring an alien time-traveler who moves through space and time in the Tardis, a spaceship that resembles the blue police boxes that were ubiquitous when the series launched in 1963. Regional teams were skeptical.

As a test of viewer interest, BBC Worldwide included Seoul in a 2014 “Doctor Who” promotional world tour that invited fans to snap selfies in the Tardis and buy tickets to meet the actor portraying the Doctor, Peter Capaldi, and the actress who plays his companion, Jenna Coleman. Some 50,000 people signed up in minutes for a chance to purchase the 4,000 available tickets, Boyle said.

This proof of concept for data-driven insights set the stage for BBC Worldwide’s more recent work with Parrot, helping it evaluate the 200-plus markets where it functions as a studio, distributor or broadcaster.

Boyle said Parrot’s data helped bring one unidentified broadcaster back to the bargaining table, after conversations had gone cold. The data indicated strong demand in the country — and the program has been successful for the network. Another Parrot insight is causing BBC Worldwide to rethink its distribution strategy for another show, whose traditional TV ratings are down but still enjoys strong demand among online viewers.

“It provides new ways to understand this kind of stuff,” Boyle said. “What these guys do is bigger, better, more scalable than research we could possibly do — by orders of magnitude.”

This article originally appeared on Recode.net.