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Investigating the measures of relative importance in marketing research
Harvir S. Bansal and Philippe Duverger, International Journal of Market Research, Vol. 55, No. 5, 2013, pp. 675-694
Determining the relative importance of various predictors in a marketing research model is important for both theoretical and practical reasons.
Determining the relative importance of various predictors in a marketing research model is important for both theoretical and practical reasons. To date, the most commonly used methods to assess relative importance have involved examining either the regression coefficients or zero-order correlations of each predictor. Unfortunately, these indices are problematic when the predictors are correlated, as is the case with many of the drivers of service-provider switching, loyalty studies, satisfaction models and other marketing research. In this paper, we introduce Dominance Analysis to an audience of researchers in marketing research and empirically demonstrate its usefulness for assessing predictor relative importance. Using a Monte Carlo simulation, we first compare the accuracy of five traditional methods used in marketing research assessing relative importance and comparing them to Dominance Analysis. There are theoretical, as well as empirical, advantages to using Dominance Analysis over other methods, and these are discussed in the context of an empirical example using data drawn from a larger study of auto-repair service customers (n = 355).
Stop Flawed Marketing Mix Models From Stunting Growth
David Hoo and Michael von Gonten, ARF Experiential Learning, Audience Measurement 8.0, 2013
This paper argues that marketing mix models are not useful, and that the mix models currently in use, either the original format or the newer, VAR style, systematically understate the true effects of advertising.
This paper argues that marketing mix models are not useful, and that the mix models currently in use, either the original format or the newer, VAR style, systematically understate the true effects of advertising. Mix models are regression models and, as such, are incapable of providing truly causal evidence as to the effects of advertising and promotion. This leads marketers to undervalue the real effects of advertising and to reduce their advertising spending, reallocating those funds to price promotion. Such reductions in expenditure have the unintended effect of stunting sustainable growth and eroding the brand equity built by advertising. Moreover, reducing adspend to maximise efficiency is a vicious circle; on the other hand, effective advertising is an engine of growth.
Rediscovering the Master, John D. C. Little: A global approach to marketing ROI analytics
Lisa Wellington, ARF Experiential Learning, Re:think conference, 2012
Lisa Wellington of the Coca-Cola Company outlines the approach to marketing ROI analytics used by the soft drinks giant.
Lisa Wellington of the Coca-Cola Company outlines the approach to marketing ROI analytics used by the soft drinks giant. Specifically, the company uses a number of scientific models that quantify the volume of one or a set of marketing drivers, which are then strung together to provide a comprehensive view of the marketplace. The paper outlines the specific models used and how they fit together, covering the importance of increasing productivity, the media investment approach of the company and the scientific models used to estimate marketing ROI.
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.
Market share predictions: a new model with rating-based conjoint analysis
Hervé Guyon and Jean-François Petiot, International Journal of Market Research, Vol. 53, No. 6, 2011, pp. 831-857
Conjoint Analysis (CA) is a technique heavily used by industry in support of product development, pricing and positioning, and market share predictions.
Conjoint Analysis (CA) is a technique heavily used by industry in support of product development, pricing and positioning, and market share predictions. This generic term CA encompasses a variety of experimental protocols and estimation models (e.g. rating-based or choice-based), as well as several probabilistic models for predicting market share. As for the rating conjoint, existing probabilistic models from the literature cannot be considered as reliable because they suffer from the Independence of Irrelevant Alternatives (IIA) property, in addition to depending on an arbitrary rating scale selected by the experimenter. In this article, after a brief overview of CA and of models used for market share predictions, we propose a new model for market share predictions, RFC-BOLSE, which avoids the IIA problem, yields convergent results for different rating scales, and outputs predictions that match regression reliability. The model is described in details and simulations and a case study on truck tyres will illustrate the reliability of RFC-BOLSE.
Building profit through innovation in property development
Matt Elliott, David Laffin and John Marinopoulos, ESOMAR, Congress, Amsterdam, September 2011
This paper demonstrates key stages in the development of dynamic and innovative models based on consumer, industry and business research and intelligence as well as market research-driving decisions and strategy, resulting in a significant increase in the design, value and profitability of new communities and housing developments.
This paper demonstrates key stages in the development of dynamic and innovative models based on consumer, industry and business research and intelligence as well as market research-driving decisions and strategy, resulting in a significant increase in the design, value and profitability of new communities and housing developments. It offers guidance to decision makers to help them connect with employees, consumers and government stakeholders whilst supporting corporate strategy. It also discusses connecting business with consumers and other key stakeholders to optimise the design of new communities and housing developments with significant positive impact on business and society.
Predictability of movie box office based on trailer testing - Using neuroscience and bio-sensory measurements for predictive modeling
W. Bryan Smith and Keith Winter, ESOMAR, Congress, Amsterdam, September 2011
The Emsense Movie Trailer Project was established to demonstrate the in-market performance prediction power of neurometrics.
The Emsense Movie Trailer Project was established to demonstrate the in-market performance prediction power of neurometrics. Testing new movie trailers prior to film release, EmSense measures neurometric EEG response patterns among quantitative target samples and combines them with survey metrics and other data to predict first week box office results. Findings to date have established greater accuracy for performance prediction than standard existing movie industry methods. This pioneering project is the first known quantitative neurometric prediction validation study. It has far reaching implications for predicting in-market performance of other marketing stimuli such as advertising, packaging and new product concepts.
From a snapshot to a movie - Pushing the boundaries of marketing ROI
Ram Krishnamurthy, Vittorio Raimondi and Patricio Pagani, ESOMAR, Congress, Amsterdam, September 2011
This paper illustrates an innovative approach that enables Coca-Cola to bring a scenario planning dimension to their consumer tracking study.
This paper illustrates an innovative approach that enables Coca-Cola to bring a scenario planning dimension to their consumer tracking study. This increased tenfold the power of the study beyond just reading current and historic brand performance. The authors explain how they overcame the traditional view of Quantitative Tracking (basically learning about the past and monitoring of brand health), by creating a tool for forward planning and strategizing. This new framework, originally adopted just at the corporate level, is now being rolled-out across Coca-Cola’s key 33 markets, empowering local markets to entertain fact-based conversations on topics like the importance of consumer retention vs. recruitment initiatives, and the consequent investment decisions.
Household vehicle consumption forecasts in the United States, 2000 to 2005
Qiushi Feng, Zhenglian Wang, Danan Gu and Yi Zeng, International Journal of Market Research, Vol. 53, No. 5, 2011, pp. 593-618
Forecasts of household vehicle consumption are important for automobile market analyses. This paper employs the ProFamy extended cohort-component new method to project household vehicle consumption from 2000 to 2025 across four regions of the United States (the Northeast, Midwest, South and West).
Forecasts of household vehicle consumption are important for automobile market analyses. This paper employs the ProFamy extended cohort-component new method to project household vehicle consumption from 2000 to 2025 across four regions of the United States (the Northeast, Midwest, South and West). The results show that the total number of household vehicles in 2025 will reach 235 million, representing a 31% increase over the 25 years. About a half of the increase is due to the consumption of cars, while the household consumption of vans will increase at a faster rate than that of cars and trucks. Household vehicle consumption will grow more in white non-Hispanic and Hispanic households in comparison with black non-Hispanic and Asian and other non-Hispanic households. Owners of household vehicles in the United States will be ageing quickly. Among households of different sizes, the largest increase in household vehicles will come from two-person households. Across the four regions, the largest increase in household vehicle consumption will be in the South, followed by the West, Midwest and Northeast.
The Measure of All Things: Finding Out That Something Doesn't Work Is the First Step Toward Learning What Does Work
Duncan Watts, Journal of Advertising Research, Vol. 51, No. 2, 2011, pp. 373-379
Duncan Watts shares insights from his new book Everything is Obvious, including a recent randomized experiment testing online advertising with 1.6 million Yahoo! users.
Duncan Watts shares insights from his new book Everything is Obvious, including a recent randomized experiment testing online advertising with 1.6 million Yahoo! users. The researchers estimated that the additional revenue generated by the advertising was roughly four times the cost of the campaign in the short run, and possibly much higher over the long run. But what they also discovered was that almost all the effect was for older consumers—the ads were largely ineffective for people under 40. At first, this latter result seems like bad news. But the right way to think about it is that finding out that something doesn’t work is also the first step toward learning what does work.
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