watchworthy
"This marks the open-for-business milestone," David Yon, who was brought into the company to lead Ranker Insights, told dot.LA. "Ranker is now available for B2B data licensing."
Ranker Insights will be the company's next step in its evolution from a website where someone can vote on their favorite U.S. president, fast food burger and Marvel Cinematic Universe character to a purveyor of consumer information, feeding the entertainment industry as it navigates a world dominated by streaming.
But in an industry awash in analytics, Ranker may face challenges in convincing customers that its data are valid. Although the company released a white paper with some description of its backend processes, it will likely need to peel back the curtain to prospective buyers.
Ranker is likely to face questions about the steps it takes to comply with Europe's complex data protection rules (GDPR), for example, and exactly how it is able to separate the signal from the noise, media analyst Dan Rayburn told dot.LA.
"There may be value there but the data's only as good as the methodology and how it's being collected," Rayburn added. "Everybody's always questioning that."
Ranker says that savvy companies know how to value its hoard of data. The company boasts over 160 million statistically relevant relationships and correlations on a range of consumer likes from their hamburger preferences to their favorite city in South America.
Chief executive Clark Benson, a serial entrepreneur who started Ranker 10 years ago because he liked lists and rankings and wanted to democratize them on the internet, said that within five years Ranker Insights could eclipse revenues generated by Ranker.com.
Ranker currently makes most of its money from its website via ads from streaming services such as HBOMax or consumer companies like Unilever. It's been profitable for over four years and though it's raised $7 million in venture funding, Ranker has financed its recent growth with its own cash, Benson said.
What Makes Ranker's Data Unique
The value of Ranker's data, the company says, starts with its volume. Those 1 billion votes and counting – which imply three votes per second over the company's 10 years of operating – come from over 70 million users. 40 million users visit the site on a monthly basis, according to the company. Voters spend over 4 minutes per visit and vote about 11 times per list.
"A lot of TV networks and studios, pay-TV and video on-demand platforms are not yet fully leveraging the power of data," Yon said.
Although the company's focus has been on building up rankings around entertainment – TV, movies, music and celebrities – the site also includes subjects like food, sports, fashion and history. There's data on favorite skin care products, grapefruit drinks and beaches in Hawaii. This variety and volume means Ranker can extract insights based on correlations.
"You start to build a connected graph that's not just about people's TV preferences but interconnected preferences," Benson said. For example, discovering the kind of music that fans of "Breaking Bad" enjoy, or the type of car to which "Call of Duty" fans aspire.
Building upon its data collection, the company launched Watchworthy in March. It poured a "7-figure investment" into the app and directed most of the company's product and engineering resources there over the past year. And it's paid off. The app had 13,000 downloads in its first month and Benson said it could ultimately drive half of Ranker's direct sales. Already Watchworthy has attracted some of Ranker's biggest advertising deals to date, Benson added.
But the app that gives television show recommendations for viewers based on their preferences has a larger purpose. Ranker will sift through the data from its website and Watchworthy to feed its Insights service.
Who will use Ranker Insights?
Yon — who has been in the data licensing business for over a decade, including stints at entertainment software company Rovi and TiVo — sees Ranker's data as valuable information for a variety of entertainment companies.
Streamers could use it to improve their own content recommendations and to guide decisions on which shows to produce and/or acquire. Studios could use the data to make casting decisions. Talent agencies may be interested in insights on which actors and directors positively correlate with which kinds of content and brands, Yon said. And the data could help content makers and brands alike to target audiences.
"When you look at the hundreds of millions of dollars companies spend on data, it's a huge market," Yon said. Ranker has done one-off data deals in the past but now it's Yon's task to consistently tap that market.
Device-makers, too, may find the data useful, especially as voice-activated search becomes more common. Yon says these queries tend to be more subjective and granular than text-based searches, which brings challenges in providing useful results. Ranker's data, he says, has the depth and richness to help meet that challenge.
"Sometimes living in your own bubble and ecosystem doesn't give you the insights and visibility you need, such as what's the right content, the right recommendations, the right ad targeting," said Yon.
But being an outsider can also be a disadvantage. Ranker won't be able to take into account every factor that a content provider considers when making programming decisions.
"Many times a (streaming company's) recommendation engine will recommend certain content where the licensing window is expiring or where the licensing cost is cheaper," Rayburn said.
That gap could diminish the value of Ranker's data.
Rayburn noted the biggest thing ad-based streamers are missing is the ability to provide personalized, programmatic advertising. That requires an improvement in the backend technological infrastructure, not data the likes of which Ranker Insights can offer.
"They're (already) kind of drowning in data," Rayburn said.
But Ranker Insights is more likely to find demand, he suggested, from the less data-savvy companies like traditional networks and studios.
Yon's challenge will be to convince potential customers that Ranker can provide value. Based on his experience, he expects it may take up to a year to get into the full swing of data dealmaking.
"Everyone says they're agile, but they usually have 6-12 month roadmap commitments," he said. "If you knock on a company's door today, unless you're extremely lucky, you have to get on their radar, build some mindshare, make it easy for them to take a spin when they have time on their hands and eventually you build the business case and then you strike the kinds of deals we're going for."
The 6-12 months that Yon says he has to build a proof of concept for Ranker Insights starts Tuesday. If he succeeds, he is optimistic about its prospects.
"It could easily exceed the revenue that we generate from Ranker and Watchworthy," he said.
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Sam Blake primarily covers entertainment and media for dot.LA. Find him on Twitter @hisamblake and email him at samblake@dot.LA
I don't think I need to convince most readers that this scenario isn't ideal for the consumer. So why are we here?
It's not that producers and distributors of entertainment content don't want to satisfy customers… they certainly do! But over the last decade or so, movie studios and television networks have seen the incredible power of using data analytics to inform decisions about what content to make, how to market it, to whom to market it and more. Subscription streaming services (like Netflix) observe everything that their viewers watch, and in turn use that information to determine what content to suggest to each viewer next. They even use it to inform decisions regarding what content to license or produce themselves and then to market that content most efficiently. They effectively create a series of personalized channels for each of their viewers, helping to connect you with content that you would love but might not be aware of. And in doing so, they can make investments in content in ways that differ from the traditional models and they reduce the inherent risk involved in bringing new shows and films to market. If you don't believe me, just ask the two professors from Carnegie Mellon who wrote a book about this.
In an era where there is more quality content – both old and new – available to us than ever before, it feels increasingly hard to know what to watch and where to watch it.
The problem that a traditional television network (or movie studio) has is that they do not get this kind of personalized data on each of their over-the-air or box office viewers – nor do they usually get these data from the subscription services that license their shows and films. Even if they had such data, they don't have a platform that serves as a direct connection to the consumer, and so they cannot personalize which shows they market to each viewer and how they market them. That's what subscription streaming services have been able to do. And for a while, networks and studios have felt pretty left out of the new data-driven entertainment revolution. This largely explains why so many major players in the industry want to have a successful streaming service now — to gather individual data about each viewer and have a personalized connection / marketing channel to every one of their customers.
If you are a major network or studio trying to get into the streaming game and you need to compete with an established service like Netflix – who consumers already know and like – what do you do? You fall back on what you are already great at and make content that everyone wants to watch, and you make it exclusive to your streaming service as a draw to new customers. Or you stop licensing your best catalog content to the established streaming players and make it exclusive to your new service (sorry, "Friends" fans, you'll need to pay for HBO Max!). Hence, nearly every one of the subscription services out there has at least a few shows that you probably want to watch, and great content feels fragmented across a plethora of services for which you struggle to remember all of the names.
Watchworthy's app is one of several trying to make it easier for viewers to find the content they're looking for, across services.
But even if the current fragmentation of content across so many services can be explained as a form of business competition, that does not make it ideal for the end consumer. I've already mentioned the obvious result that consumers are back to facing the choice of paying an ever-increasing multitude of subscription fees, missing out on content, or else turning to piracy. But there is another, less obvious consequence for the customer. When most content that was online was centralized on just one or two services, those services observed most of what a customer viewed online, and thus had a strong understanding of each consumer's preferences. Those services also had an incentive to recommend or market to you the content that you would like most.
Now, however, if you only do 15% of your online viewing on, for example, Hulu, they observe a lot less about your viewing preferences than when you did 50-60% of your television and movie viewing there. They just don't know you as well. Moreover, a service like Netflix or Disney+ only has the incentive to recommend to you the content that is on their service, even if there are shows or films that you would meaningfully prefer on other subscription services. And this leads us to the irony that in an era where there is more quality content – both old and new – available to us than ever before, it feels increasingly hard to know what to watch and where to watch it. By fragmenting content across so many services in an effort to draw in customers and have a more personalized relationship with them, players in the industry have unintentionally left customers struggling to search for and find the content that is best suited for them.
One of the most commonly offered solutions to streaming fragmentation is that we should just bundle the services again – some have suggested that you should be able to pick up a bundle of Hulu, Netflix, HBO Max, etc. for perhaps half of what it would cost to buy them each separately. This may partly solve the customer's budget problems, but note that it does not solve the problem outlined above – if our viewing is spread out across a multitude of services, then the underlying viewer data are still fragmented. No one service knows us particularly well, and no service has the incentive to connect us with the content that best matches our preferences.
Where this eventually leads is a subject for another article – perhaps we will see the failure or consolidation of some of these services, or perhaps a third party can solve the problems I have described even while a number of subscription services retain exclusive content.
There are examples of companies trying to address this issue such as Likewise, Justwatch, or WatchWorthy, but it is not clear whether or not they will succeed (disclosure: I myself am involved in a stealth startup working on a solution to this). Either way, I see this problem as one that requires a consumer-friendly solution, and I fully expect that the market will provide this one way or another.
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The average video streaming user spends over seven minutes deciding what to watch, per a 2019 study from Nielsen. With Comcast, AT&T, Quibi and Discovery all planning to launch streaming services to compete with the likes of Netflix, Amazon, Hulu, Disney, and Apple, making a choice is poised to only get harder.
Enter Watchworthy, which — in contrast to the platforms' own recommendation engines — will provide suggestions across over 200 streaming services.
People are streaming shows and movies more as the coronavirus fallout has decimated leisure alternatives and flushed people's lives with free time. According to a Bloomberg story, Wurl Inc. estimated that globally time spent streaming last weekend rose by an average of 20%. That seems likely to grow, based on a separate analysis from Nielsen finding that viewing spiked by over 60% during certain past shut-ins.
This could prove fortuitous for Watchworthy, which has been under development for a year or so, according to Benson, and coincidentally launches as demand for its service may be rising.
How does it work?
"It starts on Ranker.com," explains Chantelle Silveira, Ranker's Chief Product Officer, who helped manage the development of Watchworthy.
Ranker.com, which launched in 2009, is a trove of all kinds of rankings derived from user votes. Categories range from the relatively normal (The Best TV Shows to Binge Watch, The Greatest Animated Series Ever Made) to the wildly specific (TV Shows That Only Smart People Appreciate, The Most Epic Insults from Game of Thrones).
"Ranker collects around 15 million votes per month across tens of thousands of rankings," said Benson. "We have over 5,000 rankings about TV alone."
Over one billion votes in total have amounted so far.
Tracking and analyzing users' voting behavior across varied categories has enabled Ranker to construct user groups with highly detailed preference profiles, the company says. When Watchworthy users answer a few questions–a process described to dot.LA as akin to Tinder for movies and shows–it is this backend data from Ranker.com that the Watchworthy model uses to propose a recommendation.
"Watchworthy creates a digital taste fingerprint based on your unique combination of likes and dislikes," explains Silveira. The model then compares that fingerprint to millions of others in the Ranker database, and finds a similar user group. "Then it looks at what those people are watching, and not watching, to come up with your personalized list of recommendations."
Data and the Entertainment Business: What Watchworthy Shows
One of Netflix's early competitive advantages was its digital proximity to customers. Whereas legacy companies like Disney formerly needed to rely on third parties for much of their customer data–which was usually coarse and of limited usefulness–Netflix early on had direct access to highly granular, extremely useful data about its customers. Among other outcomes, this enabled their lauded recommendation engine, which got better the more customers used it and so helped Netflix retain subscribers.
The power of customer data goes a long way in explaining the rise of Disney+ and other direct-to-consumer (D2C) platforms. Information about user behavior and preferences will help those companies make decisions.
The story of Ranker and its release of Watchworthy shows how the broader entertainment industry's data evolution is far from complete.
"I didn't know there would be a data business in this when I first started," reflects Benson. But now, entirely new businesses have sprung from the information collected from Ranker visitors.
Earlier this year Benson hired David Yon to lead Ranker Insights, a new business unit aiming to use Ranker data to provide insight to entertainment businesses.
Watchworthy will be free for users, but will generate advertising revenue and referral fees from streaming platforms, Benson said.
Though there is already plenty to watch, such industrial ripples will continue to provide yet more content to keep an eye on.
Follow Sam Blake on Twitter and email him at samblake@dot.la
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