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Using graphical statistics to better understand market segmentation solutions
Sara Dolnicar and Friedrich Leisch, International Journal of Market Research, Digital First, December 2013
Market segmentation lies ‘at the heart of successful marketing’ (McDonald 2010), yet market segmentation solutions are not trivial to interpret, especially if consumers are segmented using post hoc or a posteriori or data-driven segmentation, where several consumer characteristics are analysed simultaneously to identify or construct market segments.
Market segmentation lies ‘at the heart of successful marketing’ (McDonald 2010), yet market segmentation solutions are not trivial to interpret, especially if consumers are segmented using post hoc or a posteriori or data-driven segmentation, where several consumer characteristics are analysed simultaneously to identify or construct market segments. In fact, 65% of marketing managers admit to having difficulties with the interpretation of data-driven market segmentation solutions. In this study we develop novel ways of visualising segmentation solutions using graphical statistics methodology. The proposed plots help academics and practitioners to interpret complex market segmentation solutions, thus improving the practical usability of market segmentation, reducing the risk of misinterpretation and contributing to closing the much-lamented ‘theory–practice divide’ in market segmentation.
Mythbuster: Ignoring the 'still' majority
Les Binet and Sarah Carter, Admap, April 2013, pp. 9-9
In their regular column, the authors question why the advertising and media industries insist on ignoring the 'silent majority'.
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.
Choosing the right baskets for your eggs: deriving actionable customer segments using supervised genetic algorithms
Sam Davis, International Journal of Market Research, Vol. 54, No. 5, 2012, pp. 689-706
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.
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.
How respondents use verbal and numeric rating scales: a case for rescaling
Michael Bendixen and Yuliya Yurova, International Journal of Market Research, Vol. 54, No. 2, 2012, pp. 261-282
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.
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.
An improved, practical model of consumer choice
Len Marchant, Phil Prescott and Nic Jackson, International Journal of Market Research, Vol. 54, No. 1, 2012, pp. 71-92
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.
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.
Optimizing Market Segmentation for a Global Mobile Phone Provider for both Targeting and Insight
Marc O'Regan, Kalidas Ashok, Olga Maksimova and Oleg Reshetin, Journal of Advertising Research, Vol. 51, No. 4, 2011, pp. 571-577
This paper describes a complex 5-country segmentation of the mobile telephony market on behalf of MTS, a leading global mobile phone provider.
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.
Adaptive Execution in Media Planning
Malcolm Murdoch, Warc Exclusive, Datacentric, December 2011
Malcolm Murdoch, director of digital data and performance, Mindshare presented at the Warc Datacentric conference in London.
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.
Mythbuster: Don't believe all the stats
Les Binet and Sarah Carter, Admap, October 2011, pp. 9-9
Particle physicists don't treat results as statistically significant unless there's under a one in two million chance that it's a fluke.
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.
From brilliant to actionable - It takes technical brilliance and constant questioning to achieve the truly actionable in marketing ROI
Rafael Alcaraz, Steve Cohen and Mark Garratt, ESOMAR, Congress, Amsterdam, September 2011
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.
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.
Improving the display of correspondence analysis using moon plots
Tim Bock, International Journal of Market Research, Vol. 53, No. 3, 2011, pp. 307-326
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.
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.
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