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• Cover Page
• Title Page
• Copyright Page
• Brief contents
• Contents
• Preface
• Publisher’s acknowledgements
• About the authors
• 1 Introduction to marketing research and insight
• Objectives
• Overview
• What does ‘marketing research’ mean?
• Marketing research in context
• Definition of marketing research
• The global marketing research industry
• Justifying the investment in marketing research
• The future – addressing the marketing research skills gap
• Summary
• Questions
• Exercises
• Notes
• 2 Defining the research problem and developing a research approach
• Objectives
• Overview
• Importance of defining the research problem
• The marketing research brief
• Components of the marketing research brief
• The marketing research proposal
• The process of defining the problem and developing a research approach
• Environmental context of the problem
• Discussions with decision makers
• Interviews with industry experts
• Initial secondary data analyses
• Marketing decision problem and marketing research problem
• Defining the marketing research problem
• Components of the research approach
• Objective/theoretical framework
• Research questions
• Hypothesis
• Summary
• Questions
• Exercises
• Notes
• 3 Research design
• Objectives
• Overview
• Research design definition
• Research design from the decision makers’ perspective
• Research design from the participants’ perspective
• Research design classification
• Descriptive research
• Causal research
• Relationships between exploratory, descriptive and causal research
• Potential sources of error in research designs
• Summary
• Questions
• Exercises
• Notes
• 4 Secondary data collection and analysis
• Objectives
• Overview
• Defining primary data, secondary data and marketing intelligence
• Advantages and uses of secondary data
• Disadvantages of secondary data
• Criteria for evaluating secondary data
• Classification of secondary data
• Published external secondary sources
• Databases
• Classification of online databases
• Syndicated sources of secondary data
• Syndicated data from households
• Syndicated data from institutions
• Summary
• Questions
• Exercises
• Notes
• 5 Internal secondary data and analytics
• Objectives
• Overview
• Internal secondary data
• Geodemographic data analyses
• Customer relationship management
• Big data
• Web analytics
• Linking different types of data
• Summary
• Questions
• Exercises
• Notes
• 6 Qualitative research: its nature and approaches
• Objectives
• Overview
• Primary data: qualitative versus quantitative research
• Rationale for using qualitative research
• Philosophy and qualitative research
• Ethnographic research
• Grounded theory
• Action research
• Summary
• Questions
• Exercises
• Notes
• 7 Qualitative research: focus group discussions
• Objectives
• Overview
• Classifying qualitative research techniques
• Focus group discussion
• Planning and conducting focus groups
• The moderator
• Other variations of focus groups
• Other types of qualitative group discussions
• Misconceptions about focus groups
• Online focus groups
• Advantages of online focus groups
• Disadvantages of online focus groups
• Summary
• Questions
• Exercises
• Notes
• 8 Qualitative research: in-depth interviewing and projective techniques
• Objectives
• Overview
• In-depth interviews
• Projective techniques
• Comparison between qualitative techniques
• Summary
• Questions
• Exercises
• Notes
• 9 Qualitative research: data analysis
• Objectives
• Overview
• The qualitative researcher
• The process of qualitative data analysis
• Grounded theory
• Content analysis
• Semiotics
• Qualitative data analysis software
• Summary
• Questions
• Exercises
• Notes
• 10 Survey and quantitative observation techniques
• Objectives
• Overview
• Survey methods
• Online surveys
• Telephone surveys
• Face-to-face surveys
• A comparative evaluation of survey methods
• Other survey methods
• Mixed-mode surveys
• Observation techniques
• Observation techniques classified by mode of administration
• A comparative evaluation of the observation techniques
• Advantages and disadvantages of observation techniques
• Summary
• Questions
• Exercises
• Notes
• 11 Causal research design: experimentation
• Objectives
• Overview
• Concept of causality
• Conditions for causality
• Definitions and concepts
• Definition of symbols
• Validity in experimentation
• Extraneous variables
• Controlling extraneous variables
• A classification of experimental designs
• Pre-experimental designs
• True experimental designs
• Quasi-experimental designs
• Statistical designs
• Laboratory versus field experiments
• Experimental versus non-experimental designs
• Application: test marketing
• Summary
• Questions
• Exercises
• Notes
• 12 Measurement and scaling: fundamentals, comparative and non-comparative scaling
• Objectives
• Overview
• Measurement and scaling
• Scale characteristics and levels of measurement
• Primary scales of measurement
• A comparison of scaling techniques
• Comparative scaling techniques
• Non-comparative scaling techniques
• Itemised rating scales
• Itemised rating scale decisions
• Multi-item scales
• Scale evaluation
• Choosing a scaling technique
• Mathematically derived scales
• Summary
• Questions
• Exercises
• Notes
• 13 Questionnaire design
• Objectives
• Overview
• Questionnaire definition
• Questionnaire design process
• Specify the information needed
• Specify the type of interviewing method
• Determine the content of individual questions
• Overcoming the participant’s inability and unwillingness to answer
• Choose question structure
• Choose question wording
• Arrange the questions in proper order
• Identify the form and layout
• Reproduce the questionnaire
• Eliminate problems by pilot-testing
• Summarising the questionnaire design process
• Designing surveys across cultures and countries
• Summary
• Questions
• Exercises
• Notes
• 14 Sampling: design and procedures
• Objectives
• Overview
• Sample or census
• The sampling design process
• A classification of sampling techniques
• Non-probability sampling techniques
• Probability sampling techniques
• Choosing non-probability versus probability sampling
• Summary of sampling techniques
• Issues in sampling across countries and cultures
• Summary
• Questions
• Exercises
• Notes
• 15 Sampling: determining sample size
• Objectives
• Overview
• Definitions and symbols
• The sampling distribution
• Statistical approaches to determining sample size
• The confidence interval approach
• Multiple characteristics and parameters
• Other probability sampling techniques
• Adjusting the statistically determined sample size
• Calculation of response rates
• Non-response issues in sampling
• Summary
• Questions
• Exercises
• Notes
• 16 Survey fieldwork
• Objectives
• Overview
• The nature of survey fieldwork
• Survey fieldwork and the data-collection process
• Selecting survey fieldworkers
• Training survey fieldworkers
• Recording the answers
• Supervising survey fieldworkers
• Evaluating survey fieldworkers
• Fieldwork and online research
• Fieldwork across countries and cultures
• Summary
• Questions
• Exercises
• Notes
• 17 Social media research
• Objectives
• Overview
• What do we mean by ‘social media’?
• The emergence of social media research
• Approaches to social media research
• Accessing social media data
• Social media research methods
• Research with image and video data
• Limitations of social media research
• Summary
• Questions
• Exercises
• Notes
• 18 Mobile research
• Objectives
• Overview
• What is a mobile device?
• Approaches to mobile research
• Guidelines specific to mobile marketing research
• Key challenges in mobile research
• Summary
• Questions
• Exercises
• Notes
• 19 Data integrity
• Objectives
• Overview
• The data integrity process
• Checking the questionnaire
• Editing
• Coding
• Transcribing
• Cleaning the data
• Statistically adjusting the data
• Selecting a data analysis strategy
• Data integrity across countries and cultures
• Practise data analysis with SPSS
• Summary
• Questions
• Exercises
• Notes
• 20 Frequency distribution, cross-tabulation and hypothesis testing
• Objectives
• Overview
• Frequency distribution
• Statistics associated with frequency distribution
• A general procedure for hypothesis testing
• Cross-tabulations
• Statistics associated with cross-tabulation
• Hypothesis testing related to differences
• Parametric tests
• Non-parametric tests
• Practise data analysis with SPSS
• Summary
• Questions
• Exercises
• Notes
• 21 Analysis of variance and covariance
• Objectives
• Overview
• Relationship among techniques
• One-way ANOVA
• Statistics associated with one-way ANOVA
• Conducting one-way ANOVA
• Illustrative applications of one-way ANOVA
• n-way ANOVA
• Analysis of covariance (ANCOVA)
• Issues in interpretation
• Repeated measures ANOVA
• Non-metric ANOVA
• Multivariate ANOVA
• Practise data analysis with SPSS
• Summary
• Questions
• Exercises
• Notes
• 22 Correlation and regression
• Objectives
• Overview
• Product moment correlation
• Partial correlation
• Non-metric correlation
• Regression analysis
• Bivariate regression
• Statistics associated with bivariate regression analysis
• Conducting bivariate regression analysis
• Multiple regression
• Statistics associated with multiple regression
• Conducting multiple regression analysis
• Multicollinearity
• Relative importance of predictors
• Cross-validation
• Regression with dummy variables
• Analysis of variance and covariance with regression
• Practise data analysis with SPSS
• Summary
• Questions
• Exercises
• Notes
• 23 Discriminant and logit analysis
• Objectives
• Overview
• Basic concept of discriminant analysis
• Relationship of discriminant and logit analysis to ANOVA and regression
• Discriminant analysis model
• Statistics associated with discriminant analysis
• Conducting discriminant analysis
• Conducting multiple discriminant analysis
• Stepwise discriminant analysis
• The logit model
• Conducting binary logit analysis
• Practise data analysis with SPSS
• Summary
• Questions
• Exercises
• Notes
• 24 Factor analysis
• Objectives
• Overview
• Basic concept
• Factor analysis model
• Statistics associated with factor analysis
• Conducting factor analysis
• Applications of common factor analysis
• Practise data analysis with SPSS
• Summary
• Questions
• Exercises
• Notes
• 25 Cluster analysis
• Objectives
• Overview
• Basic concept
• Statistics associated with cluster analysis
• Conducting cluster analysis
• Applications of non-hierarchical clustering
• Applications of TwoStep clustering
• Clustering variables
• Practise data analysis with SPSS
• Summary
• Questions
• Exercises
• Notes
• 26 Multidimensional scaling and conjoint analysis
• Objectives
• Overview
• Basic concepts in MDS
• Statistics and terms associated with MDS
• Conducting MDS
• Assumptions and limitations of MDS
• Scaling preference data
• Correspondence analysis
• Relationship among MDS, factor analysis and discriminant analysis
• Basic concepts in conjoint analysis
• Statistics and terms associated with conjoint analysis
• Conducting conjoint analysis
• Assumptions and limitations of conjoint analysis
• Hybrid conjoint analysis
• Practise data analysis with SPSS
• Summary
• Questions
• Exercises
• Notes
• 27 Structural equation modelling and path analysis
• Objectives
• Overview
• Basic concepts in SEM
• Statistics and terms associated with SEM
• Foundations of SEM
• Conducting SEM
• Higher-order CFA
• Relationship of SEM to other multivariate techniques
• Application of SEM: first-order factor model
• Application of SEM: second-order factor model
• Path analysis
• Software to support SEM
• Summary
• Questions
• Exercises
• Notes
• 28 Communicating research findings
• Objectives
• Overview
• Why does communication of research findings matter?
• Importance of the report and presentation
• Preparation and presentation process
• Report preparation
• Guidelines for graphs
• Report distribution
• Digital dashboards
• Infographics
• Oral presentation
• Research follow-up
• Summary
• Questions
• Exercises
• Notes
• 29 Business-to-business (b2b) marketing research
• Objectives
• Overview
• What is b2b marketing and why is it important?
• The distinction between b2b and consumer marketing
• Concepts underlying b2b marketing research
• Implications of the differences between business and consumer purchases for researchers
• The growth of competitive intelligence
• The future of b2b marketing research
• Summary
• Questions
• Exercises
• Notes
• 30 Research ethics, privacy and trust
• Objectives
• Overview
• Ethics in marketing research
• Professional ethics codes
• Ethics in the research process
• Ethics in data collection
• Data analysis
• Ethical communication of research findings
• Key issues in research ethics: informed consent
• Key issues in research ethics: maintaining respondent trust
• Key issues in research ethics: anonymity and privacy
• Key issues in research ethics: sugging and frugging
• Summary
• Questions
• Exercises
• Notes
• Glossary
• Subject Index
• Name Index
• Index of Organisations