About Kevin Gray

Kevin Gray is president of Cannon Gray, a marketing science and analytics consultancy.

Kevin Gray Posts (39)

• What is Segmentation? - 22 Jun 2021
  
  Segmentation refers to many things, and is one of the most frequently used words in marketing This article looks at segmentation from a somewhat different-than-usual perspective.
• Where is Marketing Data Science Headed? - 05 Jan 2021
  
  Marketing data science - data science related to marketing - is now a significant part of marketing. Some of it directly competes with traditional marketing research and many marketing researchers may wonder what the future holds in store for it.
• Modeling 101 - 13 May 2019
  
  In the past couple of decades, innovation in statistics and machine learning has been increasing at a rapid pace and we are now able to do things unimaginable when I began my career.
• AI For Ordinary Folks - 11 Apr 2019
  
  There are many excellent books, articles, YouTube lectures and blogs on AI and topics related to it aimed at data scientists and AI researchers. You may want to, instead, check out this list of AI resources crafted for ordinary folks.
• Spatio-Temporal Statistics: A Primer - 05 Apr 2019
  
  Marketing scientist Kevin Gray asks University of Missouri Professor Chris Wikle about Spatio-Temporal Statistics and how it can be used in science and business.
• Why Primary Research? - 04 Dec 2018
  
  Primary studies have always been a strength of marketing research. Many younger marketing researchers, however, have only been exposed to standardized ready-made research products or big data. This is a concern. What is the point of the word research in marketing research?
• Causation in a Nutshell - 20 Jul 2018
  
  Every move we make, every breath we take, and every heartbeat is an effect that is caused. Even apparent randomness may just be something we cannot explain.
• A Better Stats 101 - 12 Jun 2018
  
  Statistics encourages us to think systemically and recognize that variables normally do not operate in isolation, and that an effect usually has multiple causes. Some call this multivariate thinking. Statistics is particularly useful for uncovering the Why.
• The Book of Why - 01 Jun 2018
  
  Judea Pearl has made noteworthy contributions to artificial intelligence, Bayesian networks, and causal analysis. These achievements notwithstanding, Pearl holds some views many statisticians may find odd or exaggerated.
• Frequentists Fight Back - 24 May 2018
  
  Frequentist methods are sometimes described as “classical”, though most have only appeared in recent decades and new ones are under development as you read this. Whatever we call it, this branch of statistics is very much alive.