Structure Of The Chapter
The role and limitations of marketing research
A definition of marketing research
The purpose of the research
Clear, concise, attainable, measurable and quantifiable objectives
The need to set a time horizon for marketing research
A reporting period
The research proposal
Step 1: Problem definition
Step 2: Hypothesis generation
Step 3: Decision on type of study
Step 4: Decision on data collection method
Step 5: Development of an analysis plan
Step 6: Data collection
Step 7: Analysis of data
Step 8: Drawing conclusions and making recommendations
In essence, management is about decision making. Decision is invariably surrounded by uncertainties and, therefore, risks. Marketing research is charged with helping to reduce such uncertainties, "...but will never remove it. At best, marketing research will increase the probability that the decisions which management has to take will help attain the organisation's marketing objectives.
The objectives of this chapter are to:
· Define the role of marketing research in decision making
· Outline the contents of a research brief
· Outline the contents of a research proposal, and
· Explain in detail each of the principal steps in research design.
This chapter begins by explaining the limitations of marketing research in so much that it serves to reduce rather than remove the risks attendant to decision making. The discussion proceeds to an outline of the research brief which has to be drawn up for the guidance of the individual or group charged with executing the study. At this point, the researcher has to respond to the brief with a research design. In this text an eight step research design is proposed and the reader will find a fairly thorough discussion of each of these steps within the chapter.
"Marketing research does not make decisions and it does not guarantee success". Marketing managers may seek advice from marketing research specialists, and indeed it is important that research reports should specify alternative courses of action and the probability of success, where possible, of these alternatives. However, it is marketing managers who make the final marketing decision and not the researcher. The second observation, that marketing research does not guarantee success, is simply a recognition of the environment within which marketing takes place. In the fields of science and engineering researchers are often working with deterministic models of the world where y = f(x). That is, x is a necessary and sufficient condition for y to occur. For instance, an increase in pressure is usually necessary and sufficient to bring about a rise in air temperature. In the social sciences, and this includes marketing and marketing research, the phenomenon under investigation rarely, if ever, lends itself to deterministic modelling. Consider the marketing problem of determining how much to spend on promotion in order to achieve a given market share. The link between promotional expenditure and sales is not so direct as that between pressure and temperature. There are a great many more intervening variables, including: the media used, the effectiveness of the promotional message, the length and frequency of the campaign, not to mention the many dimensions of the product, price and distribution. Marketing researchers work with probabilistic models of the form:
y = f(x1)..(fx2)...f(xn)...
This reflects the fact that in order for a target market share to be reached some promotion (amount unknown) is necessary but will not be sufficient, on its own, to achieve the target. Y is a function of a number of variables and the interactions between them. The model is further complicated by the fact that these interactions are themselves often not understood. It is for these reasons that marketing researchers cannot guarantee that decisions based on their information will always prove 'successful'. Rather the best that a competent researcher and a well designed study will be able to offer is a reduction in the amount of uncertainty surrounding the decision.
Green and Tull1 have defined marketing research as follows:
"Marketing research is the systematic and objective search for, and analysis of, information relevant to the identification and solution of any problem in the field of marketing."
The key words in this definition are; systematic, objective and analysis. Marketing research seeks to set about its task in a systematic and objective fashion. This means that a detailed and carefully designed research plan is developed in which each stage of the research is specified. Such a research plan is only considered adequate if it specifies: the research problem in concise and precise terms, the information necessary to address the problem, the methods to be employed in gathering the information and the analytical techniques to be used to interpret it.
Maintaining objectivity in marketing research is essential if marketing management is to have sufficient confidence in its results to be prepared to take risky decisions based upon those results. To this end, as far as possible, marketing researchers employ the scientific method. The characteristics of the scientific method are that it translates personal prejudices, notions and opinions into explicit propositions (or hypotheses). These are tested empirically. At the same time alternative explanations of the event or phenomena of interest are given equal consideration.
Not many years ago an agricultural engineering company developed an improved rice milling machine. The machine was introduced into Thailand where existing rice milling machines were of a design which resulted in a high percentage of brokens (broken kernels). The new rice mill produced a negligible percentage of brokens. Intuitively a successful product would be predicted, launched with hardly any need for marketing research when the new mill had such obvious advantages over existing products. The agricultural engineering company went through the expensive and time-consuming process of importing the machine into Thailand. They set up extensive distribution and servicing facilities only to be surprised when the mill failed to gain acceptance. In Thailand, smallholders take their rice to a miller.
Since they do not have sufficient cash to pay for milling their rice they get paid in 'brokens'. The miller then sells the 'brokens' for animal feed. The more effective milling machine simply did not fit into the Thai rice processing system. The company's assessment of the market was hardly objective. They saw the 'brokens' as a problem which their product solved. The prospective customer did not see it as a problem at all.
The third of the key terms in the definition given a little earlier was analytical. The marketing researcher's task goes beyond the collecting of data. He/she must also interpret the data in terms of what the it means to the organisation which commissioned the research. Knowing that 60% of those interviewed thought that product A was superior to product B is, in itself, of little value. The organisation needs to know the alternative ways it can respond to this data. Data is equivalent to the raw materials of manufacturing; it has to be converted into information before it becomes useful in decision making. The process of convening data into information is achieved through analysis.
Although the need for precision and thoroughness in marketing research has been stressed here, it is to be remembered that, in practice, there is a perpetual conflict between the demands of expediency and the search for truth. The reality is that management is frequently under pressure to make timely decisions. Therefore management often seeks answers through marketing research in the shortest time possible and, moreover, at minimum cost. On such occasions its methods tend to be less theoretically rigorous and its analysis more superficial.
The market research brief
Marketing research can be concerned with any of a variety of aspects of the market: the product, sales, buyer behaviour, promotion, distribution, pricing, packaging, etc. Since the researcher cannot investigate everything about a market, he/she must be selective. The question remains as to how the researcher decides where to focus the study, and to what depth each issue should be investigated. The answer should lie in a document called the research brief. The research design is a set of guidelines given to the researcher by the person(s) who have commissioned the research and/or the individual(s) who are to make use of the results in their decision making. The brief must inform the researcher which aspects of the market are particularly important. In particular, the research brief should include:
· the purpose of the research
· the objectives stated in a clear, concise, attainable, measurable and quantifiable way
· a time horizon
· a resource allocation, including the budget and facilities
· a reporting period.
Each of these components of the brief is explained in a little more detail in the section that follows.
It is not at all unusual for marketing managers to neglect to tell the researcher the precise purpose of the research. They often do not appreciate the need to do so. Instead, they simply state what they think they need to know. This is not quite the same thing. To appreciate the difference consider the case of the marketing research agency which was contacted by the International Coffee Organisation (ICO) and asked to carry out a survey of young people in the age group 15-24. They wanted information on the coffee drinking habits of these young people: how much coffee they drank, at what times of day, with meals or between meals, instant or ground coffee, which other beverages they preferred and so on. In response, the research organisation developed a set of wide-ranging proposals which included taking a large random sample of young people.
In fact much of the information was interesting rather than important. Important information is that information which directly assists in making decisions and the ICO had not told the research company the purpose of the research. The initial reason for the study had been a suspicion, on the part of the ICO, that an increasing percentage of young people were consuming beverages other than coffee, particularly soft drinks, and simply never developed the coffee drinking habit. Had this been explained to the research company then it is likely that their proposals would have been radically different. To begin with, the sample would have been composed of 15-24 year old non-coffee drinkers rather than a random sample of all 15-24 year olds. Second, the focus would have been non-coffee drinking habits rather than coffee drinking habits.
Unless the purpose of the research is stated in unambiguous terms it is difficult for the marketing researcher to translate the decision-maker's problem into a research problem and study design.
Suppose that the marketing manager states that he needs to know the potential market for a new product his/her organisation has been developing. At first glance this might appear to meet all of the requirements of being clear, concise, attainable, measurable and quantifiable. In practice it would possibly meet only one of these criteria, i.e. it is concise!
Here is another case to be considered. A small engineering firm had purchased a prototype tree-lifter from a private research company. This machine was suitable for lifting semi-mature trees, complete with root-ball intact, and transplanting such trees in another location. It was thought to have potential in certain types of tree nurseries and plantations.
The problem with the objective is that the marketing manager needs to know the potential market for the new tree-lifter is that it is not attainable. One could find out how many tree-lifters were currently being sold but this is not the same as the objective set by the marketing manager. The market potential for any new brand is a function of at least 4 things, as shown in Figure 1.1.
Figure 1.1 The components of market potential
It was possible to test customer reaction to the concept of the new tree-lifter by showing pictures, line drawings and by supplying product specifications to prospective buyers. However, since the company had not decided their pricing policy an important element could not be tested. In large measure, it was also possible to gauge the likely reaction from competitors. The researchers began by looking at the basis of competition to determine whether it was on price, product quality or unique product features. The researchers were able to look at precedents. They examined the pattern of response on past occasions when one or other of those companies already in the market had launched a new product. An audit of the environment was undertaken too, but the missing component was the company's' own plans for exploiting the market. Since the company had no involvement in the agricultural engineering sector, prior to acquiring the rights to the tree-lifter, they had no agreements with distributors, no idea of which, if any, of the distributors would be prepared to stock their product; they had no salesmen trained in selling into this industry and so on. The product's potential depended very much on such initiatives.
The solution would have been to undertake a study which would have described the market in detail in terms of customers, competitors and the environment. The company could then have put a marketing plan together and conducted a follow-up study to test their propositions out on the marketplace.
Inevitably there are deadlines which the marketing research activity must fit and these must be stated clearly at the outset of the research. As was said earlier, because of time pressures, management is often seeking quick answers from marketing research. If the researcher is aware of the time constraints then this will become an overriding factor when he/she plans the research design. He or she is likely to put forward a design which is less elegant, and gives rise to less precise information but delivers the results on schedule.
A resource allocation, including the budget and facilities
There are essentially two approaches to establishing the resource allocation to a particular marketing research exercise. Management can start with the problem and work out how much it will cost to solve it. Alternatively, they can decide how much the management can afford to spend, at the time, and seek the best answer they can for the time, money and manpower allocated. In practice the decision-makers prefer the latter approach and the researchers the former. In the end, some kind of compromise develops. The researcher rarely gets all of what he/she judges is required to reach a satisfactory conclusion but if the research proposal is well thought out and persuasively presented some concessions can be obtained.
Whichever the approach to resource allocation adopted, it is imperative that the researcher is aware of the financial and other constraints within which he/she must complete the work.
The researcher must also know from the outset of the study the points in time when interim reports are required, if any, and the deadline for the final report. The form of interim reports should also be specified at the outset, whether verbal or written, and whether presentations are to be made to a group (nature and size of the group) or an individual.
In addition there are several characteristics of a good research brief and these are that it:
· means the same thing to all concerned
· does not ask for irrelevant information
· defines the relevant populations to be measured
· identifies the correct variables to be measured
· specifies the degree of accuracy really needed within the main results
· specifies an order of priorities when the sample has to be broken down for the purposes of analysing data for subgroups, and
· does not pre-judge the selection of research techniques and procedures.
Having received the research brief, the researcher responds with a research proposal. This is a document which develops after having given careful consideration to the contents of the research brief. The research proposal sets out the research design and the procedures to be followed. The eight steps are set out in figure 1.2. These are only briefly discussed here since the remainder of this textbook consists of a detailed explanation of each step.
Figure 1.2 The research design
The point has already been made that the decision-maker should clearly communicate the purpose of the research to the marketing researcher but it is often the case that the objectives are not fully explained to the individual carrying out the study. Decision-makers seldom work out their objectives fully or, if they have, they are not willing to fully disclose them. In theory, responsibility for ensuring that the research proceeds along clearly defined lines rests with the decision-maker. In many instances the researcher has to take the initiative.
In situations, in which the researcher senses that the decision-maker is either unwilling or unable to fully articulate the objectives then he/she will have to pursue an indirect line of questioning. One approach is to take the problem statement supplied by the decision-maker and to break this down into key components and/or terms and to explore these with the decision-maker. For example, the decision-maker could be asked what he has in mind when he uses the term market potential. This is a legitimate question since the researcher is charged with the responsibility to develop a research design which will provide the right kind of information. Another approach is to focus the discussions with the person commissioning the research on the decisions which would be made given alternative findings which the study might come up with. This process frequently proves of great value to the decision-maker in that it helps him think through the objectives and perhaps select the most important of the objectives.
Whilst seeking to clarify the objectives of the research it is usually worthwhile having discussions with other levels of management who have some understanding of the marketing problem and/or the surrounding issues. Other helpful procedures include brainstorming, reviews of research on related problems and researching secondary sources of information as well as studying competitive products. Kerlinger2 suggests that a well-defined marketing research problem tends to have three common characteristics as shown in figure 1.3.
Whilst it is true that the purpose of research is to address some question, nonetheless one does not test research questions directly. For example, there may be interest in answering the question: "Does a person's level of education have any bearing upon whether or not he/she adopts new products?" Or, "Does a person's age bear any relation to brand loyalty behaviour?". Research questions are too broad to be directly testable. Instead, the question is reduced to one or more hypotheses implied by these questions.
Figure 1.3 Characteristics of a sound definition of the research problem
A hypothesis is a conjectural statement regarding the relation between two or more variables. There are two key characteristics which all hypotheses must have: they must be statements of the relationship between variables and they must carry clear implications for testing the stated relations. These characteristics imply that it is relationships, rather than variables, which are tested; the hypotheses specify how the variables are related and that these are measurable or potentially measurable. Statements lacking any or all of these characteristics are not research hypotheses. For example, consider the following hypothesis:
"Red meat consumption increases as real disposable incomes increase."
This is a relation stated between one variable, "red meat consumption", and another variable, "disposable incomes". Moreover, both variables are potentially measurable. The criteria have been met. However for the purposes of statistical testing it is more usual to find hypotheses stated in the so-called null form, e.g.
"There is no relationship between red meat consumption and the level of disposable incomes."
Consider a second hypothesis:
"There is no relationship between a farmer's educational level and his degree of innovativeness with respect to new farming technologies."
Again there is a clear statement of the relationship being investigated but there are question marks over the measurability with respect to at least one of the variables i.e. "...a farmer's degree of innovativeness." We may also encounter difficulties in agreeing an appropriate measure of the other variable, i.e. "level of education". If these problems can be resolved then we may indeed have a hypothesis.
Hypotheses are central to progress in research. They will direct the researcher's efforts by forcing him/her to concentrate on gathering the facts which will enable the hypotheses to be tested. The point has been made that it is all too easy when conducting research to collect "interesting data" as opposed to "important data". Data and questions which enable researchers to test explicit hypotheses are important. The rest are merely interesting.
There is a second advantage of stating hypotheses, namely that implicit notions or explanations for events become explicit and this often leads to modifications of these explanations, even before data is collected.
On occasion a given hypotheses may be too broad to be tested. However, other testable hypotheses may be deduced from it. A problem really cannot be solved unless it is reduced to hypothesis form, because a problem is a question, usually of a broad nature, and is not directly testable.
Marketing research can be carried out on one of three levels: exploratory, descriptive or causal.
Figure 1.4 Three types of marketing research study
Exploratory research: The chief purpose of exploratory research is to reach a better understanding of the research problem. This includes helping to identify the variables which should be measured within the study. When there is little understanding of the topic it is impossible to formulate hypotheses without some exploratory studies. For example, crop residues such a straw are high in lignin (a wood-like substance) and low in nutrients. This makes them a poor animal feed since the lignin acts against digestibility and the low nutrient content means poor food value. However, if treated in a strong alkali, plus a little heat, the lignin breaks down and the nutrient content increases. A company was established to exploit this technology and did so successfully for 4 seasons. After this period sales began to slow down. Three other manufacturers had entered the market by this time. The company, Animal Feed Systems, did not know whether the whole industry had slowed down or if only their product was suffering. Nor did they know if the problem was temporary in that perhaps the market comprised of "early adopters" had been saturated but it was only a matter of time before other farmers began to buy their systems when they saw how well they worked. It was also possible that if a problem did exist it could lie in any one of a number of areas: animal populations might be declining, distributors may not be promoting the product aggressively, customers may be experiencing difficulties in getting the chemicals, and so on and on.
This is a good example of a situation where insufficient knowledge prevented the development of clear objectives, since the problem could not be articulated with any precision and therefore research of an exploratory nature was required. Such research can take the form of literature searches, informal personal interviews with distributors and users/non-users of the product and/or focus group interviews with farmers and/or distributors.
Exploratory research is intended to help researchers formulate a problem in such a way that it can be researched and suggest testable hypotheses.
Descriptive research: As the name suggests, descriptive research is concerned with describing market characteristics and/or marketing mix characteristics. Typically, a descriptive study specifies the number and size of market segments, the alternative ways in which products are currently distributed, listing and comparison of the attributes and features of competitive products, etc.
This type of study can involve the description of the extent of association between variables. For example, the researcher may observe that there is an association between the geographical location of consumers and their tendency to consume red meat. Note that the researcher is able to describe the relationship rather than explain it. Nonetheless if the relationship between the two is fairly stable this descriptive information may be sufficient for the purposes of prediction. The researcher may, for example, be able to predict how fast the per capita consumption of red meat is likely to rise over a given time period.
The principal difference between exploratory and descriptive research is that, in the case of the latter, specific research questions have been formulated before the research is undertaken. When descriptive research is conducted the researcher must already know a great deal about the research problem, perhaps because of a prior exploratory study, and is in a position to clearly define what he/she wants to measure and how to do it.
Causal research: Causal research deals with the "why" questions. That is, there are occasions when the researcher will want to know why a change in one variable brings about a change in another. If he/she can understand the causes of the effects observed then our ability to predict and control such events is increased.
In summary then there are three distinct types of marketing research study: exploratory, descriptive and causal. The purpose of each is summarised in figure 1.4. In some cases, a research programme will be of one kind or another, but in other instances these three typologies will represent phases within a single marketing research investigation.
The next set of decisions concerns the method(s) of data gathering to be employed. The main methods of data collection are secondary data searches, observation, the survey, experimentation and consumer panels. Each of these topics is dealt with later on, so they are simply noted here.
Figure 1.5 Data collection methods
Those new to marketing research often intuitively believe that decisions about the techniques of analysis to be used can be left until after the data has been collected. Such an approach is ill-advised. Before interviews are conducted the following checklist should be applied:
· Is it known how each and every question is to be analysed? (e.g. which univariate or bivariate descriptive statistics, tests of association, parametric or nonparametric hypotheses tests, or multivariate methods are to be used?)
· Does the researcher have a sufficiently sound grasp of these techniques to apply them with confidence and to explain them to the decision-maker who commissioned the study?
· Does the researcher have the means to perform these calculations? (e.g. access to a computer which has an analysis program which he/she is familiar with? Or, if the calculations have to be performed manually, is there sufficient time to complete them and then to check them?)
· If a computer program is to be used at the data analysis stage, have the questions been properly coded?
· Have the questions been scaled correctly for the chosen statistical technique? (e.g. a t-test cannot be used on data which is only ranked)
There is little point in spending time and money on collecting data which subsequently is not or cannot be analysed. Therefore consideration has to be given to issues such as these before the fieldwork is undertaken.
At this stage the researcher is ready to go into the field and collect data. The various issues relating to data collection constitute the main body of the text and therefore, are not dwelt upon here.
The word 'analysis' has two component parts, the prefix 'ana' meaning 'above' and the Greek root 'lysis' meaning 'to break up or dissolve'. Thus data analysis can be described as:
"...a process of resolving data into its constituent components, to reveal its characteristic elements and structure."
Where the data is quantitative there are three determinants of the appropriate statistical tools for the purposes of analysis. These are the number of samples to be compared, whether the samples being compared are independent of one another and the level of data measurement.
Suppose a fruit juice processor wishes to test the acceptability of a new drink based on a novel combination of tropical fruit juices. There are several alternative research designs which might be employed, each involving different numbers of samples.
Comparing sales in a test market and the market share of the product it is targeted to replace.
Number of samples = 1
Comparing the responses of a sample of regular drinkers of fruit juices to those of a sample of non-fruit juice drinkers to a trial formulation.
Number of samples = 2
Comparing the responses of samples of heavy, moderate and infrequent fruit juice drinkers to a trial formulation.
Number of samples = 3
The next consideration is whether the samples being compared are dependent (i.e. related) or independent of one another (i.e. unrelated). Samples are said to be dependent, or related, when the measurement taken from one sample in no way affects the measurement taken from another sample. Take for example the outline of test B above. The measurement of the responses of fruit juice drinkers to the trial formulation in no way affects or influences the responses of the sample of non-fruit juice drinkers. Therefore, the samples are independent of one another. Suppose however a sample were given two formulations of fruit juice to taste. That is, the same individuals are asked first to taste formulation X and then to taste formulation Y. The researcher would have two sets of sample results, i.e. responses to product X and responses to product Y. In this case, the samples would be considered dependent or related to one another. This is because the individual will make a comparison of the two products and his/her response to one formulation is likely to affect his/her reaction or evaluation of the other product.
The third factor to be considered is the levels of measurement of the data being used. Data can be nominal, ordinal, interval or ratio scaled. Table 1.1 summarises the mathematical properties of each of these levels of measurement.
Once the marketing researcher knows how many samples are to be compared, whether these samples are related or unrelated to one another and the level of measurement then the selection of the appropriate statistical test is easily made. To illustrate the importance of understanding these connections consider the following simple, but common, question in marketing research. In many instances the age of respondents will be of interest. This question might be asked in either of the two following ways:
Please indicate to which of the following age categories you belong
15-21 years ___
22 - 30 years ___
Over 30 years ___
How old are you? ___ Years
Table 1.1 Levels of measurement
Producing grading categories
Confined to a small number of tests using the mode and frequency
Ranking of items
Placing brands of cooking oil in order of preference
Wide range of nonparametric tests which test for order
Relative differences of magnitude between items
Scoring products on a 10 point scale of like/dislike
Wide range of parametric tests
Absolute differences of magnitude
Stating how much better one product is than another in absolute terms.
All arithmetic operations
Choosing format (a) would give rise to nominal (or categorical) data and format (b) would yield ratio scaled data. These are at opposite ends of the hierarchy of levels of measurement. If by accident or design format (a) were chosen then the analyst would have only a very small set of statistical tests that could be applied and these are not very powerful in the sense that they are limited to showing association between variables and could not be used to establish cause-and-effect. Format (b), on the other hand, since it gives the analyst ratio data, allows all statistical tests to be used including the more powerful parametric tests whereby cause-and-effect can be established, where it exists. Thus a simple change in the wording of a question can have a fundamental effect upon the nature of the data generated. Figure 1.6 provides a useful guide to making that final selection.
Figure 1.6 Selecting statistical tests
The individual responsible for commissioning the research may be unfamiliar with the technicalities of statistical tests but he/she should at least be aware that the number of samples, their dependence or independence and the levels of measurement does affect how the data can be analysed. Those who submit marketing research proposals involving quantitative data should demonstrate an awareness of the factors that determine the mode of analysis and a capability to undertake such analysis.
Marketing researchers have to plan ahead for the analysis stage. It often happens that data processing begins whilst the data gathering is still underway. Whether the data is to be analysed manually or through the use of a computer program, data can be coded, cleaned (i.e. errors removed) and the proposed analytical tests tried out to ensure that they are effective before all of the data has been collected.
Another important aspect relates to logistics planning. This includes ensuring that once the task of preparing the data for analysis has begun there is a steady and uninterrupted flow of completed data forms or questionnaires back from the field interviewers to the data processors. Otherwise the whole exercise becomes increasingly inefficient. A second logistical issue concerns any plan to build up a picture of the pattern of responses as the data comes flowing in. This may require careful planning of the sequencing of fieldwork. For instance, suppose that research was being undertaken within a particular agricultural region with a view to establishing the size, number and type of milling enterprises which had established themselves in rural areas following market liberalisation. It may be that the West of the district under study mainly wheat is grown whilst in the East it is maize which is the major crop. It would make sense to coordinate the fieldwork with data analysis so that the interim picture was of either wheat or maize milling since the two are likely to differ in terms of the type of mill used (e.g. hammer versus plate mills) as well as screen sizes and end use (e.g. the proportions prepared for animal versus human food).
The final chapter of this textbook is devoted to the topic of report writing. However, it is perhaps worth noting that the end products of marketing research are conclusions and recommendations. With respect to the marketing planning function, marketing research helps to identify potential threats and opportunities, generates alternative courses of action, provides information to enable marketing managers to evaluate those alternatives and advises on the implementation of the alternatives.
Too often marketing research reports chiefly comprise a lengthy series of tables of statistics accompanied by a few brief comments which verbally describe what is already self-evident from the tables. Without interpretation, data remains of potential, as opposed to actual use. When conclusions are drawn from raw data and when recommendations are made then data is converted into information. It is information which management needs to reduce the inherent risks and uncertainties in management decision making.
Customer oriented marketing researchers will have noted from the outset of the research which topics and issues are of particular importance to the person(s) who initiated the research and will weight the content of their reports accordingly. That is, the researcher should determine what the marketing manager's priorities are with respect to the research study. In particular he/she should distinguish between what the manager:
· must know
· should know
· could know
This means that there will be information that is essential in order for the marketing manager to make the particular decision with which he/she is faced (must know), information that would be useful to have if time and resources within the budget allocation permit (should know) and there will be information that it would be nice to have but is not at all directly related to the decision at hand (could know). In writing a research proposal, experienced researchers would be careful to limit the information which they firmly promise to obtain, in the course of the study, to that which is considered 'must know' information. Moreover, within their final report, experienced researchers will ensure that the greater part of the report focuses upon 'must know' type information.
Marketing research serves marketing management by providing information which is relevant to decision making. Marketing research does not itself make the decisions, nor does it guarantee success. Rather, marketing research helps to reduce the uncertainty surrounding the decisions to be made. In order to do so effectively, marketing research has to be systematic, objective and analytical.
The manager or other individual initiating the research must provide guidance to the researcher in the form of a research brief. This document should state the purpose of the research, its objectives, the time by which it must be completed, the budget to which the researcher must work in developing the research design and the timing and frequency of any interim reports which the researcher is expected to make.
Having read, questioned and understood the research brief the onus is then upon the marketing researcher to respond by preparing the research design. Research design begins with an accurate and, as far as is possible, precise definition of the problem. This is followed by the generation of hypotheses. There will then be an intermediate stage whereby the hypotheses are restated in a testable form, i.e. the null form. This will probably only be done if it is intended that statistical analysis is to be undertaken. Where the research is more qualitative in nature then it is still recommended that hypotheses should be developed. These should include alternative hypotheses; depending upon what is already known about the research problem one of three types of study might be undertaken, i.e. an exploratory study, a descriptive study or a causal study. Before proceeding further, the researcher has to develop an analysis plan. It is only when the analysis plan has been considered that fieldwork, in the form of data collection, should be undertaken. The final step in the research design would be to write the report. Customer oriented marketing researchers will have noted from the outset of the research which topics and issues are of particular importance to the person(s) who initiated the research and will weight the content of their reports accordingly.
From your knowledge of the material in this chapter, give brief answers to the following questions below.
1 Name the 3 key words used in the definition of marketing research by Green, Tull and Albaum.
2. Define the term 'hypothesis'.
3. What are the 3 types of research described in this chapter?
4. What are the main items of information which should be included in a research brief?
5. Name the 3 factors which determine which is the appropriate statistical test to conduct on data obtained from a random sample.
6. What is the aim of exploratory research?
7. Name 4 characteristics of a good research brief.
8. Why is it important to devise a data analysis plan before collecting the data?
1. Green, P.E., Tull, D.S. and Albaum, G (1993), Research For Marketing Decisions, 5th edition, Prentice-Hall
2. Kerlinger, FN.(1994) Foundations of Behavioural Research, 1st edition, Holt, Rinehart and Winston, p. 174.