How to Use Data to Drive Online Video Success
Ask any digital video publisher what its data strategy 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 interpretation, 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?
Our first stop on the data trail uses data to identify what content 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 stations to give them an affordable platform for distribution. Listeners from all over can tune in to hear locally produced content tailored to their interests. The result is data-driven content curated via a combination of machine learning and human assistance.
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 media delivery," Dube says. This testing has been a way for NPR to design features and content, and then test to see what resonates. 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 includes 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 nsertion into content driven by audience data. Accurate analysis of audience data is vital to keeping media companies on the right side of their audience, since irrelevant sponsorships can send listeners somewhere else.
Our next data point comes from the video 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 customers use the VHX dashboard to see information 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 platforms," according to Pugh.
Data is nothing more than useless numbers and meaningless statistics until you gain insight about what works. Black&Sexy TV found that push notifications and releasing content over the weekend both drove increased engagement. The media company is also very active on social media, constantly engaging with its audience.
Another optimization technique VHX publishers use is offering promo codes for discounts to specific customers. "We released 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 marketing sales tool to drive more subscriptions 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 subscribers already."
While Black&Sexy TV has identified the important items that drive their engagement, not all publishers are as focused on all of the distribution details as they should be. Pugh says VHX provides automated and human advice to all its publishers based on evaluation of customer data. "One [piece of advice] is a simple thing," Pugh says. "For SVOD, you need to upload content all the time. Some people 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.
While Vimeo is ensuring its publishers have the building blocks to create strong businesses, 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 morning 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 strategy." 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 insight by examining its licensing and user interface (UI) structure. The customer was a property 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 other 10%. That went completely against our standard 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 popular 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. Analysis of traffic showed that viewers started dropping off around 60% of the way through a program, 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 newspaper customers. At one, people were only logging on from 5:00 to 9:00 a.m. At the other property, 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 differentiator provided guidance for tweaks to programming 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 happening on the commute to promote content. That one single data point changes the way we speak to both of those companies."
Our next stop on the data trail looks at how data is used for licensing rights. "Because we are an acquisition and business development group, we use data to identify what content creators we want to reach out to," says Anthony Layser, content director at Dailymotion. The ad-supported user-generated content (UGC) platform uses tools from two companies, Tubular and Tableau, to help it make sense of its data. Tubular posts a daily report of what is trending on about 30 social media sites.
Merging Tubular's information with internal data allows Layser to build projected revenue models. "We can get a rough idea about what potential 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."