Blog Archives

Feature Prioritization: Multiple Correspondence Analysis Reveals Underlying Structure

December 10, 2013
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Feature Prioritization:  Multiple Correspondence Analysis Reveals Underlying Structure

Measuring the Power of Product Features to Generate Increased DemandProduct management requires more from feature prioritization than a rank ordering. It is simply not enough to know the "best" feature if that best does not generate increased demand. W...

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Maximizing Return from Every Item in the Marketing Research Questionnaire

December 3, 2013
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Maximizing Return from Every Item in the Marketing Research Questionnaire

Consumers will not complete long questionnaires, so marketing research must get the most it can from every item.  In this post, we look into the toolbox of R packages and search for statistical models that enable us to learn a great deal about eac...

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Key Driver vs. Network Analysis in R

November 8, 2013
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Key Driver vs. Network Analysis in R

When marketing researchers speak of driver analysis, they are referring to an input-output model with overall satisfaction as the output and performance ratings of specific product and service components as the inputs. The causal model is straightforwa...

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Remembering the Gist, But Not the Details: One-Dimensional Representation of Consumer Ratings

October 13, 2013
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Remembering the Gist, But Not the Details:  One-Dimensional Representation of Consumer Ratings

In survey research, it makes a difference how the question is asked.  "How would you rate the service you received at that restaurant?" is not the same as "Did you have to wait to be seated, to order your meal, to be served your food, or to pay yo...

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Latent Variable Mixture Modeling: When Heterogeneity Requires Both Categories and Dimensions

August 26, 2013
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Latent Variable Mixture Modeling:  When Heterogeneity Requires Both Categories and Dimensions

Dichotomies come easily to us, especially when they are caricatures as shown in this cartoon.  These personality types do seem real, and without much difficulty, we can anticipate how they might react in different situations.  For example, if...

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Using Heatmaps to Uncover the Individual-Level Structure of Brand Perceptions

August 16, 2013
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Using Heatmaps to Uncover the Individual-Level Structure of Brand Perceptions

Heatmaps, when the rows and columns are appropriately ordered, provide insight into the data structure at the individual level.  In an earlier post I showed a cluster heatmap with dendrograms for both the rows and the columns.  In addition, I...

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The Brand as Affordance: Item Response Modeling of Brand Perceptions

August 13, 2013
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The Brand as Affordance: Item Response Modeling of Brand Perceptions

It is just too easy to think of a brand as a web of associations.  What comes to mind when I say "Subway Sandwich"?  Did you remember a commercial or the "eat fresh" tagline?  Without much effort, one can generate a long list of associat...

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The Reorderable Data Matrix and the Promise of Pattern Discovery

June 12, 2013
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The Reorderable Data Matrix and the Promise of Pattern Discovery

We typically start with the data matrix, a rectangular array of rows and columns.  If we type its name on the R command line, it will show itself.  But the data matrix is hard to read, even when there are not many rows or columns.  The heat map is a visual alternative.  All you need is the R function...

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Why doesn’t R have a MaxDiff package?

May 28, 2013
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Almost once every year someone asks if R has a package for running the MaxDiff procedure sold by Sawtooth.  One such inquiry recently received a reply with a link showing in some detail the R code needed to generate a balanced incomplete...

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Incomplete Data by Design: Bringing Machine Learning to Marketing Research

May 6, 2013
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Incomplete Data by Design: Bringing Machine Learning to Marketing Research

Survey research deals with the problem of question wording by always asking the same question.  Thus, the Gallup Daily Tracking is filled with examples of moving averages for the exact same question asked precisely the same way every day. &nb...

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