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Data mining and market intelligence : implications for decision making /

Bibliographic Details
Main Author: Akinkunmi, Mustapha (Author)
Corporate Author: Morgan & Claypool Publishers
Format: eBook
Language:English
Published: [San Rafael, California] : Morgan & Claypool, 2018.
Series:Synthesis digital library of engineering and computer science.
Synthesis lectures on engineering ; # 30.
Subjects:
Data mining.
Marketing research > Data processing.
data mining
decision making
market intelligence
market pooling
survey
Electronic books.
Online Access:Connect to the full text of this electronic book (PDF)
Table of 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
  • 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
  • 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
  • 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.