PinnedMarketing Data Science with Joe Domaleski·Jun 7A Marketer’s Field Guide to Machine LearningHow to match the right machine learning algorithm to the right marketing problem, from linear regression to large language models.A response icon7A response icon7
Marketing Data Science with Joe Domaleski·2d agoA Practical Guide to Measuring Text SimilarityA hands-on look at how text can be compared by words, structure, and meaning, and why no single method answers every question.A response icon1A response icon1
Marketing Data Science with Joe Domaleski·Sep 13The Same Answer, Ten Different Explanations: Non-Determinism in Generative AI SearchLast year, I coined a marketing term, “Weighted Average Cost of Marketing (WACM).” I asked ChatGPT ten times who came up with it to see how…A response icon1A response icon1
Marketing Data Science with Joe Domaleski·Sep 6Fast, Cheap, and Wrong: The Business Case Against AI SlopWhat AI slop is, what it costs you, what it costs the people around you, and how to use AI without adding to the mess.A response icon1A response icon1
Marketing Data Science with Joe Domaleski·Aug 30SEO, AEO, and GEO: A Marketer’s Guide to Search VisibilityHow to rank in search, surface in answers, and earn citations from generative AI
Marketing Data Science with Joe Domaleski·Aug 23The Middle-Aged Graduate Student Earns a Master of Science in Analytics from Georgia TechWhat I learned from Georgia Tech graduate classes, hackathons, research competitions, and becoming a student again in my late 50s.A response icon11A response icon11
Marketing Data Science with Joe Domaleski·Aug 16Vanity Metrics: You Can’t Deposit Likes at the BankHow to tell whether your marketing numbers are driving real business growth or just making your dashboard look goodA response icon11A response icon11
