Research Instrument and Data Analysis

In the observation method, the researcher may use a camera, tape recorder, or daily sheet (a sheet in which the number of times an event occurs is recorded). Whatever the instrument used, the researcher must ensure that the instrument is appropriate to the occasion and is reliable.

In the survey method, the most commonly used instrument is the questionnaire. This is a written and organized format containing all the questions relevant to soliciting the required information. 

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The construction of a questionnaire requires great skill. To check that the questionnaire serves the necessary purpose, it should be tested on a limited scale and this is technically known as a pilot survey. 

The objective of a pilot survey is to weed out unnecessary questions, and questions that are difficult to answer, and to improve the phrasing of certain questions which are difficult to comprehend.

In constructing a questionnaire, the important points to be considered are the types of questions to be asked, the wording of questions, and the sequencing of questions. Each question should be checked to evaluate its necessity in terms of fulfilling the research objectives.

Furthermore, the questions should be such that the respondent can answer them easily. Questions that require the respondent to answer questions about events that occurred a long time ago or about which they do not have direct knowledge should be avoided since you are not likely to get very accurate responses. 

The question should have direct relevance to the problem being researched. Too many irrelevant questions will only increase the length of the questionnaire (which would only put off the respondent) and also add to the burden of analysis without yielding any useful result.

The wording of the questions is a very important input in ensuring the correct response. Clearly worded, precise questions are not only easy to understand but they also facilitate the proper response.

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The wording of the question should be neutral and not attempt to influence or bias the response. This is especially relevant when information is being sought on non-physical issues such as the motivation, attitudes, and personal values of the respondent.

In deciding on the sampling size, you have to make a trade-off between the desired accuracy of the results and your budget. The larger the sample, the more accurate are the results likely to be, but the cost would also be correspondingly high. 

Another factor affecting the sample size is the kind of research that is being conducted. In exploratory research, even a small sample may be sufficient. In focus-group interviews and motivation-research studies, very small sample sizes are sufficient because here the emphasis is on qualitative aspects rather than the accuracy of numbers.

The choice of the sampling procedure is between two kinds: probability sampling and non-probability sampling. In the former, each item of the universe has an equal chance of being selected as a sample unit. In non-probability sampling, the researcher selects the units to be included in the sample. 

Non-probability sampling is mostly used in exploratory research where a true representation of the universe is not important. But where true representation is important, probability or random sampling is used. 

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Random sampling enables the researcher to make an accurate estimate of the population characteristic but it is more expensive than non-random sampling. The cost that you can beat and the degree of accuracy which you require have to be weighed to arrive at a decision.

The fourth element in the sampling plan is the sampling procedure. How should you reach your sample units: personally, by mail, or by telephone? Personal interviewing is most suited when there are many questions to be asked and it is important to ensure that the questions are understood properly. 

Thus, wherever the questions are a little complex, personal interviewing should be used. This is also the best method to ensure that correct answers are given which can be corroborated by the interviewer through observation. But this technique requires a skilled interviewer and a great deal of administration and supervision. Also, it is the most expensive of the three methods.

The mail questionnaire is extremely appropriate when your sampling units are distributed over a wide geographical area and the cost of reaching them personally is very high. However, the return rate of mail questionnaires is usually very low, ranging between three and seven percent. 

On average, you would have to mail 1000 questionnaires to get back thirty filled-up questionnaires. Another drawback is that you have no way of checking the authenticity and accuracy of the response. The respondent may fill in the wrong information and you may never be able to detect it.

The telephone interview combines the advantages of both personal and mail interviews. It allows you to clarify questions that may not be clearly understood by the respondent and to reach a widely scattered sample at a relatively low cost. But the obvious disadvantage is that your sample is restricted to people who have telephones. Also, you cannot conduct very long interviews over the telephone.


No information can be collected without incurring costs. Before undertaking a research project, its cost should be calculated and assessed against the benefits it would yield in improving the quality of decision-making. If the benefits outweigh the cost, it is certainly worthwhile initiating the research. 

There are four kinds of costs involved in marketing research. They include:

Cost of data collection: The actual cost incurred for collecting the data, which may comprise the research organization’s fee, staff time, printing and postage of questionnaire, computer time, etc.

Cost of time delays: The more time it takes to provide the research results, the longer the dependent decision(s) is delayed.

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In the meanwhile, the opportunity may be lost or it may become less attractive.

Risk of adverse environment change: While the decision is pending, unfavorable conditions may set in (entry of competition), and consequently, the returns may be lower.

Cost of error: Sometimes, by chance or because of some bias or wrong choice of sampling units, there could be an error in the results leading to expensive consequences for the company concerned.

Field Work

This is the stage where the research design has to be converted from the planning stage to that of implementation. 

To achieve the stated research objectives, data has to be collected. This data collection is known as fieldwork. The two stages in fieldwork are planning and supervision.


It has to be planned how many people will be assigned to the field, what will be their geographical areas of coverage, how many days will be required for the entire operation, and what is the pattern to be used for choosing sample units (every fourth household in a lane, all flats with an even number in an apartment ‘block’, etc.). 

All this planning has to be done following the details spelled out in the sampling plan.


Supervision is an extremely important input to ensure that the data collected is genuine and accurate. Most fieldwork is carried out by a team of field surveyors, and each team is assigned to a supervisor. 

The team members would plan their daily area of fieldwork in consultation with the supervisor. The supervisor may accompany different team members on different days. In the evening the team would meet the supervisor, hand over the data which they have collected, and sort out any problems they may have faced.

Apart from actually accompanying team members on data collection missions, the supervisor would also make random checks to ensure that the data collected is genuine. The check can be conducted either over the telephone (wherever possible) or by again visiting the sampling unit. The supervisor may either ask the respondent whether he or she was visited by the field interviewer and cross-check the accuracy of the data.

Random checking is carried out to ensure that the field workers do actually collect data from the genuine source of information and not just fill in the data using their imagination and ingenuity. 

The collected data has also to be checked for its objectivity and accuracy. The data has to be carefully checked to ensure that there is no distortion because of field workers’ bias or the respondent’s bias. 

Respondent bias arises because people generally like to project an image (about themselves and their lifestyle) that is more flattering than reality. 

This bias would operate more in questions relating to income, possession of certain items (VCR, air conditioner), and habits relating to lifestyle (traveling abroad frequently, visiting clubs, and restaurants). 

Interviewer bias arises because of the interviewer’s own preconceived notions and ideas. A female interviewer may prefer male respondents because she may feel that it is easy for her to gather information from men rather than women.

In conducting fieldwork, it may happen that the relevant source of information is not at home or does not wish to be interviewed. The supervisor must give guidelines for tackling such situations. The particular units may be substituted by the next one or the field worker visits the same unit again hoping to be more successful.

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Data Analysis

After you have collected the data, you need to process, organize and arrange it in a format that makes it easy to understand and directly helps the decision-making process. Raw data has to be processed and analyzed to obtain information. There are three phases for analyzing the data:

  • Classifying the raw data in a more orderly manner.
  • Summarizing the data.
  • Applying analytical methods to manipulate the data to highlight their interrelationship and quantitative significance.

Classifying the Raw Data

The most common classifications in marketing research are quantitative, qualitative, chronological, and geographical.

  • Quantitative: In this classification, data is classified by a numerical measure such as the number of respondents in each market segment, number of years employed, number of family members, number of units consumed, number of brands stocked, or some such numerical characteristic.
  • Qualitative: In this classification, the data is classified by some non-numerical attributes such as type of occupation, type of family structure (nuclear or joint family), and type of retail outlet (specialty, general merchant, department store, etc).
  • Chronological: Chronological classification is that in which data is classified according to the time when the event occurred.

In geographical classification, the data is classified according to the time when the event occurred.

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