Monetizing Content with Watson

Yesterday, I shared the first of three blogs based on my conversation about Watson with a CEO in the media & entertainment industry Watson Will Become Our Digital Self

In today's conversation, we continue to answer his key questions:

1. What is real and what is hype?
2. How can Watson help monetize our content?
3. How do we train Watson?

Debi: At the Master's, Watson helped the editors create highlight reels based on recognition of the crowd's excitement along with celebrity facial recognition, the sportscasters voice and other images in each frame. So, let's address your question: "How can a media company monetize its content with Watson?"

CEO: Yes, I can see how Watson will save our editors time in the cutting room so they can focus on more creative tasks but we can't keep up with the content we've already produced.

Debi: I get it. The real monetization opportunity will come from a better understanding of what's in your archive so we can match clips and highlights to highly targeted audiences, even an audience of 1. Watson is really good at audience insights where we collect social media and 3rd party data to understand each viewer's behavior, sentiment and preferences. Watson has an API for personality insights based on a social media profile and marketers are using personality targeting to develop highly personalized campaigns.

CEO: Are you saying that our content will find the right audience vs. having the audience search for our content?

Debi: Absolutely. Now, let's talk about the weather....?? We're starting to see that weather influences demand for media, products, services and indoor/outdoor activities. In fact, weather influences just about everything. We're really excited about Watson's integration with The Weather Channel. So, let's think about how you can use local weather to trigger an ad for example, a convertible on a sunny, Spring day or a movie theater when it's cold and dreary.

Our data scientists have demonstrated significant improvement in conversion rates when we match content to audience to weather and other factors. In fact, one national retailer was able to improve inventory predictions at the local SKU level using Watson and weather insights.

CEO: I'd be interested in Watson to help us improve our advertiser's KPIs. I'd like to help them create TV ads that are highly relevant to our audience and improve our attribution models.

Debi: There's a world of possibilities but we can start small with a pilot to prove the return on investment by improving the return on advertising for your customers.

Let’s talk more about "Training Watson" in tomorrow’s blog at Linked In / DebiStackIBM and I hope to see you at NAB for the Digital Futures Exchange session where I'll be speaking about Artificial Intelligence and Bots.

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