Go Big or Go Home: Deriving Value for Video from Big Data

Posted by piksel

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According to analyst firm IDC, the big data and analytics market will reach $125 billion worldwide in 2015. Neil Berry, EVP Commercial, EMEA at Piksel examines how value-based analytics is impacting the TV industry and the inhibitors for its wider adoption.

Big data is a perennial buzzword and it’s not surprising. In the TV industry broadcasters look longingly at the likes of Google and Facebook, who in just over a decade since launch have gone from start-ups to having combined revenues in excess of $70 billion, much of it founded on clever use of big data. While big data usage is still in its infancy in the TV industry, it’s definitely growing despite how challenging the current data applications appear to be.

It’s worth noting some big data fundamentals. The term is somewhat of a misnomer; big data is actually a catch-all for three slightly different data paradigms known as the three Vs. These are velocity, volume and variety; and in general having at least two of these factors at an extreme level can provide both a challenge but also potentially unlock an opportunity.

An example is always useful to ground this in the world of TV. Say for example as a broadcaster, one of your advertising customers want to know if its ad spot is effective. The traditional method is to look at the ratings of the program it sits within to gauge reach but this method is imprecise and does not actually reflect how the audience is reacting to that spot.

A big data solution to this challenge might be to instead gather all the remote control data from say 100,000 set top boxes when that advert is playing and analyze what users actually did. If a large percentage switched channels to surf the internet during the break, or worse, turned the volume down as the advert started, it might be time to think of a new creative or timeslot. This is a velocity and volume big data problem, as capturing and storing all this data from a large number of STBs can be tricky although not impossible. Yet this is just the beginning.

Imagine you then correlate this data set alongside your subscriber database and census information based on household and region. This adds additional variety into the big data mix allowing you as the broadcaster to deliver some really valuable insights for the advertiser. Piksel calls this approach of turning data into knowledge to enhance your offering, value-based analytics. Where value can truly be derived is through creating actionable intelligence about a user, their behavior and their preferences, to deliver tangible results from powering more targeted advertising insertion or programmatic advertising strategies, to enhancing the customer experience.

Another example of “insights” in action is during the content acquisition process. The refrain “are we paying too much for content?” can be quantified, especially in VoD environments, by looking at viewing behavior alongside subscriber habits and retention rates. Content which may at first glance appear to be low value may in fact attract and retain a core of affluent or specialist interest subscribers that are actually much more profitable over the longer term than “butterflies” that only subscribe to binge on high visibility but short duration episodic content.

The potential use cases within the TV industry for value-based analytics are numerous. The technology to gather data and analyze it is already in the marketplace but the fundamental challenge is the integration across devices, turning that data into actionable insights using data science analysis skills.

This is compounded by the massive surge in online video that has transformed TV. A new generation of software driven, technologies are often at odds with many of the core skills sets within the TV industry. Yet this is changing. A few innovative broadcasters, content owners and MSOs are increasingly building these skills sets up internally, but many more are turning to third party specialists to help kick start these transformative projects to better understand viewer behavior and use analytics as a strategic imperative.

This approach is allowing access to personalization technologies and content recommendation engines hosted in the cloud that are designed with the TV industry in mind. With time to market often the difference between a Google style success and an also-ran, the big data hype train is no longer just a speck in the distance.

In today’s competitive environment in it’s very clear that the consumer is in control. With so much competition and an increasingly fragmented content market, understanding how viewers consume your content with rich value-based analytical insights and personalization must become top priority if you are to thrive.

0704591-037-Neil-Berry(750x1050)Neil Berry leads commercial operations for Piksel across Europe, Middle East and Africa as EVP Commercial - EMEA. Neil plays a key role in providing consultation on Piksel’s unique business approach combining innovative technology with commercial strategy and managed services capabilities.

 

 

 

 

ORIGINALLY PUBLISHED BY INBROADCAST.

Topics: Insights, OTT, Analysis, Metadata, Value-based Analytics, Big Data, Data, OTT Service