"It may be that most consumers forget the attribute-based reasons why they chose or rejected the many brands they have considered and instead retain just a summary attitude sufficient to guide choice the next time."This is how Dolnicar and Rossiter con... [Read more...]

Obviously, preference precedes choice because choices are made to maximize preference. That is certainly the way we conduct our marketing research. We generate factorial designs and write descriptions full of information about products and services. Ou... [Read more...]

The journey metaphor is almost irresistible. All one needs is a starting point and a finish line, plus some notion of progression. Thus, life is a journey, and so is love. Why not apply the metaphor to your next purchase? McKinsey & Company takes s... [Read more...]

Conjoint analysis and choice modeling rely on repeated observations from the same individuals across many different scenarios where the features have been systematically manipulated in order to estimate the impact of varying each feature. We believe th... [Read more...]

Causal thinking is seductive. Product experience comes first, then feelings of satisfaction, and finally intentions to continue as a customer. Although customer satisfaction and loyalty data tend to be collected all at one time within the same question... [Read more...]

Clustering is the search for discontinuity achieved by sorting all the similar entities into the same piles and thus maximizing the separation between different piles. The latent class assumption makes the process explicit. What is the source of variat... [Read more...]

Herbert Simon was succinct when he argued that judgment and choice "is shaped by a scissor whose two blades are the structure of the task environment and the computational capabilities of the actor" (Simon, 1990, p.7). As a marketing researcher, I take... [Read more...]

The psych R package includes a data set called "bfi" with self-report ratings on 25 personality items along a 6-point agreement scale. All the details are provided in the documentation accompanying the package. My focus is how to represent the correlat... [Read more...]

Tal Yarkoni's post on "The homogenization of scientific computing, or why Python is steadily eating other languages' lunch" is an enjoyable read of his transition from R to Python. He makes a good case, and I have no argument with his reasoning or the ... [Read more...]

Statistical learning theory offers an opportunity to those of us trained as social science methodologists to look at everything we have learned from a different perspective. For example, missing value imputation can be seen as matrix completion and rec... [Read more...]

Adding features to a product can be costly, so brands have an incentive to include only those features most likely to increase demand. In the last two posts (first link and second link), I have recommended what could be called a "features stress t... [Read more...]

At the end of the last post, the reader was left assuming respondent homogeneity without any means for discovering if all of our customers adopted the same feature prioritization. To review, nine features were presented one at a time, and each time res... [Read more...]

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... [Read more...]

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... [Read more...]

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... [Read more...]

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... [Read more...]

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... [Read more...]

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... [Read more...]

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... [Read more...]

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 ... [Read more...]