Remember Moneyball, the film about the revolution in baseball strategy in the 2000s when Oakland Athletics’ General Manager Billy Beane eschewed traditional stats for new data, helping the team find undervalued players who could deliver wins?
A new report from Industry analyst TV[r]EV, “Playing OTT Moneyball: A Data-Driven Content Acquisition Strategy for Streaming Platforms,” argues that acquiring the right content to build and retain an audience is similar. No longer is it about picking the hits Fred Silverman-style. It’s about finding that undervalued niche content, the programming that maybe isn’t the blockbuster but hits a spot that viewers want to return to, again and again.
Deep data can help locate those niches and is revolutionizing content strategy, says TV[R]EV taking a look at the OTT data-as-a-service offerings from PeerLogix, which scrapes the data of around 200 million viewers worldwide to find the hidden connections and hidden programming values.
With pay services, viewers might expect high-quality, high-profile, and current topics.
“But when they are engaging with a FAST (free ad-supported service), they are looking for what’s commonly known as ‘comfort food TV’, full seasons of older sitcoms or reality shows they are very familiar with, favorite classic movies they have seen many times over or possibly movies starring their favorite actors that weren’t box office smashes and thus flew under the radar,” Will Gorfein, founder and CEO of PeerLogix, told TV[R]EV.
PeerLogix’s technology analyzes the viewing data of about 50,000 pieces of premium programming across every open-source OTT (over-the-top) platform, the company says, enabling insights for OTT providers, advertisers, content creators, and investors.
Its patented technology “in the stream” is posing as a content distribution node for the vast majority of open-source peer-to-peer, long-tail OTT networks, and cataloguing viewership data, says the company. It claims to analyze viewer data going back five years.
Just as Billy Beane looked away from the old stats like batting average and earned runs in favor of new measures like OPS (the combined on-base and slugging percentages), PeerLogix has its own fresh stats — the Niche Attractor score, the Binge Factor, the Churn Reducer score — to identify value among the thousands of content options available.
The goal of a Niche Attractor series, for example, is to attract that strong fan base of loyal fans who will watch every episode of a show, and everything connected with it. Niche attractor series, TV[R]EV explains, may not have had stellar ratings when they were first on TV, but they attract a fan base that chats about the show and cast online well after the show is off the air.
“The best Niche Attractor series are the ones that are hard to find,” Gorfein said to TV[R]EV. “Fans may have been watching bootleg low-res copies on YouTube or downloading them off file servers. But as soon as you add one of these to your line-up, word is going to spread among the community, and they are going be coming to your site and talking you up.”
Firefly and Samurai Jack are classic Niche Attractors.
Churn Reducers, usually a series, have high rates of repeat watching. They’re shows the viewers have seen many times and are ready to watch again — the TV version of “comfort food.”
These are typically older shows, not the new releases that drive subscriptions, but which also lead to churn when the series ends. They work well as mainstays on a FAST.
“The viewer’s tendency is to click around the app and to see what’s there,” Gorfein told TV[R]EV. “When they encounter a Churn Reducer series, that stops them, because they’ve found something they know well and feel close to. They know that whenever they go back, there will be dozens, if not hundreds of episodes of that series waiting for them. That’s a huge win.”
The Binge Factor is generally thought of in terms of relatively new releases that viewers gobble up in chunks. But it also applies to older shows, movie series, and other content. The cable “marathons” of movies around different themes or actors have been examples of binge fare for decades.
All this data can also help providers fill out their programming lineup with shows that are likely to hook the audience. Typically, the back bench of programming for providers is the lower-cost options. According to TV[R]EV, PeerLogix will perform an audit of a platform’s best performing genres and titles and then find shows that may have lower raw streaming rates but high correlations with shows with high viewership.
“Rather than being selected randomly, these titles represent ‘Hidden Gems’ that are more likely to appeal to the platform’s specific audience and can be acquired at lower costs,” TV[R]EV writes.
As streaming options proliferate and competition intensifies across the industry, this kind of data could be the difference between success and failure for many programmers looking ahead, says TV[R]EV.
READ THE COMPLETE REPORT HERE: Playing OTT Moneyball: A Data-Driven Content Acquisition Strategy for Streaming Platforms (TV[R]EV)