As part of the AI Academy for Marketers membership, we offer monthly Ask Me Anything (AMA) sessions with leading industry experts. We chat about everything from technology trends, use cases, lessons learned, to much more.
This post offers an inside look into the latest, exclusive members-only session with Jim Sterne (@jimsterne), President, Target Marketing of Santa Barbara. During the session, we discussed the benefits of machine learning—all questions stemming from his course and certification offered in the AI Academy for Marketers (listed below).
Below is a quick video from our chat, followed by top takeaways from the conversation.
Can you give us a snapshot of machine learning at a very basic level?
Machine learning looks at the data and creates the model. If you change the data, it changes the model. Once you understand it’s not magic, and it’s just software, then the question becomes: what is it good at? It’s good at sorting and manipulating data. So solving for practical applications is the next step! Understand where to use it. The fun part is solving for the question: what kind of new problems can we solve now with machine learning?
Will marketers always have a job?
Yes. Main reason being: The marketer tells the machine what to do. And the marketer decides what data the machine will look at. Then the marketer ensures that the results make sense. The human decides that, not the machine.
When should you use machine learning?
If you have a small data set, look at it yourself. If it’s a lot of data, use statistical analysis. If it’s an enormous amount, get the machine to look at it for us. And a bonus: The machine is building the model built on JUST the data; there is no human bias.
What are the best books for getting your team introduced to machine learning?
Jim suggests his book Artificial Intelligence for Marketing: Practical Applications as a good starting point. Then, read 3 more books that offer different levels of depth for technology or math. When you read a variety you get different perspectives. Other good books to start with: Prediction Machines: The Simple Economics of Artificial Intelligence or Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die.
What remains uniquely human?
Creativity and thinking outside the box. The human mind takes its experience and applies it to different subjects. You might be going on a run, and suddenly ideas hit you. The machine doesn’t do that! Also, collaboration is a big one. People get in one room to solve a problem, have differing perspectives, and that’s powerful.
How can we get more collaboration around the data?
Know your data and what is available. Ask yourself: What might exist that other people aren’t aware of? Build that pipeline. In a large enterprise, you probably have a data science team. They probably aren’t looking at marketing problems. Make sure they understand the problem you need to solve. You can improve SEO with the right data, for example. Go to the people in power, and say: I have some data that I think could help you. With business goals in mind, show them you have data that can help and you become a trusted advisor.
Who’s role is maintaining that data that needs to be cleaned?
The data engineer. And what about the marketer’s role? If marketing is curious about data and becomes more knowledgeable about it, they become more valuable.
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Sandie Young was formerly the Director of Marketing at Ready North. She started at the agency during the summer of 2012, with experience in magazine journalism and a passion for content marketing. Sandie is a graduate of Ohio University, with a Bachelor of Science from the E.W. Scripps School of Journalism.