Loyalty programs are an interesting marketing tactic. On the one hand, they have the potential to encourage consumers to stick with a provider. On the other hand, they can end up rewarding those who would have purchased anyway. At their worst one might say that the programs don’t so much create loyalty as feed consumers…
Author: neilbendle
Neil is an Associate Professor Marketing at the Terry College of Business, University of Georgia. He investigates the measurement of marketing performance, the accounting/marketing interface, and the impact of non-standard decision making in commercial and political markets.
Neil is the Chair of the Marketing Accountability Standards Board advisors. He is co-author of Marketing Metrics: The Manager’s Guide to Measuring Marketing Performance (3rd edition) Wharton School Press and is co-author of a cartoon book: Behavioural Economics for Kids.
How Sexy is Working With Big Data?
I think that academics should share their opinions widely. Some academics may believe that they have no opinions, they just relate what the data says. This is might be true for extremely empirical scholars, those who typically see themselves working with big data. Such scholars are kidding themselves. We must be willing to change with data but our experience helps…
Nudges Are Not Magical (Just in Case Someone Thought They Were)
The idea of nudging, designing choices to help people make better choices, has become popular for good reason. Yet, nudges aren’t magical, which some people seem disappointed about when they find this out. Nudges Or What? A nudge is a well-designed attempt to guide the decision-maker towards a beneficial outcome. The alternative seems to be random,…
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…
Bringing Accountability To Marketing
Peter Rosenwald shares his experience bringing accountability to marketing. He describes trying to account for the success of marketing campaigns in his book Accountable Marketing. This examines many ideas that are critical to quantitative marketing and covers a vast range of industries. No One Is Average He gives some great perspectives — such as “Average: The Most…
Understanding What A Fallacy Is
Formal logic makes for elegant research. It can help us in understanding what a fallacy is. Formal And Informal Logic With formal logic there is a right answer and so researchers can be confident that some choices are simply wrong. Unfortunately, formal logic has relatively limited application in the real world. Gerd Gigerenzer has argued that some flaws in…
Bad Arguments
A lot of arguments simply don’t make sense. Spotting bad arguments is a vital, and I’d guess, rare skill for academics and business people. Ali Almossawi has a fun little book on bad arguments. They are all illustrated to make them more memorable. I don’t completely endorse all the descriptions. Still, he raises important things to bear in mind…
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…
