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53STREAMINGMEDIA.COM

Along the Data Trail By Nadine Krefetz

From content creation to subscriber retention,

video publishers are embracing Big Data in a big way.

52 STREAMING MEDIA September 2016

Ask any digital video publisher what its data strate-gy is, and you’ll likely get an answer ranging from, “We’re a highly tuned data-driven organization,” to, “Well, we collect a lot of it, but don’t really know what to do with it.” Without solid analysis and inter-pretation, data is useless. So what kind of data is

most valuable to streaming publishers, and how can they gain insights and generate outcomes from the data they collect?

Audience ProfilingOur first stop on the data trail uses data to identify what con-

tent the audience wants. Nonprofit broadcaster NPR collects data to deepen the relationships between stations, sponsors, and listeners. NPR comprises member radio stations all around the country, and it delivers personalized content through the NPR One app, which promises listeners, “Public radio made personal.”

How do you make content personal? “The location of the end user is of great importance because it helps us to target not only which member station they’re affiliated with, but also localized content that we would push to them,” says Michael Dube, head of streaming media at NPR.

NPR developed the app and made it available for local sta-tions to give them an affordable platform for distribution. Listen-ers from all over can tune in to hear locally produced content tailored to their interests. The result is data-driven content cu-rated via a combination of machine learning and human assis-tance. For deeper recommendations, listeners have the option to identify themselves and have their likes and dislikes tracked.

“We do a tremendous amount of A/B testing around our me-dia delivery,” Dube says. This testing has been a way for NPR to design features and content, and then test to see what res-onates. For example, if a user chooses not to listen to politics, then the app won’t deliver political news to them, although it may present a piece that has a wider subject matter and in-cludes political content.

“We’re creating personalized and dynamic experiences,” says Dube. Content is commonly 2–5 minutes long, with longer shows occasionally divided into short clips. The average unique session on the NPR One app is 40 minutes, which suggests its curation formula works well.

NPR stations raise funds from local listeners as well as sponsorships placed within the programming, and NPR’s data helps them attract more sponsors. “Big Data is very important, because the more people are consuming our content, the more opportunities we have to include our sponsors within those deliveries,” says Dube. The organization is selective about the types of sponsors it works with, and it uses its own ad network to perform dynamic sponsorship insertion into content driven by audience data. Accurate analysis of audience data is vital to keeping media companies on the right side of their audi-ence, since irrelevant sponsorships can send listeners some-where else.

Along the Data Trail


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Our next data point comes from the vid-eo platform’s perspective. Vimeo’s VHX subscription video-on-demand (SVOD) platform provides media companies with the technology they need to sell and serve subscription content. Vimeo’s media cus-tomers use the VHX dashboard to see in-formation about viewer conversion rate and location, along with which platform is driving the most traffic. This data helps their media customers create stronger businesses.

“One of the biggest things we’ve been rolling out this year is our branded apps on every device,” says Casey Pugh, co-founder and head of product at VHX. “That data [collected via app use] helps sellers place their marketing dollars in the right place to reach customers.” VHX’s top SVOD seller is Black&Sexy TV, which bills itself as “the leading network for young and progressive black people since 2008.” “It has some of the best conversion on the entire platform. It has niche comedy and drama series which you don’t typically find on any other plat-forms,” according to Pugh.

Data is nothing more than useless num-bers and meaningless statistics until you gain insight about what works. Black&Sexy TV found that push notifications and releas-ing content over the weekend both drove increased engagement. The media compa-ny is also very active on social media, con-stantly engaging with its audience.

Another optimization technique VHX publishers use is offering promo codes for discounts to specific customers. “We re-leased this new tool that allows sellers to create a promotional code to give out to the customer to get, for example, 30% off their subscription,” says Pugh. “It’s a mar-keting sales tool to drive more subscrip-tions by creating a lower barrier to entry and increase conversion. Black&Sexy TV has rolled out the promo feature, which has shown significant increase in subscrib-ers already.”

While Black&Sexy TV has identified the important items that drive their engage-ment, not all publishers are as focused on all of the distribution details as they should be. Pugh says VHX provides automated and

Vimeo’s VHX SVOD platform offers a dashboard that lets publishers analyze their data based on (from top to bottom) products, subscribers, and traffic.


human advice to all its publishers based on eval-uation of customer data. “One [piece of advice] is a simple thing,” Pugh says. “For SVOD, you need to upload content all the time. Some peo-ple forget to do it, and they are slowly churning customers.” It seems obvious, but analytics can drive decisions about putting up new content, finding the right time to publish the content, and making sure viewers know about new offerings.

Optimizing StrategyWhile Vimeo is ensuring its publishers have

the building blocks to create strong business-es, Ooyala is providing strategy optimization to its customers through its data insights. “I come from the world of TV. When we had a new show come out we had to wait till 9:00 the next morn-ing to hear how viewers had reacted to that show,” says Steve Langdon, global director of the strategic media consulting group at Ooyala. “Now, publishers can see all sorts of details and immediately make changes to their video strat-egy.” Langdon outlined a few examples where data has allowed publishers to uncover valuable information to optimize their businesses.

In the first scenario, a publisher gained in-sight by examining its licensing and user inter-face (UI) structure. The customer was a proper-ty delivering kids’ content. “Their viewing data showed episode one of each of their TV shows was getting about 90% of the overall views, and episodes two through 10 were getting the oth-er 10%. That went completely against our stan-dard analysis of SVOD,” says Langdon. “The reason for that is children enjoy the repetition.”

The insight meant the publisher could ask itself if it actually needed to buy a whole series or just the first episode of about 40 different series.

In the next scenario, Arsenal Media Group, the media property associated with the popu-lar English football club, wanted to find a way to gain longer engagement periods and reduce what it calls the one-video bounce—viewers who watch a piece of content and then leave. Analy-sis of traffic showed that viewers started drop-ping off around 60% of the way through a pro-gram, so Arsenal decided to run a thumbnail saying which video was coming up next. “You would never see an episode of Downton Abbey finish on a commercial network and then the screen goes to black,” says Langdon.

The last scenario shows the importance of context. In this case, Ooyala had two newspa-per customers. At one, people were only log-ging on from 5:00 to 9:00 a.m. At the other prop-erty, viewers were checking in at various points during the day, with the peak between 5:00 to 7:00 p.m. The overall traffic numbers showed one peak period, but the exact content viewing time showed peaks and valleys. This key differ-entiator provided guidance for tweaks to pro-gramming strategy for each publisher.

“The result is the first publication can go about informing its viewers that there are lots more videos to be watched in the afternoon and the evening,” says Langdon. “For the other company, it’s about how do you maximize what’s happen-ing on the commute to promote content. That one single data point changes the way we speak to both of those companies.”

Analyzing TrendsOur next stop on the data trail

looks at how data is used for li-censing rights. “Because we are an acquisition and business de-velopment group, we use data to identify what content creators we want to reach out to,” says An-thony Layser, content director at Dailymotion. The ad-supported user-generated content (UGC) platform uses tools from two com-panies, Tubular and Tableau, to help it make sense of its data. Tubular posts a daily report of what is trending on about 30 so-cial media sites.

Dailymotion uses data from third-party

providers such a Tubular and Tableau

to determine what content might do

well on its platform.


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data allows Layser to build projected revenue models. “We can get a rough idea about what po-tential revenue might look like if we were able to acquire that partner’s content on our platform,” says Layser. “If there’s a content manager who is managing sports, they can see what sports- related accounts [on Tubular] were popular last week from a traffic standpoint.”

If you need to analyze data for thousands of content partners, finding good tools becomes key to your business. Layser uses Tableau to help see and understand trends. “When you have a partnership you’re handling that has many doz-ens of channels, you need some centralized loca-tion where you can categorize and manipulate data to get a clear understanding about how the partnership is performing,” says Layser. “For example, I have over 800 Fullscreen accounts on the platform. If I want to see how all those accounts are performing collectively from a revenue standpoint or from a traffic standpoint, Tableau allows us to easily arrange that data.”

On the partner side, Dailymotion offers two types of measurement tools. “The traffic dash-board is a lot of view data—minutes watched, geography, what the audience retention is, per-cent of video watched, domain breakdown [for embedded content], and traffic sources,” says Layser. “The revenue dashboard is a day-by-day breakdown of impressions, average CPM [cost per thousand], and estimated revenue per day.”

Partners with content on multiple platforms such as Dailymotion, YouTube, and go90 need to be able to grab the data from their partners and crunch the numbers themselves, says Lay-ser. “It’s really important to them to be able to export spreadsheets from our dashboards to a CSV file and drop them into a centralized database [so they can compare how activity does on different locations], rather than hav-ing to manually see something in a dashboard and have an intern actually trying to create a spreadsheet,” he says.

This brings up two very important points. First, the manual handling of data easily allows errors to be introduced. Second, standardized metrics are critical, so publishers can compare apples with apples.

Data-Driven CreativeOur next media company is going data first

when it comes to designing content. Whistle

Sports’ focus is providing content to young mil-lennial sport fans. “The truth is, sports happens billions of times a day in backyards, in parking lots, in playgrounds, in practice fields, some-times even in office buildings, and that can be at least as compelling as that live sporting event if you aggregate it,” says Brian Selander, EVP at Whistle Sports. Viewers are highly en-gaged by this content, so Whistle Sports is able to monetize it not by selling ads but by finding sponsors. This is the latest approach brands, sports leagues, and media companies are tak-ing to combat ad backlash and ad blockers.

Competing with live content can be challeng-ing, but Whistle Sports is creating evergreen branded entertainment. “If you’re a brand or agency and the content you’ve created with us can be rediscovered in a month or 6 months and be as interesting to somebody, that’s an invest-ment that pays off repeatedly,” says Selander. “This means it’s important to figure out what’s going to work before you make it. Sports that re-ally engages young millennial audiences needs to be research and insight first, content second.”

So far, Whistle Sports’ insight has proved successful. Since its launch in January 2014, it has attracted 190 million followers in the 14–32 age range across all social platforms, and it attracts 2 million new followers a week. The company has approximately 400 content part-ners, such as Dude Perfect, a group of enter-taining guys broadcasting a reality show, sport-ing event, and long-form commercial all rolled into one.

“I’ll often say at conferences, we need to lib-erate brands and agencies from the tyranny of the view count,” says Selander. “I think partic-ularly in the digital space, people remain hung up on how many views something gets and are less concerned about the more important num-ber, which is how engaging this content is and how often people are actively sharing it.

“Before we bring any creator into the envi-ronment we take a hard look at the data around their engagement, their viewability, and their scalability. We are data-driven from the begin-ning of any decisions,” says Selander. “We get hundreds of millions of data points a month from interactions between creators, content, and fans that we analyze to see what works best.”

Whistle Sports looks at data points like what time of day content is viewed, what brand inte-gration is connecting most strongly, and what


words in the video description may make view-ers more likely to engage with content. All sto-ries are crafted based on the insight Whistle Sports gains from its persistent focus on trans-lating data into valuable analytics. “We may fol-low a particular video minute-by-minute after it launches, and we can also have insight across the network on an hour-by-hour basis,” says Selander. “Then at the end of the month we can compile that to see if there are any emerging trends we might not have seen if we were too in the forest and not standing outside of it. Media has always been data-driven; it’s just the imme-diacy and levels on which that feedback hap-pens are now far more connected.”

You Might Also Like …While Whistle Sports is experiencing great

success curating its viewers’ experiences, our next company is there to help when you want to watch something, but you’re faced with too many choices.

Most of the major TV Everywhere (TVE) pro-viders use tools from Digitalsmiths to identify trends and build on user preferences. “The old Amazon model is, ‘This show is similar to these three things, so you might be interested,’” says Bil-ly Purser, VP of marketing at Digitalsmiths. “We take into consideration what that person typical-ly watches, on what type of device, at a partic-ular time, then make sure it’s blended into the recommendation.” The number of data sources on which Digitalsmiths bases its analytics varies from 10 to a couple thousand pieces of informa-tion, including scheduling data, what’s on now, what’s available to a subscriber, third-party crit-ics’ ratings, popularity, type of content, mobile location, and device type.

How do you make sense of thousands of piec-es of information? Digitalsmiths does multi-variate A/B testing, which is testing 60, 70, or 80 variables to identify which UI, features, or pro-motional campaigns have the best reception. It’s like A/B testing on steroids. A/B testing typically


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of a change to that variable. With multivariate testing, several variables can be tested together to uncover the best combinations.

This type of testing helps providers seg-ment subscribers to ensure the right audience is receiving the best recommendations. “I think where the market is going is segmenting the ap-propriate audience from a promotional stand-point and being able to leverage data to drive more viewership, more engagement, [and] more revenue,” says Purser. “The Holy Grail is to de-liver a really personalized offering so all the rec-ommendations are unique to the person or the group that’s in the room.”

Measurement as a Platform?Moving from the TVE world to the other end

of the spectrum brings us back to Tubular. Tu-bular publishes daily rankings of content on the top advertiser-supported video platforms in-cluding Facebook, YouTube, Vine, AOL, Yahoo, and Twitter. Tubular has about 120 enterprise subscribers, and it offers a free version.

“People use data for content strategy, for sales support, for media planning, for executive reporting, for identifying influencers,” says Al-lison Stern, co-founder and VP of marketing at Tubular. “There are a lot of different ways to use that intelligence layer, but it all [goes] back to being data-driven and using data to inform your content, promotion, and distri-bution decisions.”

Tubular’s data enables com-panies to track their own or competitors’ content and see what is trending by views and engagement metrics. “If you are Scripps and you’re track-ing food content, you can have a dashboard that shows you what are the trends in food, what food videos are taking off on what platforms,” says Stern. “It can [answer the question], ‘How is Tasty doing?’ Or, ‘How is TipHero or Tastemade or all these other food channels doing in comparison to your food channels?’ You can get a feel for how engaging your content is benchmarked across the universe.”

Ranking results gives publishers an idea of best practices they should follow to see, for in-stance, what production style drives higher en-gagements. “For food videos right now, there’s a lot of stop motion that makes the recipe in 10 different steps where it’s pictures of the food, not of the person making it. In news, there are videos that have a lot of text because in Face-book the sound is off.”

Driving Revenue From DataThe takeaway from the experts varies ac-

cording to the business model, but there are three keys to making data drive revenue: Un-derstand what the high value questions are, monitor the data that gives you answers, and gather insight and identify how to respond. Ev-eryone wants higher engagement rates with their content, whether they are ad-supported or subscription-based. Some media companies need their data to tell them when to deliver and market new content, while others look at their content’s engagement levels to see exactly what resonates with the audience. In each example, the experts tested what they were doing and tracked whether their ideas resonated or were something they should revise.

While our data trail ends here, the world of Big Data is only just beginning to impact vid-eo. Content creators and publishers need to find ways to integrate it into their businesses.

Tubular publishes daily rankings of content on the top ad-supported video platforms.