TV recommendation apps creating data-mining, retention opportunities

It’s a familiar refrain — a viewer flipping through hundreds of channels, complaining there’s nothing to watch. Consumers today have access to more content than ever, not only through a growing number of TV channels, content from which they can save on personal video recorders (PVR), but also through on-demand video and over-the-top (OTT) alternatives. The sheer amount of choice means customers could use help in digging through the mountain of content, and TV providers are betting that recommendation engines can not only do that, but also stop some of those customers from going to the competition — and maybe even gather the kind of data that can lead to personalized ads. “One of the main purposes here is to, in effect, improve the value proposition of pay TV,” Keith Nissen, senior analyst with SNL Kagan in Arizona, said in a telephone interview. TV providers and content producers recognize that if customers can’t find the content they’re most interested in, they’re “not going to be satisfied,” he said. That’s why, he added, all the major TV service distributors in the U.S. and Canada have implemented recommendation engines in “one way, shape or form or another.” Most of those recommendation engines are used for video-on-demand (VOD) content, but they’re also they’re being rolled out for live TV, Nissen said. “Why should I have to scroll through 250 channels in order to find what’s on?” he asked. “So what the next evolution is, once typically a pay-TV service provider has rolled out a recommendation engine for their VOD, they often times have another one ... for their broadcast.” Nissen said it’s still unknown whether the technology will actually bring in revenues, and that the proliferation of these engines will be determined not only by whether they end up increasing customer satisfaction, but by whether they end up being profitable. “The next evolution,” he said, “is what kind of data are they collecting to this and how can they use it to their advantage?” Nissen said that recommendations would allow pay TV operators to collect “big data” on their customers, since the types of content they are watching can provide indications about gender, age, income and other demographic data. One way to make recommendations profitable would be to leverage that data and introduce personalized ads, he said. “The back end of all this is that they all want to figure out how provide personalized ad insertion so that then they can make money off the personalization of these services,” he said. “If can’t generate more revenue, meaning personalized ad insertion,” Nissen asked, “then what is the business basis for deploying these things?’ Perhaps the most recognizable engine out there is that pioneered by Netflix Inc. The company, which employs 800 engineers, credits its recommendation engine for 75 per cent of viewer activity on its streaming service, Wired reported this summer. In Canada, a number of broadcast distributors have also been getting into the recommendation game. Last year, SaskTel launched recommendations for its IPTV service. It said in a release at the time that the service would be “capable of recommending both video-on-demand content and linear TV programs in an integrated way,” and said that the launch was “one of the first full-blown deployments of such a system in North America.” Rogers Communications Inc. launched a recommendation app for its NextBox PVR service in November, saying in a release that “the app gives access to personalized live, rental, on demand and previously recorded program recommendations displayed right on TV screens.” Earlier this month, Telus Corp. launched a service for its Optik TV customers, giving them access to recommendation and rating features when they use the company’s VOD service. BCE Inc.’s PVR offerings don’t include a personalized recommendation service, though Shawn Omstead, Bell’s vice-president of residential product management, said the company wouldn’t rule out offering them in the future. While Bell currently offers recommendations on its video-on-demand service, those are based on ratings from the movie review website Rotten Tomatoes, and aren’t personalized based on viewing habits. “I think recommendations are fantastic,” he said. “I think recommendation engines are fantastic. I think that certainly that’s a trend in the industry that I think we’ll continue to look at and see if we can add value to the current service.” He did not provide any details about services Bell might launch. The reason Telus introduced recommendations for its VOD service is that the company has expanded the amount of VOD content it offers, and customers told the company they had trouble picking something to watch, said Greg Goodwin, vice-president of home solutions at Telus. “People are overwhelmed by the choice,” he said. By making it easier to find content, recommendations boost viewership, Goodwin said. “You get to the content quicker and you don’t get frustrated by not finding what you want to watch.” Recommendations can also increase viewership by allowing customers to discover content they might be interested in. For instance, instead of a customer cancelling their Super Channel subscription after the latest season of Homeland is over, recommendations could lead them to discover other shows that are broadcast on the channel, causing them to keep the subscription, Goodwin said. Recommendations could also help TV providers fight curb shaving, he added. “I think recommendations will just keep people viewing the content on OptikTV spend 10 minutes in the menu, get frustrated that they don’t find something and fire up Netflix to see what’s over there,” he said. Goodwin said the company would consider expanding the service to live TV and PVR recordings. “We’re certainly going to evolve and enhance it as we get feedback from customers on what features they’d like to see,” he said, adding that it’s still “early days” for the technology. David Purdy, senior vice-president of content at Rogers, said the company introduced recommendations because customers weren’t aware of the options available to them. “The more you can do to make people aware of the content, the higher the usage and engagement,” he said. For instance, customers who use services like VOD or TV everywhere tend to churn at lower rates, Purdy said, and he expects the recommendations to work in much the same way. He said TV providers have access to the most recent seasons of popular shows on channels like HBO, unlike their OTT competition, but customers have to be made aware of that. “If we’re going to solidify the place in the home, and the share of wallet for, say, Super Channel or TMN, we’re going to have to help these customers find the amazing shows that exist there,” he said. “With the recommendation app, you’re going to finish watching True Blood, and it’s going to say, ‘Here’s five other shows that are available that you already have access to.’…. And I think you’re going to see a lot more usage and engagement and, ergo, a lot stickier customers.” Purdy added that as the company rolls out more advanced set-top boxes, they will integrate the kind of features and functions, like search capabilities, that are currently available on the web. “Ultimately, we want the online and the set-top box to be very, very similar, if not identical. And so the recommendation engine is one thing we’re doing to improve navigation, but not the only thing,” he said. That kind of evolution is necessary, Purdy said. “If we don’t evolve from a linear cable offering to a service that allows you to watch what you want, when you want, where you want in a meaningful way, then I think we do run the risk of losing customers,” he said. — With reporting by Anja Karadeglija at akarad@thewirereport.ca and editing by Derek Abma at dabma@thewirereport.ca

TV recommendation apps creating data-mining, retention opportunities

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