Unit 3 : Marketing Research : MARKETING RESEARCH DESIGN AND SAMPLING

What is a Research Design?

A research plan that specifies the procedures for collecting and analyzing data necessary to identify or react to a problem or opportunity.

Key Functions:

• Ensures collected information is relevant, objective, and economical.

• Guarantees smooth research execution while establishing reliability and validity.

• Outlines decisions regarding info sources, data collection methods, sampling plans, and analytical tools.

What are the Characteristics of a Good Research Design?

1. Reliability: Consistency, dependability, and stability—produces the same results when using identical tools on the same sample.

2. Objectivity: Examines evidence independently without personal bias, beliefs, emotions, or perceptions.

3. Validity: Ensures the integrity of conclusions; tests data to make accurate future predictions.

4. Generalization: Allows findings from a small sample to represent the entire target population.

What are the 8 Components of a Research Design?

1. Type of Investigation: Informal exploratory design vs. comprehensive conclusive/experimental design.

2. Sources of Information: Identifying specific data needs and primary/secondary sources.

3. Type of Survey: Large-scale consumer profile survey vs. limited-scale concept test.

4. Sampling: Determining sample size and selecting appropriate sampling methods.

5. Data Gathering Instruments: Observation checklists, cameras, recorders, questionnaires, or interview guidelines.

6. Data Collection Procedure: Field management, monitoring, and supervising interviewers and field officers.

7. Data Preparation Process: Editing (ensuring logical consistency), coding (categorizing responses), data entry, and tabulation.

8. Data Analysis Tools and Methods: Selecting statistical techniques to draw inferences from frequency tables.

What are the Types of Research Design?

• 1. Qualitative Research Design (Exploratory):

  • Investigates qualitative phenomena like motivation, perception, and attitudes.

  • Unstructured, informal, highly flexible, and deeply probes mindset.

• 2. Quantitative Research Design (Descriptive):

  • Describes quantifiable phenomena (e.g., user characteristics, age/income variations, ad awareness).

  • Based on large scale samples to check validity of existing theories.

  • Steps: Formulate objectives - Define population & sample - Design collection method - Analyze data.

Primary vs. Secondary Sources of Data

• 1. Primary Data Sources: Developed by the researcher specifically for the current study (Interviews, Questionnaires, Observations).

• 2. Secondary Data Sources: Information gathered by someone else for another purpose:

  • Published: Government reports, international organization publications, private publications.

  • Unpublished: Office records, hospital/school records, student dissertations.

  • Computerized Databases: Online (central bank network) or offline electronic data.

What are the 6 Methods of Collecting Primary Data?

1. Direct Personal Investigation (Observation): Direct observation by researcher; reliable for confidential topics, but costly and prone to investigator bias.

2. Indirect Oral Investigation: Interviews third parties (used for sensitive areas like addiction/diseases); extensive scope but risk of twisted facts.

3. Telephone Interview: Quick, saves time and money, but restricted to telephone owners with limited response time.

4. Local Correspondents (Channel Agency): Local agents send info to head office; cheap and widespread but lower accuracy.

5. Schedule / Questionnaire through Enumerators: Trained fieldworkers visit respondents with schedules; high response rate but expensive and time-consuming.

6. Mailed Questionnaire: Low cost, wide coverage, no interviewer bias, but suffers high non-response and incomplete answers.

Qualitative Data Collection Techniques

1. Interview: In-person or phone; formal/informal with open ended questions.

2. Observation: Evaluates dynamic real-time behaviors via checklists or video.

3. Focus Group: Facilitated group interview with common individuals to analyze thematic perspectives.

4. Ethnographies, Oral History & Case Studies: Examines single phenomena/people in natural settings.

5. Documents & Records: Reviews existing databases, meeting minutes, and financial logs.

What are the Key Analytical Techniques in Marketing Research?

1. Regression Analysis: Examines direct effects of one or more independent variables on a dependent outcome variable.

2. Grouping Method (Discriminant Analysis): Classifies observations into meaningful categories (e.g., distinguishing families seeking subsidies vs. those who don't).

3. Multiple Equation Model: Extension of regression to analyze causal pathways:

1. Path Analysis: Diagram showing direct and indirect routes between variables.

2. Structural Equation Modeling (SEM): Expands path analysis by allowing multiple indicators per variable.

What is Population vs. Sample, and Why Sample?

• Population: The entire collection of all observations of interest (e.g., all graduates, all NEPSE-listed service companies).

• Sample: A representative portion of the target population selected for study. 3 Reasons to Sample:

  1. Cost: Reduces heavy expenditure of census research.

  2. Time: Substantially reduces collection and analysis time.

  3. Accuracy: Better supervision, interviewing, and investigation of missing data compared to census.

What are the 6 Steps in the Sampling Process?

1. Define the Population: Specify target elements, units, extent, and time frame.

2. Specify Sampling Frame: Locate the master list (e.g., telephone directory, city registry).

3. Specify Sampling Unit: Choose unit level (e.g., household, city block, company).

4. Determine Sample Size: Select the specific number of elements to sample.

5. Prepare Sampling Plan: Define operational procedures for selecting units.

6. Select the Sample: Execute office and fieldwork activities to gather respondents.

Basic Sampling Terminology

1. Sampling Frame: Master list identifying each unit in the study population (e.g., directory, student list).

2. Sampling Unit: The individual element (person, institution) chosen as the selection basis.

3. Sample Statistics: Data values obtained directly from respondents in the sample.

4. Population Parameters: Population characteristics/means estimated from sample statistics.

What are the Types of Probability Sampling?

1. Simple Random Sampling: Every element in the population has an equal chance of being selected.

2. Systematic Sampling: Every $n$-th element is selected starting from a random point in the frame.

3. Stratified Sampling: Population is divided into meaningful sub-groups (strata), and samples are drawn proportionally.

4. Cluster Sampling: Heterogeneous groups are identified; entire groups are chosen at random to study members.

What are the Types of Non-Probability Sampling?

1. Purposive / Judgmental Sampling: Subjects selected specifically based on expert knowledge/experience.

2. Quota Sampling: Convenient selection of subjects to meet pre-determined demographic quotas.

3. Convenience Sampling: Selection of the most easily accessible population members.

4. Self Selecting Sampling: Samples formed by individuals voluntarily choosing to respond.

5. Snowball Sampling: Initial respondents refer additional respondents, creating a referral chain.