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Data mining and market intelligence : implications for decision making

Author: Mustapha Akinkunmi
Publisher: [San Rafael, California] : Morgan & Claypool Publishers, [2018] ©2018
Series: Synthesis lectures on engineering, #30.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This book is written to address the issues relating to data gathering, data warehousing, and data analysis, all of which are useful when working with large amounts of data. Using practical examples of market intelligence, this book is designed to inspire and inform readers on how to conduct market intelligence by leveraging data and technology, supporting smart decision making. The book explains some suitable  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Mustapha Akinkunmi
ISBN: 9781681733210 1681733218
OCLC Number: 1033620112
Description: 1 online resource (xxii, 159 pages) : illustrations
Contents: 1. Introduction to market intelligence --
1.1 Understanding the link between marketing insights and decision making --
1.2 Transform data into insights for decisions: segmentation, positioning, product development, etc. --
1.3 Market intelligence tools --
1.4 Scientific method and technology of marketing research --
1.5 Innovative solutions to real-life issues --
1.6 Designing the research methodology, questionnaire, sampling plan, and data analysis --
1.7 Turning data into strategic insights --
1.8 Exercises 2. The market research process --
2.1 The marketing research framework and process --
2.2 Research problems and correct design techniques --
2.3 Data collection methods --
2.4 Generating marketing insights --
2.5 Exercises 3. Qualitative techniques --
3.1 Self-administered method --
3.2 Personal interview or face-to-face method --
3.3 Exercises 4. Quantitative techniques --
4.1 Data preparation and descriptive statistics --
4.2 Fundamentals of quantitative methods and their applications --
4.3 Concept of distribution pattern, central tendency, and dispersion --
4.3.1 Distribution pattern --
4.3.2 Measure of central tendency --
4.3.3 Measure of dispersion --
4.4 Construction of confidence intervals --
4.4.1 Application of confidence intervals --
4.5 Other descriptive statistics --
4.5.1 Skewness --
4.5.2 Kurtosis --
4.6 Exercises 5. Hypothesis testing and regression analysis --
5.1 Data preparation and evaluation for quantitative analysis --
5.2 Constructing and testing data hypotheses --
5.3 Regression analysis: concept and applications (interpret data relationships and forecasting) --
5.3.1 Assumptions of linear regression --
5.3.2 Simple linear regression --
5.3.3 Multiple regression --
5.3.4 Assumptions of multiple regression --
5.4 Exercises 6. Analyzing survey data --
6.1 Quantitative technique of collecting survey data: consumer expenditure survey --
6.2 Types of measurement scales and their applications --
6.3 Survey research rigor --
6.4 Testing data quality: survey error detection procedures --
6.5 Exercises 7. Index methodology --
7.1 Bra expectation index: principles, techniques, and applications --
7.1.1 Objectives of bra expectation index --
7.1.2 Methodology --
7.1.3 Calculation of bra expectation index --
7.2 Bra consumer confidence index: principles, techniques, and applications --
7.2.1 Components of braCCI --
7.2.2 Methodology --
7.2.3 Illustrative example --
7.2.4 Index maintenance --
7.3 BraIndex: principles, techniques, and applications --
7.3.1 Basic criteria for selection of constituent stocks --
7.3.2 Technical criteria --
7.3.3 Fundamental selection criteria --
7.3.4 Corporate event --
7.3.5 Stock splits adjustment barometer --
7.3.6 Free-float --
7.3.7 Calculation of braIndex --
7.3.8 Illustrative example --
7.3.9 Measure of braIndex volatility --
7.3.10 Index maintenance --
7.4 Bra producer price index: principles, techniques, and applications --
7.4.1 Uses of braPPI --
7.4.2 Components of braPPI --
7.4.3 Scope and coverage --
7.4.4 Collection of data --
7.4.5 Index calculation --
7.4.6 Illustrative example --
7.5 Bra bond index: principles, techniques, and applications --
7.5.1 Definition of terms --
7.5.2 Basic criteria for constituent bonds --
7.5.3 Index calculation --
7.5.4 Sub-indices --
7.5.5 Illustrative example --
7.6 BraInflation index: principles, techniques, and applications --
7.6.1 Uses of bra inflation index --
7.6.2 Classification of braII items --
7.6.3 Period of the survey --
7.6.4 Data collection, collation, and processing --
7.6.5 Quality adjustment --
7.6.6 Index calculation --
7.6.7 Bra inflation indices publication --
7.6.8 Expenditure category weight --
7.6.9 Illustrative example --
7.7 Exercises 8. Digital media monitoring, measurement, and modeling --
8.1 Understandings of social media monitoring, measurement, and modeling --
8.2 Strategic insight of social media monitoring --
8.3 Social media measurement --
8.4 Social media modeling --
8.5 Exercises 9. Causal methods --
9.1 Marketing mix modeling: concept, principles, methods, and applications --
9.2 Effective communication of research, intelligence, and analytic insights --
9.3 Exercises 10. Mobile data mining --
10.1 Concept of mobile data mining --
10.2 Activities of mobile data mining --
10.3 Architecture of mobile data mining --
10.4 Algorithms of mobile data mining --
10.5 Application of mobile data mining --
10.6 Exercises A. Questionnaires, items survey, and weights of elementary items --
Sample of business expectation survey questionnaire --
List of items survey monthly --
Weights of some items --
Bibliography --
Author's biography.
Series Title: Synthesis lectures on engineering, #30.
Responsibility: Mustapha Akinkunmi.
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Abstract:

Addresses issues relating to data gathering, data warehousing, and data analysis. Using practical examples of market intelligence, this book informs readers on how to conduct market intelligence by  Read more...

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