TY  - BOOK
AU  - Dolnicar,Sara
AU  - Grün,Bettina
AU  - Leisch,Friedrich
ED  - SpringerLink (Online service)
TI  - Market Segmentation Analysis: Understanding It, Doing It, and Making It Useful 
T2  - Management for Professionals,
SN  - 9789811088186
AV  - HF5415.2-5415.34 
U1  - 658.83 23
PY  - 2018///
CY  - Singapore
PB  - Springer Singapore, Imprint: Springer
KW  - Market research
KW  - Statistics 
KW  - Market Research/Competitive Intelligence
KW  - Statistics for Business, Management, Economics, Finance, Insurance
N1  - Part I. Introduction -- Chapter 1. Market segmentation -- Chapter 2. Market segmentation analysis -- Part II. Ten steps of market segmentation analysis -- Chapter 3. STEP 1: Deciding (not) to segment -- Chapter 4. STEP 2: Specifying the ideal target segment -- Chapter 5. STEP 3: Collecting data -- Chapter 6. STEP 4: Exploring data -- Chapter 7. STEP 5: Extracting segments -- Chapter 8. STEP 6: Profiling segments -- Chapter 9. STEP 7: Describing segments -- Chapter 10. STEP 8: Selecting (the) target segment(s) -- Chapter 11. STEP 9: Customising the marketing mix -- Chapter 12. STEP 10: Evaluation and monitoring.; Open Access
N2  - This book is published open access under a CC BY 4.0 license. This open access 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 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
UR  - https://doi.org/10.1007/978-981-10-8818-6
ER  -