Custom Search

Popular Posts

Sunday, December 29, 2013


It is very important to have a strategy for developing new products. Many products fail and in order to keep expanding company sales, we must have new products. Some products of Hindustan Lever have failed, but still they remain leading manufacturers because they have continuously added to their lines and added product lines to their product mix. Their 'Hima' peas introduced in the 60's flopped, because, in the words of the Chairman of Hindustan Lever, 'India is not yet ready for convenience foods, neatly done up in packages.' The product 'concept' requires testing before one goes into product designing and it is very necessary to have an adequate strategy for developing new products and introducing them. Several stages must be defined. Figure I gives the stages in new product development. These will now be discussed in detail. 

Figure-I : Stages in New Product Development



A company which introduces a new product naturally hopes that the product will contribute to the profits and provide consumer satisfaction for a long period of time. This however, does not always happen in practice. So, progressive organisations try to remain aware of what is happening throughout the life of the product in terms of the sales and the resultant profits.

The Introduction Stage  

Let us start thinking from the very beginning about what happens when a new product is introduced in the market.


Wednesday, December 18, 2013


The meaning of the word diversification is very simple. As soon as a manufacturer offers more than one product, it is described as product diversification.  Diversification implies that a company has moved from one product item to marketing more than one product. Generally, diversification is categorised into two types:

1. Related Diversification and
2. Unrelated Diversification.  

Where the new products introduced in the product mix are similar to the existing product, diversification is described as 'related'. When a company accepts new products which are very different from the existing products, the diversification is said to be ‘unrelated'.




Product related decisions form one of the 4Ps of marketing mix. These decisions include introduction of new products, Improvement of existing products, planned elimination of obsolete products and, packaging and branding.

Most product decisions are taken in the context of the overall strategy of an organisation. This strategy may also include important areas of diversification.

Product is the bundle of benefits or satisfactions offered to a customer. Product or Goods is a composite of the characteristics and features-physical and psychological-which are offered for purchase by a customer, whether it is a consumer or an industrial purchaser. How people personally feel about, or perceive the product is just as important as the actual physical characteristics of it. 

Product Differentiation: You must have understood now that a product is really a bundle of potential benefits offered to a purchaser. However, there are certain products which basically look alike. Take toothpastes, for example. These are offered by different manufacturers and were it not for the tube and the branding; the customer would not even be able to distinguish between the products of most different manufacturers. To make their product distinct from others the manufacturers identify them to the customer, that is, `differentiate', by using different packaging, colouring etc. and by emphasising different benefits or advantages in their promotion.  

Product Positioning: You know that all products do not appeal to all income groups or age groups, unless they are meant to satisfy basic necessities. A manufacturer can thus use the need-oriented segmentation. For example, a toothpaste manufacturer may appeal to prevention of `tooth decay', while another might offer `sociability' in the sense of preventing bad breath. Still another may provide the need to be `attractive' by emphasising the whiteness of the teeth which his product, toothpaste, gives. This lathe concept of product positioning. In the case of soft drinks, positioning can be done in terms of pricing, calorie contents and in many other ways. Thus positioning is used for bringing about differentiation in a manufacturer's product.


Sunday, December 15, 2013



Even buying decision involves an element of active reasoning. The manner in which this active reasoning manifests itself is illustrated in Figure I. In making a purchase decision the consumer goes through the five stages of:

1.   Problem recognition,
2.   Pre-purchase information search,
3.   Evaluation of alternatives,
4.   Purchase decision, and
5.   Post purchase behaviour.

However, in case of routine purchases, the consumer may skip the second and third stages and straight away go to the stage of purchase decision. But in case of purchase decision involving extensive problem solving, the consumer is likely to go through all the five stages in the specified sequence.


Sunday, December 8, 2013



Marketing research is undertaken in order to improve the understanding about a marketing situation or problem and consequently improve the quality of decision-making related to it. The usefulness of the marketing research output will depend upon the way the research has been designed and implemented at each stage of the process. There are five steps in every marketing research process:  

E) Report presentation and implementation


The final step is the preparation, presentation and implementation of a report giving the major findings and recommendations. A typical format of the report may comprise of the following sections:

a) Objectives and methodology in which the research objectives are stated and details of the sampling plan are described.

b) Summary of conclusions and recommendations in which the main findings of the research are highlighted. On the basis of the findings, some recommendations may be made.

c) Sample and its characteristics which contains descriptions of the sampling units in terms of their geographical location, socio-economic profile and other relevant details.

d) Detailed findings and observations in which the data which has collected is presented in a form which is easily comprehensible to the user. The data may be presented in tabular form or graphically in a bar chart, pictogram or pie diagram; or in a combination of all these.

e) Questionnaire and supporting research instruments are presented in the last section.
The research agency may or may not be involved in the implementation of the recommendation made in the report.




Marketing research is undertaken in order to improve the understanding about a marketing situation or problem and consequently improve the quality of decision-making related to it. The usefulness of the marketing research output will depend upon the way the research has been designed and implemented at each stage of the process. There are five steps in every marketing research process:  



After you have collected the data, you need to process, organise 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 analysed to obtain information. There are three phases for analysing the data:
a)   Classifying the raw data in a more orderly manner;
b)     Summarising the data;
c)     Applying analytical methods to manipulate the data to highlight their inter-relationship and quantitative significance.  

a) Classifying the raw data: The most commonly used classification in marketing research are quantitative, qualitative, chronological and geographical.

Quantitative: In this classification, data is classified by a numerical measure such as 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 attribute such as type of occupation, type of family structure (nucleus, or joint family), type of retail outlet (speciality, general merchant, department store etc.).

Chronological classification is that in which data is classified according to the time when the event occurred.

In the geographical classification the data is classified by location which may either be a country, state, region, city, village, etc.

Summarising the data: The first step in summarising the data is the tabulation. Individual observations or data are placed in a suitable classification in which they occur and then counted. Thus we know the number of times or the frequency with which a particular data occurs. Such tabulation leads to a frequency distribution as illustrated in Table 1.

The frequency distribution may involve a single variable as in Table 1 or it may involve two or more variables which is known as cross-classification or cross-tabulation.

The frequency distribution presented per se may not yield any specific result or inference. What we want is a single, condensed representative figure which will help us to make useful inferences about the data and also provide yardstick for comparing different sets of data. Measures of average or central tendency provide one such yardstick. The three types of averages are the mode, median and mean.

Mode: The mode is the central value or item that occurs most frequently. When the data is organised as a frequency distribution the mode is that category which has the maximum number of observations. (in the 121 - 140 category in Table 1). A shopkeeper ordering fresh stock of shoes for the season would make use of the mode to determine the size which is most frequently sold. The advantage of mode is that it is easy to compute, is not affected by extreme values in the frequency distribution and is representative if the observations are clustered at one particular value or class.

Median: The median is that item which lies exactly half-way between the lowest and highest value when the data is arranged in an ascending or. descending order. It is not affected by the value of the observation but by the number of observations. Suppose you have the data on monthly income of house holds in a particular area. The median value would give you that monthly income which divides the number of households into two equal parts. Fifty per cent of all households have a monthly income above the median value and fifty per cent of household have a monthly income below the median income.

Mean: The mean is the common arithmetic average. It is computed by dividing the sum of the values of the observations by the number of items observed. A firm wants to introduce a new packing of sliced bread aimed at the customer segment of small nucleus families of four members. It wishes to introduce the concept of a `single-day pack', i.e., a pack which contains only that number of bread slices that is usually eaten in a single day. This strategy would help to keep the price of the pack well within the family's limited budget. The firm has many opinions on the ideal number of slices that the pack should contain - ranging from three to as high as twelve. The firm decides to hire a professional marketing agency to conduct market research and recommend the number or bread slices it should pack.

The research agency goes about the task in two steps. In the first step, it randomly chooses five families (who are consumers of bread) in each of the four colonies in the city. These families are asked to maintain for one week a record of the exact number of slices they consumed each day. From this data, the agency calculates the average (or mean) number of bread slices eaten per family per day. There would be twenty such mean values (5 families in 4 colonies each; sample size 20). In the second step, from these mean values, the model value would provide the answer to the number of bread slices to be packed in each pack.

The mode in this frequency distribution is 8. Eight slices is the most commonly occurring consumption pattern. The agency's recommendation is to pack eight bread slices in the single-day pack.

The mean, mode and median are measures of central tendency or average. They measure the most typical value around which most values in the distribution tend to converge. However, there are always extreme values in each distribution. These extreme values indicate the spread or the dispersion of the distribution. To make a valid marketing decision you need not only the measures of central tendency but also relevant measures of dispersion. Measures of dispersion would tell you the number of values which are substantially different from the mean, median or mode. If the number of observations at the extreme values is large enough to form a substantial number, it indicates an opportunity for market segmentation. In the earlier example or bread if in a larger sample, you find that the number of households who consume three slices per day is also substantially large, the firm may find it worthwhile to introduce a 3-slice pack for light bread consumers. Such variations from the central tendency can be found by using measures of dispersion. The two commonly used measures of dispersion are range and standard deviation.

Range: The range is the difference between the largest and smallest observed value. Using the data in step I in the bread illustration, the largest observed value is 6 and the smallest observed value is 2, therefore the range is 4. The smaller the figure of range, the more compact and homogenous is the distribution.

Variance and standard deviation: These two measures of dispersion are based on the deviations from the mean. The variance is the average of the squared deviations of the observations values from the mean of the distribution. Standard deviation is the square root of the variance. The standard deviation is used to compare two samples which have the same mean. The distribution with the smaller standard deviation is more homogenous.

Selecting analytical methods: Besides having a summary of the data, the marketing manager also would like information on inter-relationships between variables and the qualitative aspects of the variables.

Correlation: Correlation coefficient measures the degree to which the change in one variable (the dependent variable) is associated with change in the other variable (independent one). As a marketing manager, you would like to know if there is any relation between the amount of money you spend on advertising and the sales you achieve. Sales are the dependent variable and advertising budget is the independent variable. Correlation coefficient, in this case, would tell you the extent of relationship between these two variables, whether the relationship is directly proportional (increase or decrease in advertising is associated with increase or decrease in advertising) or it as an inverse relationship (increase in advertising is associated with decrease in sales and vice versa) or there is no relationship between the two variables. However, it is important to note that correlation coefficient does not indicate a causal relationship. Sales is not a direct result of advertising alone, there are many other factors which affect sale. Correlation only indicates that there is some kind of association - whether it is casual or casual can be determined only after further investigation. You may find a correlation between the height of your salesmen and the sales, but obviously it is of no significance. In 1970, NCAER (National Council of Applied and Economic Research) predicted the annual stock of scooters using a regression model in which real personal disposable income and relative weighted price index of scooters were used as independent variables.

Regression Analysis: For determining casual relationship between two variables you may use regression analysis. Using this technique you can predict the dependent variables on the basis of the independent variables.

So far we have considered relationship only between two variables for which correlation and regression analysis are suitable techniques. But in reality you would rarely find a one-to-one casual relationship, rather you would find that the dependent variables are affected by a number of independent variables. Sales is affected by the advertising budget, the media plan, the content of the advertisements, number of salesmen, price of the product, efficiency of the distribution network and a host of other variables. For determining casual relationship involving two or more variables, multi-variate statistical techniques are applicable. The most important of these are the multiple regression analysis, discriminant analysis and factor analysis.

Multiple regression analysis is a variation of the regression analysis technique discussed above. The difference is that instead of considering one you may have two or more than two independent variables.

Discriminant analysis: In our discussion of dependent and independent variables, we have so far taken sale as the dependent variable. Sale is expressed in a numerical form. But not all dependent marketing variables can be expressed in numbers. Suppose you want to find out the reasons for customers brand preference for Thums Up vs. coca cola. In this case, the dependent variable, the brand, is not numerical in nature. A company is planning to introduce a new brand of detergent bar in the market and wants to find out the consumer traits associated with detergent bar as compared to detergent powder. This information would help the company focus its advertising strategy to exploit such associated traits. Several studies, aiming to discriminate between users and non-users of a particular brand of a product have been carried out. In one such study for a popular brand of Shirt, it was found that significant differences in the personality traits could determine between users and non-users.

Factor analysis: The multiple regression technique is based on the idea that you use truly independent variables. These variables are neither influenced by the dependent variable nor are they influenced by other independent variables. But in real life situations, there are many independent variables which are influenced by other independent variables, i.e. these independent variables have a high inter-correlation. You may find such an inter-correlation between the dealer discount structure and the ‘push' which the dealer provides to your product. Factor analysis is a statistical procedure which tries to determine a few basic factors that may underline and explain the inter-correlation among a large number of variables.

Statistical inference: These procedures involve the use of sample data to make inferences about the population. The three approaches used here are: estimates of population values, hypotheses about population values and tests of association between values in the population. Statistical inference as an analytical tool for marketing decisions is gaining wide acceptance.




Marketing research is undertaken in order to improve the understanding about a marketing situation or problem and consequently improve the quality of decision-making related to it. The usefulness of the marketing research output will depend upon the way the research has been designed and implemented at each stage of the process. There are five steps in every marketing research process:  



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 field work. The two stages in field work are planning and supervision.  

Planning: 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 in accordance with the details spelt out in the sampling plan.  

Supervision: Supervision is an extremely important input to ensure that the data collected is genuine and accurate. Most field work 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 field work 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 own 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 the field worker's bias or the respondent's bias. Respondent bias arises because people generally like to project an image (about themselves and their life-style) which is more flattering than the reality. This bias would operate more in questions relating to income; possession of certain items (VCR, air-conditioner), and habits relating to life-style (travelling abroad frequently, visiting clubs, restaurants). Interviewer bias arises because of the interviewer's own pre-conceived notions and ideas. A female interviewer may prefer male respondents because she may feel that it is easy for to gather information from men rather than women.
In conducting field work, 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 sampling units may be substituted by the next one or the field worker visits the same unit again hoping to be more successful.





Marketing research is undertaken in order to improve the understanding about a marketing situation or problem and consequently improve the quality of decision-making related to it. The usefulness of the marketing research output will depend upon the way the research has been designed and implemented at each stage of the process. There are five steps in every marketing research process:                                                



If you have stated your problem correctly and precisely, you should be able to spell out the precise objectives for research. Now you are in a position to prepare your research design. The research design spells out how you are going to achieve the stated research objectives. The data collection methods, the specific research, instrument and the sampling plan that you will use for collecting data and the corresponding cost are the elements that constitute the research design.

Data Collection Methods: A great deal of data is regularly collected and disseminated by international bodies, International Labour Organisation, World Bank, International Monetary Fund, Government and its many agencies including Planning Commission, Central Statistical Organisation, Reserve bank of India, Census Commission, private research organisations, and trade associations. This kind of data which has already been collected by another organisation and not by you is known as secondary data. This secondary data already exists in an accessible form; it only has to be located. You must first check whether any secondary data is available on the subject matter into which you are researching and make use of it, since it will save considerable time and money. But the data must be scrutinised properly since it was originally collected perhaps for another purpose. The data must also be checked for reliability, relevance and accuracy.

When secondary data is not available or it is not reliable, you would need to collect original data to suit your objectives. Original data collected specifically for a current research are known as primary data. Primary data can be collected from customers, retailers, distributors, manufacturers or other information sources. Primary data may be collected through any of the three methods: observation, survey and experimentation.

In the observation method, the researcher gathers information by observing. This method is generally used to observe buyer behaviour in a shop or to assess the impact of shelf placement and point of purchase promotional material. For instance you may like to observe the movement of shopping traffic through a department store, the number of shoppers who stopped before a particular display etc.

The obvious limitation of the observation method is that it allows observation of only overt behaviour. It provides no clues why a customer behaved in a particular manner, what product attributes appealed most to him, whether he would like to buy the product again etc. Such data can be generated by using the survey method. The survey method can also yield information about the socio-economic profile of your customers. The survey may either be conducted in a small group of customers through the focus group interview or may cover a large number of customers with the help of a questionnaire. In the focus group interview five to fifteen customers are invited for a discussion on a specific product or .a specific aspect of the product. The customers' comments provide valuable insight into their thinking which can help the manager to fine tune his marketing strategy to suit different customer segments. Surveys conducted with the help of questionnaire often take off from the focus group interview which yields excellent clues for designing the questionnaire. The questionnaire-based surveys yield not only qualitative but also quantitative data which have statistical validity.

The third method of collecting data is through experimentation. This is basically a simulation of the real-life situation, but in a controlled environment in which you systematically introduce certain elements to study their impact. This method is used for finding the best sales-training technique, the best price level, the most effective advertisement campaign. However, its use requires an extremely skilled researcher to ensure useful results. Also, this method is expensive.

Research Instrument: In the observation method, the researcher may use a camera, tape recorder or tally 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 organised format containing all the questions relevant to soliciting the required information. 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, questions which are difficult to answer, and improve the phrasing of certain questions which are difficult to comprehend.

In constructing a questionnaire the important points to be considered are the type of questions to be asked, wording of questions and 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 which require the respondent to answer questions about events which occurred a long time ago or about which he does not have direct knowledge should be avoided since you are not likely to get very accurate response. The questions 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. 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 motivation, attitudes, and personal values of the respondent. If you want to know the name of the shop from where the respondent bought his last tube of toothpaste, any way that you phrase the question will elicit the same response. Consider the following three alternatives in this context:

a)     Where did you buy this toothpaste?
b)     Can you please tell me the name of the shop from where you bought this toothpaste?
c)     From which shop did you buy this toothpaste?  

On the other hand, suppose you are trying to find out the customer perceptions about the performance of foreign brands of televisions versus Indian brands. The manner in which you phrase the questions is extremely critical as it can influence the response. Consider the following three alternatives:

a)     Do you think there is any difference in the performance of Indian TV sets as compared to foreign sets? (neutral wording)
b)     Don't you think foreign TVs perform better than Indian ones? (interviewer bias)
c)     Most people feel that foreign TVs perform better than Indian ones. Would you agree wit: this statement? (introducing respondent bias)

When including questions about qualitative aspects it is better to ask open ended questions rather than close ended questions, and unstructured rather than structured questions.

Open-ended question
"How would you describe the taste of this toothpaste?"

Close-ended question
"Would you describe the taste of this toothpaste as tingling?" Yes/No


Word association: For assessing toothpaste taste you may ask the respondent to give his immediate reaction to the following phrases in context of your specific brand:

Fresh          Tingling       Foamy
Mild            Pleasant      Sharp

In the structured questions you may like to give the respondents a number of answer choices to choose from. This is known as multiple-choice questions.

"Which one of the following words or phrases, in your opinion, best describes the taste of this toothpaste?"


A technique which combines both the structured and unstructured type of questions is the question scaling. The respondent is asked to rank his perception of a particular brand, product attribute, company image or any such factor on a scale ranging from extremely good to extremely poor. A typical scale may look as depicted in Figure I  
The advantage with unstructured and open ended questions is that they give the respondent freedom to answer in his own words. And this often provides information and insight about the product which the researcher had not even thought about. The only problem with unstructured questions is that of interpreting the results. The same results may lead to different analysis by different researchers. Unstructured questions also make statistical summaries difficult.

Close-ended and structured questions are easy to summarise and there is no scope for misinterpretation. But the scope of the research gets limited. The respondents have to choose from already given alternative answers, even though none may exactly match the respondent's perception.

The sequencing of the questions in the questionnaire should be such that the opening questions create interest in the respondent and are easy to answer. You would not like your respondent to be put off by posing difficult questions right in the beginning. The questionnaire should gradually move from relatively simple to difficult questions. The questions should be arranged in a logical manner to facilitate the respondent's answers and not confuse him. Personal questions about income, education, profession should be asked in the end since many people may view them as a violation of their privacy.

Sampling Plan: After preparing your questionnaire or your equipment for observation, you have to identify the source of your information, the source is also called the `population' or `universe'. For conducting marketing research you would rarely gather information from the entire population, rather you would select a small group known as sample which has all the characteristics of the population, and conduct research among the sample group. The reasons for not using the population for research are:

a)     the number of units in the population may not be known,
b)     the population units may be too many in number and/or widely dispersed thus making research an extremely time consuming process,
c)     it may be too expensive to include each population item.  

When the number of population items is small and known, (say, the number of cinema halls, colleges, government hospitals in a city) you may use the population as your source of information. But in most cases, a representative group which has all the characteristics of the population and is known as sample is drawn from the population and this is used for conducting research.

Having decided to use a sample, your next step is to draw up the sampling plan. There are four aspects to the sampling plan:

-who is to be surveyed (sampling unit)
-how many are to be surveyed (sample size)
-how are they to be selected (sampling procedure)
-how are they to be reached (sampling media).  

The choice of sampling unit will depend on the product with which you are dealing and the kind of information you need. In case of a product such as lipstick if you need information on the reasons which motivate a customer to buy your brand, your sampling unit would obviously be the actual user, i.e., a woman. But would the population comprise all the women?

Obviously not, because all women do not use lipsticks. You then need to collect information about women who use lipsticks in terms of their socio-economic background, education, occupational profile (student, housewife, professional), age and marital status. The sample which you choose must be representative of the universe in terms of all these characteristics. If you want to find out the monthly sale of all brands of lipsticks in a particular market, your 'sampling unit would be the distributors or retail outlets which deal in cosmetics. Suppose the product being researched into is toys for the under 7-years age category. Who would constitute your sampling unit: the child who actually plays with the toys or the parents who exert a strong influence in the final decision to purchase a particular toy? Here you would have to consider not only the kind of information that you need, but also who is most likely to have it and his ability to communicate, and choose your unit accordingly.

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 which 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 accuracy of numbers.

The choice of 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. 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 bear and the degree of accuracy which you require have to he 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 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 to seven per cent. On an 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 totally wrong information and you may never be able to detect it.
The telephone interviews combine advantages of both personal and mail interviews. It allows you to clarify questions which 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 the people who have telephones. Also, you, cannot conduct very long interviews over the telephone.
Cost: No information can be collected without incurring cost. 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.
Cost of data collection: The actual cost incurred for collecting the data, which may comprise the research organisation'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. In the meanwhile, the opportunity may be lost or it may become less attractive.
Risk of adverse environment change: While the decision is pending unfavourable 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.


Blog Widget by LinkWithin