A Marketer’s Guide To The World Of AI And Machine Learning

Lori Mankin
3 mins
brain representing AI and machine learning

When we think of artificial intelligence, what is it we think of? Is it Siri knowing the exact answer to what we want when we yell a question into our phones? Is it the robot team on Madden playing sub-optimally when you put the difficulty level on easy?  Or is AI something different and ever-evolving that could be of major use to a marketing team?

One of the earliest proponents of artificial intelligence and machine learning was noted British computer scientist Alan Turing, who is widely considered to be the father of modern AI. He was years ahead of time when, during a lecture in 1947, he uttered the quote, “What we want is a machine that can learn from experience.” He further expanded on it, saying, “The possibility of letting the machine alter its own instructions provides the mechanism for this,” outlining the framework of machine learning.

So what exactly is AI and machine learning? And how can marketers use it to their advantage? Let’s explore a few ways that artificial intelligence and machine learning are changing the game in marketing and how marketing professionals can deploy it in their own programs.

A Deeper Dive Into AI and Machine Learning

Artificial intelligence refers to computers performing tasks that require intelligence when done by humans. In the software world, this example may be most prominent in the chatbots that appear at opportune times when you visit a company’s website and can’t seem to find what you’re looking for.

Machine learning is one aspect of AI. The idea behind machine learning is that a particular computer program can change how it responds to interactions with exposure to new data.

Think about the music you listen to on Spotify or your purchases on Amazon. Do you see that every time you purchase something, or listen to artist, there’s a recommendation engine on the side that lists similar things you might be interested in? That’s machine learning in action.

Now think about it from the marketing perspective. Say a customer clicks on various emails in a marketing funnel. Machine learning can help a CMO  figure out a customer’s buying process based on a particular promotional email sent a few days before.

But where do the concepts of AI and machine learning fit in when it comes to business?

Ray Wang, founder of Constellation Research developed a spectrum that can help marketers deliver the business value of AI.


Marketers should use this spectrum as a guide for how a marketing program can effectively deploy an AI solution. During the first portion, the “perception,” a marketer can understand what is going on when events are programmed manually. With additional manual input, the second circle, “notification,” gives alerts, signals, and other methods to deliver information. In the third circle, “suggestion,” the AI makes suggestions based on attributes that were given manually, along with past behaviors. When there is enough information where the AI is making suggestions, these suggestions can then be automated (number 4), with the AI ultimately being able to predict outcomes before they happen.

All this information allows those using AI to figure out what they should be avoiding based on the information given (six), with the final spectrum, situational awareness, giving the AI an almost human capability to make decisions.

So what does that look like when marketers put the AI plan into action?

  1. Suggestions based on buying patterns. With AI, marketers can detect consumer buying patterns, allowing them to figure out the ideal time to reach out in the prospect cycle. Seeing the data of buying patterns can also help marketers suggest other products a customer didn’t consider beforehand but that might be attractive to them based on past purchases.
  2. Leads routed to the right sales people. Sometimes, lead generation campaigns are botched because a lead goes to the wrong salesperson. Artificial intelligence within your marketing programs can analyze a lead and based on the data, send it to the right salesperson, increasing your company’s chances of closing a deal.
  3. Rapid data collection. Chatbots are collecting data on the front end and interacting with customers in the way that humans do, allowing marketers to focus on high level strategy.
  4. Greater visibility online. Machine learning, coupled with effective keywording, can help customers more easily find your product or service on Google.
  5. Optimization through segmentation. Marketers can segment customers based on data gathered from automated machine learning, helping to better optimize email and website communications.

It shouldn’t come as a shock to CMOs that AI continues to play a growing role in a marketer’s job duties. While AI won’t be taking the jobs of people on the marketing team, the fact is that those companies that seamlessly integrate AI and machine learning into their marketing programs will be able to find deeper customer insights and patterns within their data. That, in turn, will give them a leg up on their competitors, who are seeing data from a bird’s eye view.

The points is, don’t fear AI, embrace it.

February 24, 2017

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