MR_Chap002

Chapter 02: The Marketing Research Process and Proposals

Value of the Research Process

• Business owners and managers often identify problems needing solutions.

• Additional information is often required.

• A solution is a marketing research study based on a scientific research process.

Changing View of the Marketing Research Process

• The internet and big data have the most significant influence on marketing research.

• Types of Data:

  • Secondary Data: Previously collected data for another problem.

  • Primary Data: Specifically collected data for current issues.

  • Big Data: Unstructured secondary data stored in warehouses.

• Advances in technologies present challenges for marketers.

• Global expansion introduces cultural issues, repositioning marketing research in strategy development.

• The information research process involves: collecting, analyzing, interpreting, and transforming data into decision-making information.

Determining the Need for Information Research

• Situations when research might not be necessary include:

  • Insufficient time frames.

  • Inadequate resources.

  • Costs outweigh benefits.

  • Utilizing existing information and managerial judgment may be sufficient.

  • Availability of information in internal record systems.

  • Possibility to conduct necessary research within the time frame.

  • Assessing whether benefits justify costs or if it gives competitors too much strategic information.

Overview of the Research Process

• The research process comprises 11 steps:

  1. Identify and clarify information needs.

  2. Define research questions.

  3. Specify research objectives and confirm information value.

  4. Determine research design and data sources.

  5. Develop sampling design and sample size.

  6. Examine measurement issues and scales.

  7. Design and pretest questionnaire.

  8. Collect and prepare data.

  9. Analyze data.

  10. Interpret data to create knowledge.

  11. Prepare and present the final report.

• The steps follow the scientific method.

The Research Process: Transforming Data into Knowledge

• Primary goal: Provide decision-makers with knowledge to resolve issues or take advantage of opportunities.

• Data transforms into knowledge through interpretation and meaning.

• Considerations include complexity, urgency, costs of alternatives, and clarification of information needs.

Step 1: Determine the Research Problem—Identify and Clarify Information Needs

• Agree on the decision maker's purpose for research.

• Iceberg Principle: Decision makers perceive only 10% of the true problem.

• Conduct a situation analysis to uncover complexity.

• Identify measurable symptoms, separating causes from symptoms.

• Select a unit of analysis for direction and determine relevant variables.

Exhibit 2.4: The Iceberg Principle

• Decision Problem Definition Examples:

  • Obvious symptoms: Loss of sales, low traffic, decreased market share, unhappy customers.

  • Real Problems: Marginal sales force performance, inappropriate delivery systems, unethical customer treatment, low-quality products, poor image.

Step 2: Define the Research Questions

• Redefine initial problems as research questions through literature review.

• Consider the types of data required to answer these questions, including:

  • New data requirements.

  • Existing data quality and availability.

  • Necessity of the information requested.

Exhibit 2.6: Initial and Redefined Research Questions for Lowe's

• Initial Research Question: Do our marketing strategies need modification to increase satisfaction?

• Redefined Questions Include:

  • What aspects of operations influence customers?

  • How do customers assess Lowe's retail outlets?

  • What are the perceived strengths and weaknesses compared to competitors?

  • Demographic and psychographic profiles of Lowe's customers.

Step 3: Specify Objectives and Confirm Information Value

• Objectives stem from research questions.

• Objectives guide subsequent steps.

• Best judgment needed to ascertain:

  • Feasibility of information collection.

  • New insights provided by the information.

  • Overall benefits from the information obtained.

Step 4: Select the Research Design

• Exploratory Research: Generate insights and understand consumer behaviors.

• Descriptive Research: Collect quantitative data (e.g., satisfaction surveys).

• Predictive Research: Compare variables to understand impacts.

• Data sources depend on:

  • Existence of data.

  • Original reasons for data collection.

Step 5: Develop the Sampling Design and Sample Size

• Identify target population for research.

• Census: Attempt to analyze the entire population.

• Use representative samples for large populations; sampling plans can be:

  • Probability Sampling: Known selection chance, facilitates assessment of sampling error.

  • Non-probability Sampling: Cannot measure sampling error.

• Sample size influences accuracy and generalizability of results.

Step 6: Examine Measurement Issues and Scales

• Identify concepts and measures related to the research problem.

• Important to determine:

  • Definitions and measurements of variables.

  • Use of single or multi-item measures.

• Understanding measurement issues is vital for both primary and secondary research.

Step 7: Design and Pretest the Questionnaire

• Select appropriate question types and sequences.

• Pretesting assesses:

  • Clarity of instructions and questions.

  • Topic sequence.

  • Issues causing confusion.

Step 8: Collect and Prepare Data

• Data collection methods:

  • Interviewers or self-completed questionnaires.

  • Observation of individuals or phenomena.

• Ensure accuracy before analysis by transferring data to files and checking for errors.

Step 9: Analyze Data

• Analysis can vary in complexity:

  • Simple frequency distributions.

  • Summary statistics (mean, median, mode).

  • Multivariate analysis or advanced analytics (e.g., machine learning).

• Enables hypothesis testing, data quality evaluation, and examination of cause-effect relationships.

Step 10: Interpret Data to Create Knowledge

• Interpretation integrates findings into conclusions that answer research questions.

• Visualization tools help convey data analytics insights effectively.

Step 11: Prepare and Present the Final Report

• Typical sections of a research report include:

  • Executive summary.

  • Introduction.

  • Problem definition and objectives.

  • Methodology.

  • Results and findings.

  • Limitations of the study.

• Reports may be provided both in written form and as oral presentations.

Develop a Research Proposal

• A research proposal outlines the research framework for decision-makers.

• Key elements of a research proposal include:

  • Purpose of the research.

  • Type of study.

  • Target population and sample size.

  • Design and data collection methods.

  • Specific research instruments.

  • Managerial benefits of the study.

  • Estimated project costs.

  • Research company profile.

  • Potential example tables for projected results.