A research design is a framework that details the procedures needed to obtain information to solve marketing problems. It includes defining the needed information, designing exploratory, descriptive, or causal phases, specifying measurement and sampling procedures, and developing a data analysis plan. Research designs can be exploratory to gain insights, descriptive to characterize markets, or causal to determine relationships. Common methods include surveys, panels, and experiments.

3. Classification of Marketing Research Designs Single Cross-Sectional Design Multiple Cross-Sectional Design Fig. 3.1 Research Design Conclusive Research Design Exploratory Research Design Descriptive Research Causal Research Cross-Sectional Design Longitudinal Design

4. Exploratory & Conclusive Research Differences Objective: Character-istics: Findings /Results: Outcome: To provide insights and understanding. Information needed is defined only loosely. Research process is flexible and unstructured. Sample is small and non-representative. Analysis of primary data is qualitative. Tentative. Generally followed by further exploratory or conclusive research. To test specific hypotheses and examine relationships. Information needed is clearly defined. Research process is formal and structured. Sample is large and representative. Data analysis is quantitative. Conclusive. Findings used as input into decision making. Exploratory Conclusive Table 3.1

5. A Comparison of Basic Research Designs Objective: Characteristics: Methods: Discovery of ideas and insights Flexible, versatile Often the front end of total research design Expert surveys Pilot surveys Secondary data Qualitative research Describe market characteristics or functions Marked by the prior formulation of specific hypotheses Preplanned and structured design Secondary data Surveys Panels Observation and other data Determine cause and effect relationships Manipulation of one or more independent variables Control of other mediating variables Experiments Exploratory Descriptive Causal Table 3.2

12. Relative Advantages and Disadvantages of Longitudinal and Cross-Sectional Designs Evaluation Criteria Cross-Sectional Design Longitudinal Design Detecting Change Large amount of data collection Accuracy Representative Sampling Response bias - - - + + + + + - - Note: A “+” indicates a relative advantage over the other design, whereas a “-” indicates a relative disadvantage. Table 3.4

14. Potential Sources of Error in Research Designs Fig. 3.2 Surrogate Information Error Measurement Error Population Definition Error Sampling Frame Error Data Analysis Error Respondent Selection Error Questioning Error Recording Error Cheating Error Inability Error Unwillingness Error Total Error Non-sampling Error Random Sampling Error Non-response Error Response Error Interviewer Error Respondent Error Researcher Error