content marketing AI

The Power of Content Marketing AI


If you are confused about how content marketing AI works, take some time to binge-watch your favorite shows on Netflix.

AI is a buzzword, but Netflix demonstrates its enormous potential. Each year, Netflix generates original content that continuously wins awards, even edging out HBO as the recipient of the most Emmy nominations. How do they do it? Because Netflix knows what you want to see before you even see it, explains Jared Loftus, chief operating officer at, an AI-powered newsletter platform that helps build relationships with subscribers by delivering personalized content.

Jared breaks down the power of content marketing AI in his session at Managing Editor Live 2020. For content marketers unsure about the future, he detailed what could be next.

What Content Marketers Can Learn From Netflix

You may think “House of Cards” was Netflix’s first foray into original content, but you would be wrong. The company dipped its toe in the original content pond with “Lilyhammer,” a series about a former New York gangster trying to start a new life in a remote part of Norway. The series helped Netflix learn several lessons about content production that are relevant to managing editors, Jared explains:

The Story Arc Drives the Length of the Show

An essential takeaway for content marketers here, too: Every content asset should fit the story being told.

Make All Episodes available at Once

For content marketers, that can mean understanding the value of their content archive and refreshing popular evergreen stories when needed.

Create Programming That Caters to Specific Interests

Content marketers who focus their content creation can develop large niche audiences. You don’t have to please everyone to build a valuable content portfolio.

High Production Value Attracts New Subscribers

People respond to quality. Netflix committed to two seasons of “House of Cards” for a reported $100 million. That investment turned them into an original content powerhouse.

Streaming allowed Netflix to analyze customer behavior. They were able to see what actors, directors and genres their customers were most interested in. The company was able to track when and how customers used the streaming service. Finally, the search data and browsing habits are used to develop new content for the service.

Producing content based on customer behavior -- rather than demographics -- gives Netflix an edge. “It really doesn’t matter if you are a 60-year-old woman or a 20-year-old man, because a 20-year-old man can watch ‘Say Yes to the Dress’ and a 60-year-old woman could watch ‘Hellboy,’” said Todd Yellin, Netflix’s vice president of product, to explain how the service knows customers better than they know themselves.

Using customer insights, Netflix was able to feel comfortable about its $100 million gamble on the American version of “House of Cards.” It knew that many users liked films from “The Social Network” director David Fincher and performances from Kevin Spacey before the #MeToo movement. The British version of “House of Cards” also did well enough on the platform that Netflix could have confidence that its original show would be popular with its users.

This level of insight is only possible through artificial intelligence. Netflix can personalize programming for nearly 182 million subscribers because it leverages AI, but not all AI systems are created equal.

What Is Content Marketing AI? Start with the Basics

Content marketers should know the basics about AI, Loftus says. Here are the three main concepts:

  • Artificial intelligence is any technique that enables computers to mimic human behavior. This broad definition encompasses the other two significant aspects of AI.
  • Machine learning is the ability to learn without being explicitly programmed. So instead of hard coding software routines with specific instructions to accomplish a particular task, machine learning is a way of training an algorithm so that it can learn. This training involves feeding vast amounts of data to the algorithm and allowing it to adjust and improve.
  • Deep learning is essentially machine learning plus experience. It uses algorithms to create artificial neural networks that can learn and make intelligent decisions on their own. Deep learning is an evolved form of machine learning.

"So with the emergence of the internet and the huge increase in the amount of digital information being generated, it's become much more feasible to do this machine learning because we can teach computers and machines how to do it all," Jared says. "And it'd be far more efficient to code them to think like human beings, then plug them into all of this information so that that can give it the experience to take it forward."

So how can marketers push their work forward with content marketing AI?

Leverage Content Marketing AI

AI is already all around us, from Alexa to Google Assistant to Siri. This everyday AI is powered by natural language processing, which is the automatic manipulation of natural language, such as speech and text, by software. Jared says that anyone can play around with IBM's Watson Natural Language Understanding to see the potential of natural language processing.

Natural language processing powered by AI can be applied to various content marketing assets, including websites, newsletters, online courses and events, to enhance their value. "One of the ways that we've applied AI and natural language processing to email is around this idea of being able to share content with people, but on an individual basis," Jared says. His company uses AI to analyze customer behavior and tags content to create personalized emails for their audiences.

It's early days for AI in content marketing, but managing editors need to decide whether they will embrace the technology's potential or ignore it, Jared says. The consequences of this decision could be significant. When it comes to AI, "do you want to be on the side of Netflix, or would you rather be closer to the side of Blockbuster?”

Watch Jared's full session here.

Tom Anderson is a senior content marketing consultant at Rep Cap and managing editor of Managing Editor magazine. His work has appeared in, Forbes, Kiplinger's Personal Finance, Money, Monocle and Wired. He was a 2008-09 Knight-Bagehot Fellow in Economics and Business Journalism at Columbia University. He was born in St. Louis, but his heart is in New York.


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