The Handbook of Marketing Research: Uses, Misuses, and Future AdvancesRajiv Grover, Marco Vriens "The handbook addresses different aspects and ways of delivering insights in four sections. The first part of the book focuses on the insights topic. It addresses what kind of information could be believed as insights by clients; how such insights can be generated by individual marketing researchers as trusted advisors at the project level; and how insights can be routinely produced at the marketing research organizational level. The second part of the book discusses techniques of gathering accurate data that is capable of yielding insights. It presents traditional quantitative data gathering techniques, innovative qualitative techniques as well as emerging online methods. It also details how accuracy and representativeness of data can be ensured through minimization of response bias, utilization of proper sampling techniques, weighting of data, and appropriate treatment of missing data. Part three of the book is devoted to data analysis. Starting with basic data analysis techniques, the section presents advanced analytics techniques which have a greater chance of producing market insights. These include models such as Logit, Tobit, Probit, Conjoint, Discrete Choice, Latent Structure Regression, Structural Equation, Hazard/Survival, Hierarchical Bayes, and Data Mining. This section also includes a chapter on the basic philosophy of mathematical and statistical models and their use in marketing for decision support systems. The final part of the book takes a different approache to marketing research. It is structured based on the substantial marketing issues that clients would be interested in resolving through marketing research. This part has topics on modeling and testing advertising and other marketing mix variables, and conceptualization and measurement of segmentation, brand equity, satisfaction, customer lifetime value, and marketing ROI. The section concludes with chapters on international marketing research and marketing management support system." -- BACK COVER. |
Contents
How It Helps Lay the Foundations for Insights | 3 |
Structuring Market Research | 18 |
What Do Really Good Managers | 33 |
Questionnaire Design and Scale Development | 83 |
Response Biases in Marketing Research | 95 |
Online Marketing Research | 110 |
Advanced Techniques and Technologies in Online Research | 132 |
Sampling and Weighting | 159 |
Latent Structure Regression | 394 |
Hierarchical Bayes Models | 418 |
HazardSurvival Models in Marketing | 441 |
An Introduction to Data Mining | 455 |
Ad Testing | 487 |
Modeling Marketing Mix | 506 |
A Guide to the Design and Execution of Segmentation Studies | 523 |
Measuring Brand Equity | 546 |
Dealing With Missing Data in Surveys and Databases | 178 |
Basic Data Analysis | 195 |
The Marketing Engineering Approach | 230 |
Using Regression to Answer What If | 255 |
Advanced Regression Models | 267 |
Understanding Consumer Decision Making | 288 |
Construction of Efficient Designs for Discrete Choice Experiments | 312 |
Structural Equation Modeling | 330 |
Cluster Analysis and Factor Analysis | 365 |
Customer Satisfaction Research | 569 |
Measuring Customer Equity and Calculating Marketing ROI | 588 |
Customer Lifetime Value | 602 |
International Marketing Research | 628 |
Marketing Management Support Systems | 646 |
669 | |
679 | |
About the Editors | 699 |
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Common terms and phrases
advertising alternative approach associated attributes average Bayesian behavior brand equity chi-square choice design choice sets client cluster coefficients conjoint analysis consumers correlation covariance customer equity customer lifetime value data mining data set dependent variable developed discussed distribution effects Equation estimates evaluate example factors feature Figure firm focus groups function heterogeneity identify important individual insights interaction Internet interviews JCPenney Journal of Marketing latent likelihood linear linear regression logit managers marketing decision marketing research matrix means measure ment mental model methods missing data mixture models multinomial logit multiple observed online panels optimal parameters potential predictive probability problem profit purchase qualitative questionnaire questions random refers relationship respondents sample scale scores segments selection solution specific standard errors statistical strategy structural equation modeling structure sumers Table techniques tion types variance weights
Popular passages
Page 567 - It is a judgement that a product or service feature, or the product or service itself, provided (or is providing) a pleasurable level of consumption-related fulfillment, including levels of under- or overfulfillment.