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Delivering Smarter Customer Experiences in Media & Entertainment

May 30, 2013

If there is one thing that I love about my job, it’s engaging in fascinating conversations with like-minded individuals who fully understand and embrace the possibilities that advanced, predictive analytics brings to the table. It might sound corny, but I mean it. It’s like watching kids explore a toy store as they suddenly find the “tools” they need to bring their imaginations to life.

I see the same type of excitement and enthusiasm brewing across a wide variety of Media & Entertainment companies around the world.

For example, I was on a conference call this morning with a Director of Data Warehouse & BI Technologies at a global media and marketing company, involved in digital and print publishing, television broadcasting, brand licensing and much, much more. I could immediately tell that he’s determined to keep moving forward along the big data path to delivering smarter customer experiences. He’s got a solid vision for creating win-win scenarios of transforming audience insights into advertising and content relevance. And while so many others struggle to find a decent starting point, he clearly understands exactly where he is now and where he wants to go.

How so? He’s past dreaming about the possibilities and now he’s actually playing in the sandbox to see what he can do. He’s getting his hands on the tools and technology he wants, and he’s willing to think big but take small steps as he works toward positioning up in the journey to enhanced customer analytics.

The fact is that M&E has always been a “content centric” industry. They created the content and controlled the distribution windows and venues where that content was consumed by customers. However, in today’s age of digital mobility, consumers want what they want when and where they want it… which could literally be anywhere at any time on any device. This dynamic shift in consumer viewing behavior has forced a change across the industry to embrace a “consumer centric” model.

Where we used to say that “Content is King,” we can now argue that the “Consumer Audience is King and the Content is the Castle we must build around them.”

With access to vast and various data sources, media companies are striving to build closer relationships with their customers at a level where they can finally understand them as individuals. New big data and predictive analytics capabilities allow them to analyze customer and behavioral data – simultaneously – to create detailed, highly personalized customer profiles.

This new type of integrated insight allows them to: identify and deliver targeted offers, dramatically improve campaign performance, recommend content in real-time, and develop content to satisfy and delight audiences. To get there, data-driven M&E companies are taking full advantage of next-generation audience insights platforms that enable a specific set of use cases to drive new capabilities and business value. They are as follows: (but I’d love to know if you’d add or subtract use cases from this list. Let me know in the comments below.)

  1. Multi-Platform Viewing: quickly measure a TV show’s performance (or the performance of similarly delivered content) across linear and digital platforms.
  2. Audience Composition & Indexing: Identify specific audience segments or audience attributes across different TV shows.
  3. Audience Engagement & Targeting: (this one is KEY – I’ll explain later) Identify existing fans, target new prospects, analyze engagement across TV shows.
  4. Social Sentiment Analysis: (this is a good place to START) Analyze social conversations to understand audience sentiment across TV shows.
  5. Social Sentiment Trending & Correlation: Analyze and correlate social trends to TV show performance (views, ratings, etc.)
  6. Social Media Indexing and Visualization: Explore (browse, search) extracted social media postings about TV shows.

The reason I point out #3 as being a key use case for audience insights is because this is where M&E companies that are committed to delivering those smarter experiences we talked about earlier can use all of the available data across a consolidated big data platform. That means you’ve got the technology and the horsepower required to unify and utilize advanced data warehouses, streams processing, predictive analytics, data visualization tools and multi-channel marketing campaign management.

Now, I know what you’re thinking and I feel the same way: “Oh my god, that sounds awesome!”

The fact is that you’re already dealing with a massive amount of data. Data at rest. Data in motion. Linear and non-linear viewing data. Subscription data. Demographic and 3rd party data. And, of course, social media data. I’m sure the list goes on and on and on.

Once you have identified all your sources (that once were siloed and now must be shared), you can extract entity profile information and influence from social and non-social data and perform entity integration to create individual profiles. Next, it’s time to develop models to predict buying propensity, influence, fan engagement, fan type, churn rate, etc. Finally, you can create prospect lists that are based on predictive models to produce targeted marketing campaigns that deliver – say it with me – the right message to the right person at the right time for the right price.

In one instance, IBM helped a US cable provider deploy powerful analytics to understand the viewing habits of more than 100,000 DVR subscribers. They needed a way to analyze and understand the vast amounts of viewer data generated by a new cloud-based DVR infrastructure. The company now uses sophisticated analytics to analyze behavioral data collected from subscriber DVR devices. Predictive models help them identify the most popular programs and networks among various demographics at different times of day—and even identify individual habits to enable targeted advertising.

Sophisticated analysis on viewership data has changed the way this cable provider approaches advertisers and content providers, putting it in a much stronger negotiating position.

It’s OK. You can say it again: “Oh my god, that sounds awesome!”

 

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