Marketing Research

Marketing Research

Managers need information in order to introduce products and services that create value in the mind of the customer. But the perception of value is a subjective one, and what customers value this year may be quite different from what they value next year. As such, the attributes that create value cannot simply be deduced from common knowledge. Rather, data must be collected and analyzed. The goal of marketing research is to provide the facts and direction that managers need to make their more important marketing decisions.

To maximize the benefit of marketing research, those who use it need to understand the research process and its limitations.

Marketing Research vs. Market Research

These terms often are used interchangeably, but technically there is a difference.

Market research deals specifically with the gathering of information about a market's size and trends. Marketing research covers a wider range of activities. While it may involve market research, marketing research is a more general systematic process that can be applied to a variety of marketing problems.

The Value of Information

Information can be useful, but what determines its real value to the organization? In general, the value of information is determined by:

• The ability and willingness to act on the information.
• The accuracy of the information.
• The level of indecisiveness that would exist without the information.
• The amount of variation in the possible results.
• The level of risk aversion.
• The reaction of competitors to any decision improved by the information.
• The cost of the information in terms of time and money.

The Marketing Research Process

Once the need for marketing research has been established, most marketing research projects involve these steps:

1. Define the problem
2. Determine research design
3. Identify data types and sources
4. Design data collection forms and questionnaires
5. Determine sample plan and size
6. Collect the data
7. Analyze and interpret the data
8. Prepare the research report

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

Research Design

Marketing research can classified in one of three categories:

• Exploratory research
• Descriptive research
• Causal research

These classifications are made according to the objective of the research. In some cases the research will fall into one of these categories, but in other cases different phases of the same research project will fall into different categories.

• Exploratory research has the goal of formulating problems more precisely, clarifying concepts, gathering explanations, gaining insight, eliminating impractical ideas, and forming hypotheses. Exploratory research can be performed using a literature search, surveying certain people about their experiences, focus groups, and case studies. When surveying people, exploratory research studies would not try to acquire a representative sample, but rather, seek to interview those who are knowledgeable and who might be able to provide insight concerning the relationship among variables. Case studies can include contrasting situations or benchmarking against an organization known for its excellence. Exploratory research may develop hypotheses, but it does not seek to test them. Exploratory research is characterized by its flexibility.
• Descriptive research is more rigid than exploratory research and seeks to describe users of a product, determine the proportion of the population that uses a product, or predict future demand for a product. As opposed to exploratory research, descriptive research should define questions, people surveyed, and the method of analysis prior to beginning data collection. In other words, the who, what, where, when, why, and how aspects of the research should be defined. Such preparation allows one the opportunity to make any required changes before the costly process of data collection has begun.

• Causal research seeks to find cause and effect relationships between variables. It accomplishes this goal through laboratory and field experiments.

Data Types and Sources

Secondary Data:
 
Before going through the time and expense of collecting primary data, one should check for secondary data that previously may have been collected for other purposes but that can be used in the immediate study. Secondary data may be internal to the firm, such as sales invoices and warranty cards, or may be external to the firm such as published data or commercially available data. The government census is a valuable source of secondary data.

Secondary data has the advantage of saving time and reducing data gathering costs. The disadvantages are that the data may not fit the problem perfectly and that the accuracy may be more difficult to verify for secondary data than for primary data.

Some secondary data is republished by organizations other than the original source. Because errors can occur and important explanations may be missing in republished data, one should obtain secondary data directly from its source. One also should consider who the source is and whether the results may be biased.

There are several criteria that one should use to evaluate secondary data.

• Whether the data is useful in the research study.
• How current the data is and whether it applies to time period of interest.
• Errors and accuracy - whether the data is dependable and can be verified.
• Presence of bias in the data.
• Specifications and methodologies used, including data collection method, response rate, quality and analysis of the data, sample size and sampling technique, and questionnaire design.
• Objective of the original data collection.
• Nature of the data, including definition of variables, units of measure, categories used, and relationships examined.

Primary Data:

Often, secondary data must be supplemented by primary data originated specifically for the study at hand. Some common types of primary data are:

• Demographic and socioeconomic characteristics
• Psychological and lifestyle characteristics
• Attitudes and opinions
• Awareness and knowledge - for example, brand awareness
• Intentions - for example, purchase intentions. While useful, intentions are not a reliable indication of actual future behavior.
• Motivation - a person's motives are more stable than his/her behavior, so motive is a better predictor of future behavior than is past behavior.
• Behavior

Primary data can be obtained by communication or by observation. Communication involves questioning respondents either verbally or in writing. This method is versatile, since one needs only to ask for the information; however, the response may not be accurate. Communication usually is quicker and cheaper than observation. Observation involves the recording of actions and is performed by either a person or some mechanical or electronic device. Observation is less versatile than communication since some attributes of a person may not be readily observable, such as attitudes, awareness, knowledge, intentions, and motivation. Observation also might take longer since observers may have to wait for appropriate events to occur, though observation using scanner data might be quicker and more cost effective. Observation typically is more accurate than communication.

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

Questionnaire Design

The questionnaire is an important tool for gathering primary data. Poorly constructed questions can result in large errors and invalidate the research data, so significant effort should be put into the questionnaire design. The questionnaire should be tested thoroughly prior to conducting the survey.

Hypothesis Testing

A basic fact about testing hypotheses is that a hypothesis may be rejected but that the hypothesis never can be unconditionally accepted until all possible evidence is evaluated. In the case of sampled data, the information set cannot be complete. So if a test using such data does not reject a hypothesis, the conclusion is not necessarily that the hypothesis should be accepted.

The null hypothesis in an experiment is the hypothesis that the independent variable has no effect on the dependent variable. The null hypothesis is expressed as H0. This hypothesis is assumed to be true unless proven otherwise. The alternative to the null hypothesis is the hypothesis that the independent variable does have an effect on the dependent variable. This hypothesis is known as the alternative, research, or experimental hypothesis and is expressed as H1. This alternative hypothesis states that the relationship observed between the variables cannot be explained by chance alone.