A major problem in marketing is that one often has only a general idea of what another marketer is speaking about. “Unfortunately, marketing still does not have that commonality of terminology” (Farris, Reibstein, and Scheller, 2016, page 46). We need a common marketing language. We Lack Shared Meanings A marketer will talk of loyalty and…
Category: Understanding Marketing
Predictive Analytics And Vast Search
Eric Siegel has an excellent book on predictive analytics and vast search. As his title suggests these involve lying, buying and dying as well as a few things that don’t rhyme. Applying Analytics The center of his book is a table of applications of predictive analytics. The marketing examples (Table 2) give a number of interesting…
Social Network Analysis: Interesting But Still Limited
“Connected” by Christakis and Fowler explains the benefits of social network analysis with fascinating and important stories. Social network analysis tells us who is most likely to catch a habit. This is just like how doctors can predict who is most likely to catch a disease from the person’s place in a network. The analysis of networks helps illuminate a vast range…
Lying With Statistics
While statistics can help us understand the world there is plenty of opportunity to abuse them to mislead. Darrell Huff wrote a short book that was first published in 1952 on lying with statistics. Some of the text shows its age (lots of male pronouns and references to gentleman) but many of the lessons remain applicable today. Reading Huff’s…
How Do Academic Marketers Choose Their Objectives?
I think one of the great problems in marketing academia is that we spend a lot of time thinking about our models and very little time on our data. We have increasing clear views of how things connect up but we don’t really know what it is that we are connecting up. Deciding what objective…
Spurious Correlations: A Big Problem With Big Data?
Tyler Vigen has done great work popularizing Spurious Correlations. He has found an effective way to convey an important message. Namely, that correlation does not equal causation. Lots of things are correlated but that doesn’t mean that they have anything to do with each other. Data Dredging To create his graphs Vigen indulges in: Data Dredging… a technique used…
Metrics that Marketers Muddle
From 2016: With Charan Bagga I have just published an article in the Sloan Management Review (see the article here). We called the article — rather self-explanatorily — Metrics that Marketers Muddle. Annoying Things That Marketers Do This central message is a bit cranky. Indeed we could have titled the paper, “annoying things that marketers do”. We highlight:…
The Last Mile: Implementing Your Wonderful Strategy
Dilip Soman’s The Last Mile is an excellent book. It reiterates fascinating points that are commonly found in behavioral (economics) books. What sets the book apart? The effective structure put to the insights. There are plenty of classifications and tables. These help us better understand the vast number of behavioral insights that the book contains. Test Your Ideas Other interesting points…
Uncovering The Message In The Mess Of Big Data
This week I’m focusing on research that I’ve co-authored with Xin Wang in Business Horizons. We called this ‘Uncovering the Message in the Mess of Big Data’. Our article aims to explain to managers how they can work out what the messages are in large amounts of data. What Data Should You Look At? The classic application…
Why Even The Best Economists Don’t Get Marketing
George Akerlof and Robert Shiller have good points, excellent stories, and a clear aim in Phishing for Phools. The aim is to convince economist colleagues that all market outcomes aren’t perfect. I applaud their aim. That said, their conceptualization assumes consumers (and others) are robots with a monkey on our backs. The monkey prevents us from being “fully rational”. I’d say, however, that we…
