This week, Marketing Smarts host Kerry O'Shea Gorgone has swapped podcast hosting duties with John J. Wall of the Marketing Over Coffee podcast on the occasion of April Fool's Day! As John and his guest, Christopher S. Penn, discuss on this episode, they've been working with MarketingProfs and attending MarketingProfs events for more than 10 years.

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John and his Marketing Over Coffee co-host Chris discuss the five most effective applications of artificial intelligence and machine-learning for marketing.

Along the way, John and Chris touch on the risks of not extracting your data, explain why social media analytics leave a lot to be desired, offer valuable insight into which platform's influencers are more engaging, and so much more.

For example, Instagram influencers are 72x more engaging than Facebook influencers, according to the 2019 Social Media Influencer Benchmarks report from Trust Insights.

The number of hashtags you use has no impact on audience growth or engagement. Trust Insights looked at 12 million social posts on Facebook, Twitter, and Instagram; counted the number of hashtags in those posts; then ran an analysis and found that hashtags don't help you or hurt you. They're just there.

"From a user perspective," explains Chris, "if you're going to hit the search box on Instagram, you're going to search for the word. You use normal, natural language." Except for things like events, people probably aren't going to search for a hashtag, so don't concern yourself with packing social posts full of hashtags.

Be sure to listen to the full episode, because John and Chris dive into topics like the power of predictive analytics to get you out of "reactive mode marketing," and a full explanation of "the 5 U's"—the five most effective applications of artificial intelligence machine learning for marketing:

  1. Untapped: Marketers are swimming in data, from social media and Web analytics to marketing automation, CRM, and customer service information. The trouble is, it's all siloed, so much of it remains untapped by marketers.
  2. Unknown: One of the things that's so difficult about influencer marketing is that the analytics around influencer marketing are universally terrible. There aren't that many qualified data scientists who can provide the knowledge needed to map out influence. A high-quality assessment of influence using machine-learning will take a little more time (say 20 or 30 minutes versus a few seconds), but you will get much better insight into who is truly influential in your space.
  3. Unclear: In some instances, you just don't know what's going on. You know the data's good, but you're not sure what to do with it.
  4. Unfocused: What should you be doing more or less of? Marketers have too much data they don't know how to analyze. Machine learning algorithms can help you analyze all that data and figure out what to focus on.
  5. Unprepared: The role of predictive analytics, using AI and machine-learning to get a sense of what's coming. What is likely to happen? Human behavior is fairly predictable. Using this type of data, marketers can prepare for upcoming events.

    NOTE: Predictive analytics was the No. 2 most interesting application of AI in the most recent CMO Survey from Duke University School of Business.

To hear more from John and Chris, visit or follow them on Twitter: @johnjwall and @cspenn, and be sure to get your copy of Chris’s book AI For Marketers: An Introduction and Primer: Second Edition as well as The Marketing Over Coffee Playbook.

Be sure to listen to the entire show, which you can do above, or download the mp3 and listen at your convenience. Of course, you can also subscribe to the Marketing Smarts podcast in iTunes or via RSS and never miss an episode!

This episode brought to you by GoToWebinar:

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Music credit: Noam Weinstein.

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