M+E Daily

By Robert Moss, Ph.D., Partner Technology Platforms, and Tim Padilla, Senior Manager Media & Entertainment, Optimity Advisors

When broadcast media companies go “over-the-top” (OTT), they transform their sales model from a business-to-business to a direct-to-consumer model where the viewers, not media buyers are the customers. While this transformation is an important part of today’s sales strategy, it creates a new set of realities that transforms the type and volume of accessible data.

All of these changes add up to one thing: media companies need to adopt advanced data management strategies when taking their organization OTT.

As traditional content creators like CBS and NBC go over-the-top, they are taking a big risk of biting the hand that feeds them. While traditional distribution channels have been an effective solution for years, these companies are making the transition in part because they believe it is crucial that they tap into the analytic value that OTT’s Big Data can provide.

OTT: Why big data matters

In the old world, broadcasters had minimal insight into the viewing behavior of individual customers, and there was no way to tailor personal viewing experiences. However, with the transition to OTT, media companies now have access to an explosion of user data.

For example, former HBO CIO Michael Gabriel told IDG Enterprise that with the launch of HBO Go and other direct-to-consumer initiatives, the amount of usage data increased a thousand-fold, growing from 2,500 rows a day to 2.5 million.

Similarly, one of Optimity’s media clients found that as it transitioned to a new online delivery platform, its hosting vendor was generating clickstream data of 10 billion rows per year. With effective strategy and execution, OTT broadcasters can mine these huge volumes of viewing data and use it to inform every part of the business—the development and purchasing of content, the delivery of that content and the marketing of it.

Content development

Big Data promises to revolutionize a media company’s ability to understand and shape the content it develops and licenses. With the move to OTT platforms, broadcasters suddenly have access to a wealth of detailed interactive data, which opens the door to a range of analytic approaches that were not possible before:

* “All the Data”: By analyzing aggregate data that comes from all of their consumers instead of a small sample, broadcasters get a complete view of the likes and dislikes of entire demo-graphic segments.

* Correlation Analysis: With a sufficient body of data and the proper analytic techniques, companies can identify the characteristics in a particular show or type of content that correlates with sales and viewer engagement.

* External Enrichment: With external sources like social media and Open Data, broadcast companies can access powerful new bodies of real-time viewer data.

These approaches enable previously unattainable views into channel analysis, detailed profiles of individual user preferences and the ability to mine the data to uncover meaningful insights. For example, Netflix CEO Reed Hastings is banking on the idea that the company’s access to online viewer data will allow it to be-come the next HBO-style content creator.

Content delivery

OTT flips the notion of linear channels on its head; in an online, on-demand model, viewers determine their own paths through a vast network of available choices. Recommendation engines can leverage user behavior data to create tailored suggestions that ensure the viewer stays engaged and comes back for more. These same viewer profiles can be used to personalize the viewing experience—including the all-important ad placement and delivery optimization.

Marketing and advertising

In the digital economy, every tweet and post is a potential lead generator, and it becomes possible to directly tie individual clicks and the sales they generate back to the marketing campaign that initiated them.

Analytics can reveal the optimal days and times for each type of mes-sage and the optimal frequency and number of touches to maximize click-throughs.

In an OTT world, data is an integral part of advertising. Cable providers like Time Warner have already started making inroads into cross-platform data analytics, merging infor-mation from cable set-top-boxes (STB) with data from online solutions, video-on-demand and interactive television. This analysis allows them to identify the best networks to use to reach their target audiences so they can better place their own ads for on-demand content as well as optimize rate cards for their advertisers.

But this sort of analysis is only a drop in the bucket compared to the data that online streaming platforms offer to OTT content distributors. A typical cable STB generates between 50 and 100 raw events per day, but the apps on Netflix’s streaming platform collectively emit more than 1.5 million events per second during peak hours. Locked away in the tens of billions of events generated per day is an immense potential for understanding the finest nuances of viewer behavior. Getting started with Big Data can be a daunting task. However, there are a few rules of thumb that can get you off on the right foot.

Think big, start small
As with any technology initiative, media companies diving into Big Data for the first time face the risk that, in trying to do too much, they end up doing nothing at all. Instead of trying to create the ultimate analytic play-ground, consider one or two focused, clearly defined initiatives that will get your teams up to speed with new technologies and approach-es, and will allow them to create something useful in a matter of weeks.

Start with problems, then apply technology
Too often, we want to start by selecting the most powerful or most innovative technology and then try to figure out what we might do with it. A better approach is to start with the problems you need to solve and then select the tool best suited to solving them.

Data is precious
Even if you are starting small, the harvesting and retention of as much data as possible is key, even if you don’t yet know exactly how you are going to use it.

Part of the beauty of Big Data technologies like Hadoop and document-oriented databases is that you don’t necessarily need to understand the full structure of the data to be able to store it. So, take advantage of that power and be data greedy now: it will pay off down the road.

Use your existing structures
Existing data sets such as IP records, master data and descriptive metadata can be the keys to understanding the vast amounts of data being collected and stored.

Master data management (MDM) initiatives are in their second and third generations and the ability to use this structure to “connect the dots” between your Big Data and hidden insights should not be ignored.

Keep privacy and security in the foreground
As media companies gather detailed consumer data, the prospect increases that there will be a legislative push to implement stricter privacy regulations, especially as they relate to marketing activity and global presence.

As the amount of data collected and the sources from which it is collected grow, it becomes all the more important to monitor and control who has access to that information and how it is being used. Enterprise-strength security must be baked into each and every initiative to protect companies from the risk of regulation changes and data security breaches.

The road ahead
Most media companies are just getting started on their journey into the new world of OTT programming. The key thing to remember is this: we’re still in the very early stages, and no one really knows how all that data will end up being used in the long term.

At this stage there is no one single proven approach or set of technologies for tapping into the value of this data, but all the companies getting in the OTT game are now working to figure it out, and those that do stand to have a considerable competitive advantage over their less data-driven peers. It is, in short, a very different world today for media companies, and the ability to manage data is not just a technology problem.

As media companies go OTT and transform themselves into data-driven enterprises, the use of Big Data is no longer a supporting function but rather a mission-critical component of their overall operations and must be supported as a core competency. You can’t run a 21st century broadcast media business that isn’t founded on data.

For many media companies, that’s the entire reason they are going over-the-top in the first place.

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Robert Moss leads the Technology Platforms practice at Optimity Advisors. He helps organizations understand and adapt to the new technologies that are disrupting traditional business models. Tim Padilla leads the Media & Entertainment practice at Optimity Advisors. He helps clients with strategy through implementation of wide-ranging technology, data and organizational initiatives.