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Abstract
With artificial intelligence (AI) and machine learning (ML) taking the spotlight recently, it is imperative for all marketing professionals to cultivate an understanding of what these entail from a practical point of view. It is valuable to know how AI and ML arose from computer programming, some of their strengths, and some of their risks. It is useful to have a game plan for how to approach this powerful, new technology. This paper describes ML through the lens of prior programming methods and describes what it can and cannot do, while introducing some of the risks associated with using ML for marketing.
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Author's Biography
Jim Sterne sold business computers to companies that had never owned one in the 1980s, consulted and keynoted about online marketing in the 1990s, founded the Marketing Analytics Summit in 2002 and co-founded the Digital Analytics Association in 2004. He has written a number of books, including most recently, ‘Artificial Intelligence for Marketing: Practical Applications’. He is now helping companies get more value from data and helping small and medium-sized agencies achieve scale at speed.
Citation
Sterne, Jim (2017, November 7). From programming to statistics to machine learning for marketing. In the Applied Marketing Analytics: The Peer-Reviewed Journal, Volume 3, Issue 4. https://doi.org/10.69554/OKLE8586.Publications LLP