Marketing Management - Research Process

After establishing marketing requirements, we need to establish the research process. Most marketing research projects include the following steps −

  • Define the problem
  • Determine research design
  • Identify data types and sources
  • Design data collection forms and questionnaires
  • Determine sample plan and size
  • Collect the data
  • Analyze and interpret the data
  • Prepare the research report

Let us take a look at all these steps one by one.

Problem Definition

The decision-making problem faced by management must be transformed into a market research problem in the form of questions that state the information required to make the decision and shows how that information can be obtained. For example, there could be a decision problem on whether to cast a new product. The corresponding research problem might be to appraise whether the market would accept the new product.

The objective of research should be stated clearly. To ensure that the true decision problem is addressed, it is useful for the researcher to outline possible outcomes of the research results and then for the decision maker to formulate plans of action under each scenario. The use of such outcomes can assure that the purpose of the research is agreed upon before it commences.

Research Design

After defining the issue in marketing research, we need to determine the research design. Marketing research can further be categorized into three following categories −

Exploratory research

This has the goal of formulating problems more specifically, clarifying concepts, and collecting explanations, gaining insight, removing impractical ideas, and forming hypotheses.

Descriptive research

This is firmer than exploratory research and seeks to specify in brief uses of a product, determine the proportion of the population that uses a product, or predict future demand for a product.

Causal research

This explores to search for cause and effect relationships between variables. It completes this goal through laboratory and field experiments.

Any one of the above types of research can be used to determine the best research design for the marketing research.

Data Types and Sources

Data types can be described as the different attributes on the basis of which a given data is classified into different categories or types. The data types and sources to be used can be divided as secondary data or primary data. Let us take a look at these data types.

Secondary Data

Secondary data means the data that have been collected previously for other purposes but that can be used in the immediate study. Secondary data may be internal to the company like sales invoices and warranty cards or may be external to the company like published data or commercially available data. The government census is an important of secondary data.

Secondary data offers the benefit of saving time and minimizing data gathering costs.

The main disadvantage of this data type is that the data may not fit the issue perfectly and that the accuracy may be more difficult to check for secondary data than for primary data.

Primary Data

Often, secondary data must be supported by primary data originated specifically for the study at hand. Some common types of primary data are demographic and socioeconomic features, psychological and lifestyle features etc.

Primary data can be obtained by interaction or by observation. Communication includes questioning respondents either verbally or in writing. This method is versatile, as one requires questioning for the information. However, the response may not be accurate or up to the mark.

Personal interviews have an interviewer partiality that mail-in questionnaires do not have. For example, in a personal interview the respondent's imagination of the interviewer may affect the responses.

Questionnaire Design

The questionnaire is an essential tool for collecting primary data. Poorly constructed questions can result in large mistakes and invalidate the research data, so considerable effort should be put into the questionnaire design.

The questionnaire should be tested completely prior to conducting the actual survey.

Measurement Scales

Marketing attributes can be scaled on nominal, ordinal, interval, and ratio scales −

  • Nominal numbers are simply identifiers, with the only permissible analytical use being for counting. For example — social security numbers, pin code.

  • Ordinal scales are used for scaling. The gap between the numbers conveys no meaning. Median and mode calculations can be done on ordinal numbers. For example, state ranking.

  • Interval scales balance an equal interval between numbers. These scales can be used for ranking and for weighing the interval between two numbers. We know that the zero point is arbitrary and ratios cannot be taken between numbers on an interval scale. However, mean, median, and mode are all valid. For example — temperature scale.

  • Ratio scales are hinted to an absolute zero value, so ratios between numbers on the scale have some meanings. In addition to mean, median, and mode, geometric averages are also valid in this measurement scale. For example − weight, height.

Data Collection

Data collection process introduces additional errors in the document. These errors are known as non-sampling errors. Some non-sampling errors may be intentional on the part of the interviewer, who may introduce partiality by directing the respondent to provide a certain response.

The interviewer also may introduce unintentional mistakes due to not having a clear understanding of the interview process or due to fatigue.

The occurrence of such non-sampling errors can be reduced through quality control techniques.

Data Analysis and Interpretation

Before analysis can be performed, raw data must be groomed into the right format. First, it must be edited so that mistakes can be corrected or removed.

The data must then be coded; this procedure transforms the edited raw data into numbers or symbols. A codebook is made to document how the data was coded. Finally, the data is tabulated to count the number of events falling into various categories.

Cross tabulation is the most commonly used data analysis method in marketing research. This technique divides the sample into sub-groups to represent how the dependent variable varies from one subgroup to another. A third variable can be launched to uncover a relationship that was initially not evident.

Marketing Research Report

The format of the marketing research report differs as per the requirements of the organization. The report often exhibits contents like enabling letter for the research, Table of Contents, list of explanations, results, limitations and so on.