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:
- 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
Problem Definition
The decision problem faced by management must be translated into a market research problem in the form of questions that define the information that is required to make the decision and how this information can be obtained. Thus, the decision problem is translated into a research problem. For example, a decision problem may be whether to launch a new product. The corresponding research problem might be to assess whether the market would accept the new product.
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.
There are two basic types of descriptive research: longitudinal studies and cross-sectional studies. Longitudinal studies are time series analyses that make repeated measurements of the same individuals, thus allowing one to monitor behavior such as brand-switching. However, longitudinal studies are not necessarily representative since many people may refuse to participate because of the commitment required. Cross-sectional studies sample the population to make measurements at a specific point in time. A special type of cross-sectional analysis is a cohort analysis, which tracks an aggregate of individuals who experience the same event within the same time interval over time. Cohort analyses are useful for long-term forecasting of product demand.
· 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.
Measurement Scales
Attributes can be measured on nominal, ordinal, interval, and ratio scales:
· Nominal numbers are simply identifiers, with the only permissible mathematical use being for counting. Example: social security numbers.
· Ordinal scales are used for ranking. The interval between the numbers conveys no meaning. Median and mode calculations can be performed on ordinal numbers. Example: class ranking
· Interval scales maintain an equal interval between numbers. These scales can be used for ranking and for measuring the interval between two numbers. Since the zero point is arbitrary, ratios cannot be taken between numbers on an interval scale; however, mean, median, and mode are all valid. Example: temperature scale
· Ratio scales are referenced to an absolute zero values, so ratios between numbers on the scale are meaningful. In addition to mean, median, and mode, geometric averages also are valid. Example: weight
Validity and Reliability
The validity of a test is the extent to which differences in scores reflect differences in the measured characteristic. Predictive validity is a measure of the usefulness of a measuring instrument as a predictor. Proof of predictive validity is determined by the correlation between results and actual behavior. Construct validity is the extent to which a measuring instrument measures what it intends to measure.
Reliability is the extent to which a measurement is repeatable with the same results. A measurement may be reliable and not valid. However, if a measurement is valid, then it also is reliable and if it is not reliable, then it cannot be valid. One way to show reliability is to show stability by repeating the test with the same results.
Attitude Measurement
Many of the questions in a marketing research survey are designed to measure attitudes. Attitudes are a person's general evaluation of something. Customer attitude is an important factor for the following reasons:
- Attitude helps to explain how ready one is to do something.
- Attitudes do not change much over time.
- Attitudes produce consistency in behavior.
- Attitudes can be related to preferences.
Attitudes can be measured using the following procedures:
· Self-reporting - subjects are asked directly about their attitudes. Self-reporting is the most common technique used to measure attitude.
· Observation of behavior - assuming that one's behavior is a result of one's attitudes, attitudes can be inferred by observing behavior. For example, one's attitude about an issue can be inferred by whether he/she signs a petition related to it.
· Indirect techniques - use unstructured stimuli such as word association tests.
· Performance of objective tasks - assumes that one's performance depends on attitude. For example, the subject can be asked to memorize the arguments of both sides of an issue. He/she is more likely to do a better job on the arguments that favor his/her stance.
· Physiological reactions - subject's response to a stimuli is measured using electronic or mechanical means. While the intensity can be measured, it is difficult to know if the attitude is positive or negative.
· Multiple measures - a mixture of techniques can be used to validate the findings, especially worthwhile when self-reporting is used.
There are several types of attitude rating scales:
· Equal-appearing interval scaling - a set of statements are assembled. These statements are selected according to their position on an interval scale of favorableness. Statements are chosen that has a small degree of dispersion. Respondents then are asked to indicate with which statements they agree.
· Likert method of summated ratings - a statement is made and the respondents indicate their degree of agreement or disagreement on a five point scale (Strongly Disagree, Disagree, Neither Agree Nor Disagree, Agree, Strongly Agree).
· Semantic differential scale - a scale is constructed using phrases describing attributes of the product to anchor each end. For example, the left end may state, "Hours are inconvenient" and the right end may state, "Hours are convenient". The respondent then marks one of the seven blanks between the statements to indicate his/her opinion about the attribute.
· Stapel Scale - similar to the semantic differential scale except that 1) points on the scale are identified by numbers, 2) only one statement is used and if the respondent disagrees a negative number should marked, and 3) there are 10 positions instead of seven. This scale does not require that bipolar adjectives be developed and it can be administered by telephone.
· Q-sort technique - the respondent if forced to construct a normal distribution by placing a specified number of cards in one of 11 stacks according to how desirable he/she finds the characteristics written on the cards.
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