1. Marketing Research: From Data to Information to Recommended Strategies. The problem: Marketers need information. Who does marketing research? Why study marketing research? The research process. 2. The Research Question: Formulation of the Problem/Opportunity. Problems versus opportunities. The problem formulation process.
Preparing an effective research request agreement. The research proposal. Research to avoid. Choosing a research supplier. 3. Exploratory, Descriptive and Causal Research Designs. Types of research design. Exploratory research designs.
Descriptive research designs. Causal research designs. Market testing. 4. Collecting Secondary Data from Inside and Outside the Firm. Secondary data versus primary data. Advantages and disadvantages of secondary data. Internal secondary data.
Components of a decision support system. External secondary data. Standardized marketing information services. 5. Collecting Primary Data by Communication. Types of primary data. Collecting data by communication versus observation. Structured versus unstructured communication.
Issues in the use of disguise. Methods of administering questionnaires. 6. Collecting Primary Data by Observation Observation research. Structured versus unstructured observation. Using disguise with observation research. Choosing a natural or contrived setting for observation. Human versus mechanical observation.
7. Asking Good Questions. Scales of measurement. Measuring attitudes and other unobservable variables. Self-report attitude scales. Other issues in designing scales. Establishing the validity and reliability of measures. 8.
Designing the Questionnaire or Observation Form. Steps in questionnaire design. Designing observation forms. 9. Planning the Sample and Sample Size. Developing the sampling plan. Nonprobability samples. Probability samples.
How big a sample do you need? 10. Data Collection: Enhancing Response Rates while Limiting Errors and Biases Importance of nonsampling errors. Types of nonsampling errors. Calculating response rates. Improving response rates. 11. Data Preparation for Analysis. Editing.
Coding. Cleaning the data. Handling missing data. 12. Analysis & Interpretation: Individual Variables Independently. Basic univariate statistics: Categorical measures. Basic univariate statistics: Continuous measures. Hypothesis testing.
Testing hypotheses about individual variables. 13. Analysis & Interpretation: Multiple Variables Simultaneously. Analyses with categorical measures. Analyses with categorical and continuous measures. Analyses with continuous measures. 14. The Research Answer: Project Findings and Strategic Recommendations.
The written research report: Writing standards. The written research report. The oral presentation. Using graphics to communicate results.