Three Fundamental Changes in TV Measurement. Interview with Ashish Thusoo, CEO and Co-Founder, Qubole

Ashish Thusoo, CEO and Co-Founder Qubole previously ran Facebook’s Data Infrastructure team.  “Facebook was one of the earliest companies to capitalize on big data, and I had the privilege of having a front row seat to its transformation into a data-driven company’” he explains. “I was also the co-author of the Apache Hive Project, and helped drive the creation of several tools, technology and templates that are still used today,” he added. He founded Qubole in 2011 taking what he learned at Facebook about creating an open data infrastructure and applying to the public cloud. 

Charlene Weisler: From your perspective, how has TV measurement changed over the past few years?

Ashish Thusoo: The world of television has experienced three fundamental changes over the last few years. First, TV has become digital. With analog TV, there was no way to know if a viewer was watching the program unless you asked them. In today’s world, you know who is watching, what they are watching, how long they are watching, and how they are behaving, which means the types of things you can measure has grown exponentially.

Second, TV has gone multi-channel. 50 years ago there were less than 10 television stations, meaning there were only a handful of things to watch at any given time. These days there are an infinite set of distributors and broadcasters, so viewers can watch content through cable TV, stream through subscription video on demand services such as Netflix or Hulu, or access websites and apps like YouTube and Snapchat. In addition, there are endless ways to watch television, whether it’s on a TV, laptop, iPad or mobile device. And they can consume on multiple devices simultaneously.  This variety creates endless ways to measure video consumption, but also creates challenges. 

Finally, it’s not just about TV - you can correlate web, social and offline behavior to build an even more complete profile of each viewer.  Those three changes have led to an explosion of data and increasing complexity about how to create meaningful measurement. While companies have new opportunities to collect data, the challenge now becomes how to get value out of it. 

Charlene Weisler: Tell me about Qubole and where it sits in the TV measurement world.

Ashish Thusoo: We provide big data-as-a-service, meaning we help organizations in the media, advertising, gaming, e-commerce, TV and entertainment industries turn their data into business insights. Our cloud-based platform, Qubole Data Service (QDS), runs on public clouds such as AWS, Azure, Oracle and Google Cloud Platform, and addresses the challenges of processing huge volumes of structured and unstructured data. For instance, our solution helps companies process all the data collected by tracking and analyzing consumers’ consumption of video content. 

Charlene Weisler: Are you able to help develop new metrics for TV measurement?

Ashish Thusoo: In the past, TV viewership was measured on historical information. This evolved into real-time measurement, as advertisers and distributors could find out who exactly was watching a show on a real-time basis. The next measurement for TV will be predictive. Not only can you learn historical and real-time information about a viewer, you’ll be able to predict what he or she will watch next. 

Charlene Weisler: Where do you see the data in the TV ecosystem today and what role do you see it playing 3-5 years from now?

Ashish Thusoo:  In the next few years, technology will emerge that can determine precisely who is watching something - through biometric face recognition or eyeball tracking. The challenge today is that media companies aren’t able to know 100% for certain who is watching something. A middle-aged father, for example, may watch the first half of a football game in the living room, but then leave to make dinner and his young son watches the second half without him. And yet, the same commercials will play during the son and father’s separate viewing experiences, although they aren’t relevant to both of them. Biometric tracking could be something we see as a tool for the media to know precisely who is watching something and optimize his or her experience.

Additionally, we’ll see the creation of hyper-personalized viewing experiences by combining a user’s past, real-time and predictive experiences. For instance, predictive analytics will anticipate when a consumer will prefer to watch a commercial and then change a consumer’s viewing experience in real-time.

This article first appeared in www.Mediapost.com

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