Summary
In their regular column, the authors question why the advertising and media industries insist on ignoring the 'silent majority'. They point out that advertising likes to focus on what is easy to see and measure. So while 90% of the marketing universe consists of behaviour that cannot be easily tracked, the industry focuses on the easy 10%. Binet's and Carter's advice when seeing a "headline percentage", subtract it from 100 and spend more time thinking about that, probably larger, percentage as that is where most of the real action is likely to be.

Summary
In the context of key driver analysis in applied customer satisfaction research, the assumption of sample homogeneity (that single models perform adequately over the entirety of a survey sample) can be shown to restrict the value of the insights derived. While latent class regression has been used as a method of circumventing some of these issues, it is proposed that there are major barriers to both uptake and successful practical usage of the technique. Several of these issues are common to any multivariate technique, while others are specific to latent class regression. Following an examination of these issues, we introduce an alternative technique for deriving discrete latent classes, using a combination of genetic algorithms and (bivariate) correlations. This paper concludes that the proposed approach outperforms latent class regression in its ability to deliver action-orientated insights, and is better placed to assist marketers facing real-world research questions and datasets.

Summary
The dominant practice among researchers is to treat verbal rating scales as interval in nature because of the vast array of analytical techniques that this opens up when it comes to analysis. This practice prevails despite warnings to the contrary that go back over half a century. A similar assumption seems safer when it comes to numeric rating scales. This paper revisits the issue to caution researchers to use only methods appropriate to the level of the data unless the proper rescaling is employed. The change in chi-square technique is developed to supplement rescaling using correspondence analysis, to uncover how scales are used by respondents. These techniques are applied to a sample that uses a verbal scale and three samples that use numeric rating scales. In all cases, the assumption of interval behaviour of the data proves to be a poor one. Rescaling is found to preserve the association among the variables. Strong evidence that rescaling changes the distribution of the variables leading to changes in the meaning of basic descriptive statistics is provided. Further research in this area and in the field of cross-cultural research is suggested.

Summary
This paper describes a framework for understanding and researching brand choice. The underlying model starts from the assumption that purchasers faced with alternative brands will select what in their judgement suits them best. It develops the theory and the mathematics as simply as possible, and goes on to describe the marketing implications. It explains how to build a working model of the market using Monte Carlo techniques, and how this can be used to test the validity of the basic assumptions and to explore possible marketing strategies. It demonstrates, using real data from an actual study, how to interpret the market model in terms of purchasers' images of the brands. The paper will be of interest to both qualitative and quantitative researchers.

Summary
This paper describes a complex 5-country segmentation of the mobile telephony market on behalf of MTS, a leading global mobile phone provider. MTS wanted the segmentation to maintain a common framework across all countries, while capturing any real differences between them. A critical requirement was “targetability”—the ability to accurately attribute a segment to each one of MTS’s subscribers. This entailed that the segments be well differentiated on “hard” behavioral metrics from MTS’s billing databases. However, it was also critical that such differentiation was not achieved at the expense of richness on “softer” aspects of marketing—segments also needed to have distinct needs, attitudes and motivations, so that they could be used as a platform for messaging, product development, and advertising. Meeting these competing requirements led to a solution that combined survey data on more than 10,000 respondents and billing data on more than 80 million customers using an innovative analytic technique.

Summary
Malcolm Murdoch, director of digital data and performance, Mindshare presented at the Warc Datacentric conference in London. He discussed the importance of clear targets and making media planning more data-focused and less research-focused in a world of continuous, rather than discrete, data. Integrating data from retailers, set top boxes, mobiles and the web, provides greater depth to planning models. Also considered is how to approach audience targeting online, by making ads relevant and personal.

Summary
Particle physicists don't treat results as statistically significant unless there's under a one in two million chance that it's a fluke. While this may a bit extreme, Binet and Carter think marketers do need to raise their game a bit when using stats. They have noticed that quantitative research companies raise statistical significance issues far less nowadays and planners aren't routinely trained to query sample size either. Correlation doesn't equal causation and causation isn't always what you think it is either.

Summary
This paper describes the collaboration between Hershey’s and In4mation Insights to revolutionize how marketing ROI is modeled and how its results are spread throughout an organization. The development of new-to-the-world Bayesian statistical methods, coupled with scalable and speedy software run using parallel processing on the “cloud”, is addressed. Results have then been placed in a marketing enterprise-wide simulation model, where the findings have been pressure-tested by senior executives. The paper documents how a close relationship between a savvy client and advanced modelers led to groundbreaking results.

Summary
Standard correspondence analysis plots are readily misinterpreted by research users. This paper presents a new plot, called the moon plot, which is less susceptible to misinterpretation. Row points are plotted in the traditional way. Column points are plotted equidistant from the origin, with their directions from the origin as in traditional correspondence analysis plots, and the information traditionally communicated by the distance of the points to the origin instead communicated by the size of the fonts of the labels.

Summary
Market segmentation is a widely accepted concept in marketing research and planning. Although cluster analysis has been extensively applied to segment markets in the last 50 years, the ways in which the results were obtained have often been reported to be less than satisfactory by both practitioners (Yankelovich & Meer 2006) and academics (Dolnicar 2003). In order to provide guidance to those undertaking market segmentation, this study discusses the critical issues involved when using cluster analysis to segment markets, makes suggestions for best practices and potential improvements, and presents an empirical survey that seeks to provide an up-to-date assessment of cluster analysis application in market segmentation within a six-stage framework. Analyses of more than 200 journal articles published since 2000, in which cluster analysis was empirically used in a marketing research setting, indicate that many critical issues are still ignored rather than addressed adequately.