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We know exactly what you want: the development of a completely individualised conjoint analysis
Markus Voeth, Uta Herbst and Frank Liess, International Journal of Market Research, Vol. 55, No. 3, 2013, pp. 437-458
Improving the predictive validity of conjoint analysis has been an important research objective for many years.
Improving the predictive validity of conjoint analysis has been an important research objective for many years. Whereas the majority of attempts have been different approaches to preference modelling, data collection or product presentation, only a few scholars have tried to improve predictive validity by individualising conjoint designs. This comes as a surprise because many markets have observed an augmented demand for customised products and highly heterogeneous customers’ preferences. Against this background, the authors develop a conjoint variant based on a completely individualised conjoint design. More concretely, the new approach not only individualises the attributes, but also the attribute levels. The results of a comprehensive empirical study yield a significantly higher validity than existing standardised-level conjoint approaches. Consequently, they help marketers to gain deeper insights into their customers’ preferences.
Strategic management of new products: ex-ante simulation and market segmentation
Jae Young Choi, Jungwoo Shin and Jongsu Lee, International Journal of Market Research, Vol. 55, No. 2, 2013, pp. 289-314
Among various methodologies for demand forecasting of new products, the random-coefficient discrete-choice model using stated preference data is considered to be effective because it reflects heterogeneity in consumer preference and enables the design of experiments in the absence of revealed-preference data.
Among various methodologies for demand forecasting of new products, the random-coefficient discrete-choice model using stated preference data is considered to be effective because it reflects heterogeneity in consumer preference and enables the design of experiments in the absence of revealed-preference data. Based on estimates drawn from consumer preference data by structural hierarchical Bayesian logit models, this study develops the overall, strategic, demand-side management for new products by combining market share simulation and a rigorous clustering methodology, the Gaussian mixture model. It then applies the process to the empirical case of electronic payment instruments.
Using response surface methodology to optimise factors in conjoint experiments
Rubén Huertas-Garcia, Juan Carlos Gázquez-Abad, Francisco J. Martínez-López and Irene Esteban-Millat, International Journal of Market Research, Vol. 55, No. 2, 2013, pp. 267-288
Identifying relevant attributes or variables is the first objective of conjoint analysis in market research.
Identifying relevant attributes or variables is the first objective of conjoint analysis in market research. As a result of technological development, today it is common for researchers to use sequential experimental methods for adjusting design factors in successive phases. In particular, in the field of consumer behaviour these models are used predominantly for assessing subjective perceptions relating to the attributes of different products with high sensorial components (e.g. food, drinks and personal care products). This paper illustrates the use of response surface methodology in conjoint experiments, allowing sequential research in which the evaluation of a choice set determines the weight of factors in the next choice set and continues until the optimum combination is achieved. To this end we have carried out a computer simulation to determine the optimal combination of ingredients for a sauce. The simulation shows that the model needs only a few steps to reach the optimal combination of ingredients. This result indicates that response surface methodology can be considered a useful tool in the field of market research and, in particular, in studies on consumer behaviour.
Putting theory into practice
Tom Vannozzi and Stephen Skippon, Market Research Society, Annual Conference, 2013
This paper shows how behavioural economics (BE) and social psychology can be incorporated into market research methodologies to reveal non-conscious or irrational drivers of consumer attitudes, behaviours and decision making.
This paper shows how behavioural economics (BE) and social psychology can be incorporated into market research methodologies to reveal non-conscious or irrational drivers of consumer attitudes, behaviours and decision making. The paper focus focuses on three specific case studies that have integrated BE knowledge frameworks into quantitative research approaches. The first case study shows how non-conscious influences of social biases (sometimes called rules of thumb, heuristics or short cuts) impact on choices made in a supposedly rational business environment. The second example explores how behaviour can be influenced by non-conscious processing of social norming messages. The third challenges the traditionally held views that attitudes are usually seen as relatively stable, by showing that attitudes can be affected by the non-conscious goals that are active in the mind.
Visual awareness: A manifesto for market research to engage with the language of images
Simon Pulman-Jones and Colin Strong, Market Research Society, Annual Conference, 2013
This paper argues the case for market researchers to use images in order to help marketers understand consumers.
This paper argues the case for market researchers to use images in order to help marketers understand consumers. More broadly, it calls for market research to recognise that the language of images must be given due recognition in the corporate world. Images form a tool for social identity through history; the digital revolution has also led, the paper argues, to society becoming increasingly image-based. But images play a limited role in the mainstream methodological repertoire of market research - and this needs to change. Such a process represents a great new opportunity for semiotics to move into a more central role within market research. The paper suggests three methodological approaches to help improve understanding of the language of images: individual, social and cultural.
Face Value: Measuring emotions without the guesswork
Graham Page, Warc Exclusive, MAP: Measuring Advertising Performance, March 2013
This presentation outlines a new, indirect measurement of responses to marketing and brands. New methods from the field of neuromarketing provide the ability to measure biometric indicators of emotion directly, but they also add to the wide array of existing methods for measuring emotion.
This presentation outlines a new, indirect measurement of responses to marketing and brands. New methods from the field of neuromarketing provide the ability to measure biometric indicators of emotion directly, but they also add to the wide array of existing methods for measuring emotion. By using automated coding of respondents' facial expressions, marketers can read their emotional responses and understand the real emotional power of television spots. These facial measures have been shown to relate to in-market performance.
Consumer Neuroscience: Application to ad effectiveness
Thom Noble, Warc Exclusive, MAP: Measuring Advertising Performance, March 2013
Ways to use neuroscience-based research techniques to measure ad effectiveness are discussed in this presentation.
Ways to use neuroscience-based research techniques to measure ad effectiveness are discussed in this presentation. Such an approach is necessary, given the importance of the subconscious in consumer decision-making. The presentation discusses the benefits of neuro ad-testing, research methods including EEG, implicit testing and eye-tracking, and suggested applications to advertising. Case studies mentioned in the presentation include projects for Fiat and FOX Sport. The presentation concludes with examples of how neuro-marketing can track ad resonance with key brand attributes - and advice on how to get the most from neuro techniques.
IJMR Young Research Writer award 2012 Winning Entry: 'Mirror, mirror on the wall, which brand is like me most of all?': Integrating consumers into brand personality measurement
Elina Halonen, International Journal of Market Research, Vol. 55, No. 1, 2013, pp. 17-24
The purpose of this research was to understand whether consumers evaluate brands with personality traits congruent with their own more positively than brands with incongruent personality traits.
The purpose of this research was to understand whether consumers evaluate brands with personality traits congruent with their own more positively than brands with incongruent personality traits. After all, brand personality is one of the most frequently used metrics in quantitative market research, based on the implicit assumption that consumers desire and purchase brands that they perceive similar to themselves, but self–brand congruency remains virtually unexplored in market research as a measurement tool. The study was conducted as an online survey in May 2012, collected from 11 countries across North America, Europe, Asia and Africa. Results showed that the degree of self–brand congruency was found to be a good predictor of levels of brand appeal across all countries studied, which suggests that brands with distinct personality traits congruent with consumers' self-concepts are evaluated more positively than brands with incongruent personality traits across cultures, particularly in more westernised and developed countries such as UK, Germany, Spain and US. This suggests that the predictive ability of commercial brand personality measurement could be considerably improved by incorporating consumers' self-evaluations into the research.
Brand measurement scales and underlying cognitive dimensions
Marco Visentin, Mariachiara Colucci and Gian Luca Marzocchi, International Journal of Market Research, Vol. 55, No. 1, 2013, pp. 43-57
The aim of this exploratory research is to compare a well-known scale, the Aaker brand personality scale, with an empirical scale based on individuals’ relevant attributes, in order to analyse why they can lead to similar brand positioning maps.
The aim of this exploratory research is to compare a well-known scale, the Aaker brand personality scale, with an empirical scale based on individuals’ relevant attributes, in order to analyse why they can lead to similar brand positioning maps. We provide empirical evidence of how a bias can overwrite the ability of a measurement scale to actually measure its underlying construct. In order to do so, we first find that the two sets of attributes – one derived from the brand personality scale, the other reflecting attributes obtained through a focus group – span common cognitive representations when translated into perceptual maps. We then prove that this outcome is caused by a bias stemming from a more holistic view of the brand, which forces the two cognitive structures towards a common perceptual representation. We conclude discussing the challenges for current theory implicit in our findings, and the implications for managerial practice.
The difference between 'less bad' and 'much better': Helping conjoint to live up to its promises by leveraging 'behavioural economics'
Florian Bauer, ESOMAR, Congress, Atlanta, September 2012
This ESOMAR paper looks at how to integrate behavioural economics insights with conjoint analysis, thereby making predictions more valid while maintaining the core advantages of conjoint analysis.
This ESOMAR paper looks at how to integrate behavioural economics insights with conjoint analysis, thereby making predictions more valid while maintaining the core advantages of conjoint analysis. More generally, the authors argue that results can only be improved by merging conjoint analysis with other research disciplines, rather than merely attempting to develop even better conjoint analysis. They also discuss a 'General Algorithm for Patching Conjoint Analyses' tool that corrects the main cognitive and motivational distortions which occur in conjoint analysis.
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