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Artificial Intelligence and Marketing: A Roundup

August 2, 2020   By William Sepesi

Forget the hype cycle, Artificial Intelligence is starting to change marketing


This list and the write up was done by our summer research associate, William Sepesi. William is studying Computer Science with a focus on Artificial Intelligence at Washington University in St. Louis.

While there have been some pretty breathless predictions about the role artificial intelligence will play in the future of marketing, we believe we’re still in the relatively early part of the hype cycle. Here’s a roundup of articles that can help you get comfortable with the jargon and the concepts that are driving the growth of advanced marketing technology.

Must Read/Start Here:

IAB Report: Artificial Intelligence in Marketing  – A very detailed report from IAB members covering basics, definitions, specific explanations, useful case studies

AI For Advertising: Everything You Need to Know – This is a good, general overview and discussion of AI in marketing, pulls good data,  quotes, and a  vendor list

Adobe: Future of Marketing in an AI Driven World – Though this is sort of a paid piece for IDC, it’s still a good overview of where AI is making inroads in marketing. The discussion of what the future might hold could spark ideas for what comes next. 

More Specific to Marketing 

10 Ways Machine Learning is Revolutionizing Marketing – This is a couple years old now, and some of the predicted events are wrong, but there’s value in the original sources cited. Moreover, it’s a good grounding in how to think about where AI/ML will have the most impact in your org. Here’s his update POV: 2020 is the year it goes mainstream

Machine Learning for Marketers – This is a six part series on Medium (originally a vendor whitepaper). It’s valuable as a primer on how to think about your data strategy, first. Then, where to prioritize experimentation with advanced algorithms. Side note: the Towards Data Science publication on Medium is pretty useful, overall.

Facebook: 4 Keys to Using Machine Learning for Campaign Measurement – This is from a FB engineer, and it doesn’t provide any secrets, but it’s a useful “lessons learned” from some of the folks that built FB’s Data Driven Attribution model.

Google: Everything a Marketer Needs to Know about Machine Learning – Of course the emphasis is on Google’s tools, but this is still a useful place to start your deeper dive into how to tap the power of ML.

Other resources

Builtin – Built in has a number of tech-centric articles focused on how AI is being applied to a variety of marketing challenges. They’ve covered a lot of topics.

Summer Research Analyst

William is a 2020 summer research analyst, and is entering Washington University in St. Louis this fall to study Computer Science with a focus on AI/ML.

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