Market Segmentation Analysis: Understanding It, Doing It, and Making It Useful
by Sara Dolnicar (Author), Bettina Grün (Author), Friedrich Leisch (Author)

About the Author
Sara Dolnicar is Professor at The University of Queensland, Brisbane, Australia. Her core research interests are the improvement of market segmentation methodology and the testing and refinement of measures used in social science research. Because her key research interests are not tied to any particular application area, she has contributed to a range of different applied research areas, including sustainable tourism and tourism marketing, environmental volunteering, foster caring, and public acceptance of water alternatives and water conservation measures.
Friedrich Leisch is Professor at the University of Natural Resources and Life Sciences, Vienna, Austria. His research interests lie in statistical computing, multivariate statistics, cluster analysis, mixture models, generalized regression, biostatistics; software development, and statistical applications in life and business sciences.
Bettina Grün is Associate Professor at Johannes Kepler University, Linz, Austria. Her research focuses on mixture models, statistical computing with R, market segmentation methods, and statistical applications in tourism and marketing.   

About this book
This book offers something for everyone working with market segmentation: practical guidance for users of market segmentation solutions; organisational guidance on implementation issues; guidance for market researchers in charge of collecting suitable data; and guidance for data analysts with respect to the technical and statistical aspects of market segmentation analysis. Even market segmentation experts will find something new, including an approach to exploring data structure and choosing a suitable number of market segments, and a vast array of useful visualisation techniques that make interpretation of market segments and selection of target segments easier.
The book talks the reader through every single step, every single potential pitfall, and every single decision that needs to be made to ensure market segmentation analysis is conducted as well as possible. All calculations are accompanied not only with a detailed explanation, but also with R code that allows readers to replicate any aspect of what is being covered in the book using R, the open-source environment for statistical computing and graphics.

Table of contents
Part I Introduction
1 Market Segmentation
    1. 1 Strategic and Tactical Marketing
    1. 2 Definitions of Market Segmentation 6
    1. 3 The Benefits of Market Segmentation
    1. 4 The Costs of Market Segmentation
    References
2 Market Segmentation Analysis
    2. 1 The Layers of Market Segmentation Analysis
    2. 2 Approaches to Market Segmentation Analysis
        2. 2. 1 Based on Organisational Constraints
        2. 2. 2 Based on the Choice of (the) Segmentation Variable(s)
    2. 3 Data Structure and Data-Driven Market Segmentation Approaches
    2. 4 Market Segmentation Analysis Step-by-Step
    References
Part II Ten Steps of Market Segmentation Analysis
3 Step 1: Deciding (not) to Segment
    3. 1 Implications of Committing to Market Segmentation
    3. 2 Implementation Barriers
    3. 3 Step 1 Checklist
    References
4 Step 2: Specifying the Ideal Target Segment
    4. 1 Segment Evaluation Criteria
    4. 2 Knock-Out Criteria
    4. 3 Attractiveness Criteria
    4. 4 Implementing a Structured Process
    4. 5 Step 2 Checklist
    References
5 Step 3: Collecting Data
    5. 1 Segmentation Variables
    5. 2 Segmentation Criteria
        5. 2. 1 Geographic Segmentation
        5. 2. 2 Socio-Demographic Segmentation
        5. 2. 3 Psychographic Segmentation
        5. 2. 4 Behavioural Segmentation
    5. 3 Data from Survey Studies
        5. 3. 1 Choice of Variables
        5. 3. 2 Response Options
        5. 3. 3 Response Styles
        5. 3. 4 Sample Size
    5. 4 Data from Internal Sources
    5. 5 Data from Experimental Studies
    5. 6 Step 3 Checklist
    References
6 Step 4: Exploring Data
    6. 1 A First Glimpse at the Data
    6. 2 Data Cleaning
    6. 3 Descriptive Analysis
    6. 4 Pre-Processing
        6. 4. 1 Categorical Variables
        6. 4. 2 Numeric Variables
    6. 5 Principal Components Analysis
    6. 6 Step 4 Checklist
    References
7 Step 5: Extracting Segments
    7. 1 Grouping Consumers
    7. 2 Distance-Based Methods
        7. 2. 1 Distance Measures
        7. 2. 2 Hierarchical Methods
        7. 2. 3 Partitioning Methods
        7. 2. 4 Hybrid Approaches
    7. 3 Model-Based Methods
        7. 3. 1 Finite Mixtures of Distributions
        7. 3. 2 Finite Mixtures of Regressions
        7. 3. 3 Extensions and Variations
    7. 4 Algorithms with Integrated Variable Selection
        7. 4. 1 Biclustering Algorithms
        7. 4. 2 Variable Selection Procedure for Clustering Binary Data (VSBD)
        7. 4. 3 Variable Reduction: Factor-Cluster Analysis
    7. 5 Data Structure Analysis
        7. 5. 1 Cluster Indices
        7. 5. 2 Gorge Plots
        7. 5. 3 Global Stability Analysis
        7. 5. 4 Segment Level Stability Analysis
        7. 6 Step 5 Checklist
    References
8 Step 6: Profiling Segments
    8. 1 Identifying Key Characteristics of Market Segments
    8. 2 Traditional Approaches to Profiling Market Segments
    8. 3 Segment Profiling with Visualisations
        8. 3. 1 Identifying Defining Characteristics of Market Segments
        8. 3. 2 Assessing Segment Separation
    8. 4 Step 6 Checklist
    References
9 Step 7: Describing Segments
    9. 1 Developing a Complete Picture of Market Segments
    9. 2 Using Visualisations to Describe Market Segments
        9. 2. 1 Nominal and Ordinal Descriptor Variables
        9. 2. 2 Metric Descriptor Variables
    9. 3 Testing for Segment Differences in Descriptor Variables
    9. 4 Predicting Segments from Descriptor Variables
        9. 4. 1 Binary Logistic Regression
        9. 4. 2 Multinomial Logistic Regression
        9. 4. 3 Tree-Based Methods
    9. 5 Step 7 Checklist
    References
10 Step 8: Selecting the Target Segment(s)
    10. 1 The Targeting Decision
    10. 2 Market Segment Evaluation
    10. 3 Step 8 Checklist
    References
11 Step 9: Customising the Marketing Mix
    11. 1 Implications for Marketing Mix Decisions
    11. 2 Product
    11. 3 Price
    11. 4 Place
    11. 5 Promotion
    11. 6 Step 9 Checklist
    References
12 Step 10: Evaluation and Monitoring
    12. 1 Ongoing Tasks in Market Segmentation
    12. 2 Evaluating the Success of the Segmentation Strategy
    12. 3 Stability of Segment Membership and Segment Hopping
    12. 4 Segment Evolution
    12. 5 Step 10 Checklist
    References
A Case Study: Fast Food
    A.1 Step 1: Deciding (not) to Segment
    A.2 Step 2: Specifying the Ideal Target Segment
    A.3 Step 3: Collecting Data
    A.4 Step 4: Exploring Data
    A.5 Step 5: Extracting Segments
        A.5.1 Using k -Means
        A.5.2 Using Mixtures of Distributions
        A.5.3 Using Mixtures of Regression Models
    A.6 Step 6: Profiling Segments
    A.7 Step 7: Describing Segments
    A.8 Step 8: Selecting (the) Target Segment(s)
    A.9 Step 9: Customising the Marketing Mix
    A.10 Step 10: Evaluation and Monitoring
B R and R Packages
    B.1 What Is R?
        B.1.1 A Short History of R
        B.1.2 R Packages
        B.1.3 Quality Control
        B.1.4 User Interfaces for R
    B.2 R Packages Used in the Book
        B.2.1 MSA
        B.2.2 flexclust
        B.2.3 flexmix
        B.2.4 Other Packages
C Data Sets Used in the Book
    C.1 Tourist Risk Taking
    C.2 Winter Vacation Activities
    C.3 Australian Vacation Activities
    C.4 Australian Travel Motives
    C.5 Fast Food

Series: Management for Professionals
Length: 324 pages
Publisher: Springer; 1st ed. 2018 edition (July 21, 2018)
Language: English
ISBN-10: 9811088179
ISBN-13: 978-9811088179

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