AI for Marketers: An Introduction and Primer, Third Edition

by Christopher S. Penn

The march of artificial intelligence (AI) is relentless, and in marketing, nearly every software vendor is promising it in some fashion. But what does AI truly mean, and how does it apply to your work?In this expanded and improved third edition, marketers will learn even more examples and applications of AI as it applies to modern marketing. From attribution analysis to topic modeling to forecasting, learn how AI is already impacting the work you do and how it will change the fundamentals of marketing.You'll also learn how to prepare your company or organization for AI, how to prepare your career for AI (and whose jobs are most at risk), and the many, many things AI cannot do - and probably won't for some time.When you're done reading this book, you'll have a strong sense of what's possible with AI and machine learning when it comes to marketing, a blueprint for how to integrate it into your company, and perhaps even a desire to try it out for yourself. You'll be able to see through AI sales pitches from vendors and talk a little bit of shop with data scientists and AI engineers.

239 pages, Paperback

Published March 7, 2021

Reviews

[Sigo Paolini · Rating 2 out of 5]

I don't think Penn really understands the issue. His questions are not really relevant to the problem of AI though he does point out alot of the problems with their gathering process. Nor does he truly explain the various key terms (zero click, scraping) but puts that all data analysts- my particular field. That said he does not describe the various data analyst jobs very well or clearly - they seem more like dictionary terms that anything encyclopedic. I don't know who it could help because his bandying of terms is like here's a catchword -- and you say WOW! but most of those terms have been around 35 plus years, and don't answer any question. He t ries to be relevant from page 56 on about what jobs are good to into to stay ahead of the AI juggernaut, but I think some of them are already on the chopping block so I don't agree. From there he decides to hit the buzzword of bias (big yawn) . He does say one thing that is helpful -- R and statistics. If you're in college, study that. It's been gold for a while and I believe will stay that way.