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Marketing Research Data Use Articles

In Data Use articles market researchers with a background in statistics explain a specific technique or discuss ways to tackle data analysis tasks. View, sort, and refine more than 25 years of Quirk's marketing research Data Use articles.

 

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A beautiful segmentation

Published
November 2003
Author
Michael Lieberman
Abstract
Looking for an edge, managers these days are turning more frequently to the marriage of good research and advertising know-how to get there. This article follows a case study from the identification of the target segmentation, to determining sociodemographic characteristics, psychographic information, automobile self-description, client gasoline brand equity based on future behavioral intentions, and finally to developing a brand communication strategy.

A comparison of missing value options in regression analysis

Published
December 1995
Author
Gary M. Mullet
Abstract
Regression analysis is one tool for evaluating customer satisfaction measurement. Non-response is problematic for multiple regression analysis because most software discards all of a respondent’s data when it encounters a missing value. This article discusses options for coping with item non-response in regression runs, comparing run results based on a real data set.

A marketing researcher's guide to multivariate analysis

Published
November 1994
Author
Charles J. Schwartz
Abstract
Marketing researchers are regularly faced with a variety of challenges, including tight deadlines, demands for results that are concise and easy to understand, and an abundance of data. This article discusses multivariate analysis as a body of statistical techniques that helps researchers isolate actionable findings quickly and reduce them to a couple of charts and graphs.

A response to Grisaffe

Published
February 1993
Author
William McLauchlan, Ph.D.
Abstract
This article responds to an article by Doug Grisaffe's, published in this month’s Quirk’s Marketing Research Review, in which Grisaffe critiqued the author’s views about the strengths of using self-stated importance and the weaknesses of using multiple regression analysis to measure customer satisfaction.

A simple solution to nagging questions about survey, sample size and validity

Published
January 1999
Author
Susie Sangren
Abstract
The quality of a market analysis is judged by its validity. Unfortunately, data from non-probability, informal sample surveys lack measurable confidence. This article demonstrates an easy method of calculating the sample size needed for a specific market survey or experiment.

A survey of multivariate methods useful for market research

Published
May 1999
Author
Susie Sangren
Abstract
Most researchers are already familiar with universal statistical methods. This article discusses multivariate statistical methods, including key characteristics of multivariate procedures and examples.

A tale of two tallies

Published
March 2003
Author
Paul Zaff
Abstract
There are two fundamental questions in marketing research that appear at some point in most questionnaires: What did they buy? What’ll they buy next? This article discusses probability analysis technique, a procedure used to maximize the output from these two basic questions.

All customers are not created equal

Published
December 2001
Author
Jon Pinnell
Abstract
Customer satisfaction researchers often use statistical methods to infer how “important” various drivers are to overall satisfaction scores or customer loyalty indices. This article discusses latent class analysis, a technique that addresses respondent heterogeneity, which is one of the most significant pitfalls of traditional methods for computing derived importances. These methods provide a deeper understanding of individual differences between customers.

Appropriate use of regression in customer satisfaction analyses:

Published
February 1993
Author
Doug Grisaffe
Abstract
In October, 1992 Quirk’s Marketing Research Review, Dr. William McLauchlan critiqued the use of multiple regression analysis to model customer satisfaction and asserted that self-stated importance is a superior approach. The author of this article disagrees with McLauchlan, and uses this article to respond to these critiques and explain why multiple regression analysis would be a more powerful choice of analysis technique.

Assessing the monetary value of attribute levels with conjoint analysis: warnings and suggestions

Published
May 2001
Author
Bryan Orme
Abstract
Conjoint analysis is often used to assess how buyers trade off product features with price. This article reviews a common technique for converting conjoint utilities to a monetary scale and suggests a better approach.

Back to basics: remember to rotate

Published
January 1993
Author
Gary M. Mullet
Abstract
This article stresses the importance of reducing response bias by changing the order of items and scales from respondent-to-respondent in a survey market research. To analyze the results once the stimuli are rotated, the author suggests a crossover analysis using the analysis of variance programs included in statistical software packages.

Benefit impact analysis

Published
January 1995
Author
Ed Cohen
Abstract
Conjoint analysis is incredibly useful to managers. This article outlines benefit impact analysis, a relatively simple technique for exploring product elements that produces a measure analogous to conjoint’s utility values in lieu of conjoint analysis.

Beware of MCA mapping

Published
December 1992
Author
Betsy Goodnow
Abstract
The debate between spokesmen for multiple correspondence analysis and correspondence analysis has a long history. This article explains why table data is appropriate for quantitative analysis and Burt matrix data is not appropriate for quantitative analysis.

Budget for living data

Published
July 1987
Author
Harris Goldstein
Abstract
Interactive perceptual mapping, conjoint analysis and "living databases" are helping marketing research practitioners get a competitive edge and gain respect.

By the Numbers: Telephone vs. Internet data collection - a case study

Published
December 2007
Author
James H. Nelems
Abstract
The author, CEO of a research firm, explores results of his company’s research on research regarding differences in the results obtained from telephone studies versus online studies.

CHAID response modeling and segmentation

Published
June 1990
Author
Tony Babinec
Abstract
This article describes the benefits of using CHi-square Automatic Interaction Detection (CHAID) to predict a response variable based upon a set of explanatory variables. This method is useful when the variables are categorical rather than quantitative.

Classification tree methods: AID, CHAID and CART

Published
February 1992
Author
Steven Struhl
Abstract
Classification tree methods greatly expand the ways in which you can analyze, view and consider survey data and other information. This article compares several procedures for producing classification trees: AID (automatic interaction detection), CHAID (chi-squared automatic interaction detection), and CHAID/CART (CHAID and classification and regression tree).

Combining banner points - is the variance correct?

Published
April 1990
Author
Gary M. Mullet
Abstract
This article cautions researchers to scrutinize their data tabulation package when weighing or pooling a particular group of banner points. Failing to address this issue could lead to incorrect statistics and inaccurate statistical conclusions.

Computers know "how" but they don't know "what"

Published
April 1991
Author
Gary M. Mullet
Abstract
This article points to several potential pitfalls of taking statistical software results at face value.

Conjoint analysis in pharmaceutical marketing research

Published
June 2001
Authors
Gang Xu and Yilian Yuan
Abstract
Conjoint analysis is a technique that evaluates the importance of a product’s attributes to consumers. This article details how to use conjoint analysis in pharmaceutical marketing research, including design, data analysis, validation, simulating market share and limitations of the technique.

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