Marketing Research with R and Python

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This book is meant for readers with little or no experience in programming in R and Python, who wish to quickly learn what is necessary, and be able to conduct marketing research by running tests easily in R or Python.A number of marketing research textbooks have been using SPSS or SAS for many years. Conversely, R and Python can be downloaded and installed in a personal computer for free. Instructors and students do not have to go to a computer room in a university to use SPSS or SAS anymore. Instead, students can run R or Python on their personal computers.For any company, growth comes either from organic growth of existing products, or from launching successful new products. Due to competition in the marketplace, each company's marketer must determine whether or not it is time to develop and launch a new product: This book covers important frameworks and concepts of marketing research for developing a new product

Author(s): Howard Pong-Yuen Lam
Publisher: World Scientific Publishing
Year: 2023

Language: English
Pages: 297

Contents
Preface
About the Author
Acknowledgments
Chapter 1. Marketing
Marketing as Exchange
Consumers, Customers, Company, Competitors, Collaborators, Context
Segmentation, Target, Positioning
Branding Strategy
References
Chapter 2. Marketing Research or Not
The Problem
Shampoo Promotion Example
Chocolate Bar Upsize Example
Reference
Chapter 3. Marketing Research Process
Creating a Sustainable Advantage
Multiple Attributes
Positioning Map
Qualitative Research
Quantitative Research
References
Chapter 4. Measurement and Scaling 25Nominal Scale
Nominal Scale
Ordinal Scale
Interval Scale
Ratio Scale
Number of Points in a Scale
Scale with Multiple Items
References
Chapter 5. Questionnaire
Mutually Exclusive
Completely Exhaustive
Age
Nationality
Frequency
Satisfaction
Two Questions Instead of One Question
Comparison
Opening Paragraphs
Questionnaire Structure
Product Concept
Entity mindset with neutral attribute framing
Entity mindset with reduced negative attribute framing
Incremental mindset with reduced negative attribute framing
Questionnaire — Product Concept Test
References
Chapter 6. Analysis of Variance
Variance Test
Analysis of Variance
References
Chapter 7. Correlation
Chapter 8. Regression
Bivariate Regression
Values of a and b for Y = a + bX
Significance Testing
Multiple Regression
References
Appendix 1: Hierarchical Branding Strategy for New Product Launch: Evidence from China
1. Introduction
2. Name Translation Methods
2.1. Product branding strategy
2.2. Corporate branding strategy
2.2.1. Monolithic corporate branding strategy/Stand-alone corporate branding strategy
2.2.2. Corporate brand name and product brand name — The same or different?
2.2.3. Composite brand — Combination of two existing brand names
2.3. Creation of suggestive corporate names
2.3.1. Suggestive corporate name — Product category
2.3.2. Suggestive corporate name — Founders
2.3.3. Suggestive corporate name — Arbitrary
2.3.4. Corporate name — What should it suggest?
3. Hypotheses Development: Improving New Product Success by Choosing the Right Branding Strategy
3.1. Discussion
4. Conclusion and Future Research
A. Appendix I — Research Hypotheses, Method, and Results
A.1. Two-level hierarchical branding strategy
A.2. Three-level hierarchical branding strategy
A.3. Method
A.3.1. Study 1
A.3.1.1. Study 1 — Procedure and measures
A.3.1.2. Study 1 — Results of the responses to a new product
A.3.2. Study 2
A.3.2.1. Study 2 — Procedure and measures
A.3.2.2. Study 2 — Results
A. Appendix II — New Product Concept in English
References
Appendix 2: Corporate Branding Strategy for New Companies in China: Lessons Learned from GoGoVan and LaLaMove
1. Introduction
2. Brief Literature Review: Corporate Branding Strategies
3. Lessons Learned from GoGoVan and LaLaMove
4. Insights, Recommendations and Research Results
5. Conclusions, Limitations and Future Research Directions
References
Appendix 3: Dual Branding Strategy for a Successful New Product Launch in China
1. Branding Strategies for New Products
1.1. Introduction
1.2. Suggestive or non-suggestive brand names
1.3. One name or two names?
2. Dual Branding for a Successful New Product Launch — The Case of Minute Maid in China
3. Insights, Recommendations, Research Results
4. Conclusions, Limitations and Future Research Directions
References
Appendix I — New product concept in English
Appendix 4: Programming in R
1. Installation
2. R Console
3. RStudio (Hello World, Comment, readline)
4. Arithmetic Operations
5. Assignment Operations
6. Functions
7. Library
8. Conditions
9. Loop
10. Read and Write File
11. Graphics-Bar Chart
12. Graphics-Pie Chart
13. Graphics-Plot
14. Graphics-Box Plot
15. Graphics-ggplot
16. Graphics-Colors
17. Word Cloud
18. String
19. Chi-Square Test
20. Correlation
21. t-test
22. Analysis of Variance
23. Regression-Bivariate
24. Regression-Multiple
25. Sentiment Analysis
26. Web Scraping
Appendix 5: Programming in Python
1. Installation
2. Python Console
3. Anaconda/Spyder (Hello World, Comment, Input)
4. Arithmetic Operations
5. Assignment Operations
6. Functions
7. Library
8. Conditions
9. Loop
10. Read and Write File
11. Graphics-Bar Chart
12. Graphics-Pie Chart
13. Graphics-Plot
14. Graphics-Box Plot
15. Graphics-Colors
16. Word Cloud
17. String
18. Chi-Square Test
19. Correlation
20. t-test
21. Analysis of Variance
22. Regression-Bivariate
23. Regression-Multiple
24. Sentiment Analysis
25. Web Scraping
Index