MARKETING RESEARCH

ASSIGNMENT-I1. Explain the role played by marketing research in understanding the customer. How do the four components of MIS serve the informational needs of a marketer?

Ans:- Marketing research is the systematic gathering, recording, and analysis of data about issues relating to marketing products and services. The term is commonly interchanged with market research; however, expert practitioners may wish to draw a distinction, in that market research is concerned specifically with markets, while marketing research is concerned specifically about marketing processes. Marketing research is often partitioned into two sets of categorical pairs, either by target market:

* Consumer marketing research, and * Business-to-business (B2B) marketing research

Or, alternatively, by methodological approach:

* Qualitative marketing research, and * Quantitative marketing research

Consumer marketing research is a form of applied sociology that concentrates on understanding the preferences, attitudes, and behaviors of consumers in a market-based economy, and it aims to understand the effects and comparative success of marketing campaigns.

Thus, marketing research may also be described as the systematic and objective identification, collection, analysis, and dissemination of information for the purpose of assisting management in decision making related to the identification and solution of problems and opportunities in marketing.

The task of marketing research is to provide management with relevant, accurate, reliable, valid, and current information. Competitive marketing environment and the ever-increasing costs attributed to poor decision making require that marketing research provide sound information. Sound decisions are not based on gut feeling, intuition, or even pure judgment.

Marketing managers make numerous strategic and tactical decisions in the process of identifying and satisfying customer needs. They make decisions about potential opportunities, target market selection, market segmentation, planning and implementing marketing programs, marketing performance, and control. These decisions are complicated by interactions between the controllable marketing variables of product, pricing, promotion, and distribution. Further complications are added by uncontrollable environmental factors such as general economic conditions, technology, public policies and laws, political environment, competition,

and social and cultural changes. Another factor in this mix is the complexity of consumers. Marketing research helps the marketing manager link the marketing variables with the environment and the consumers. It helps remove some of the uncertainty by providing relevant information about the marketing variables, environment, and consumers. In the absence of relevant information, consumers' response to marketing programs cannot be predicted reliably or accurately. Ongoing marketing research programs provide information on controllable and non-controllable factors and consumers; this information enhances the effectiveness of decisions made by marketing managers.

COMPONENTS OF A MARKETING INFORMATION SYSTEM

A marketing information system (MIS) is intended to bring together disparate items of data into a coherent body of information. An MIS is, as will shortly be seen, more than raw data or information suitable for the purposes of decision making. An MIS also provides methods for interpreting the information. Moreover, as Kotler's definition says, an MIS is more than a system of data collection or a set of information technologies

Figure 9.1 illustrates the major components of an MIS, the environmental factors monitored by the system and the types of marketing decision which the MIS seeks to underpin.

The explanation of this model of an MIS begins with a description of each of its four main constituent parts: the internal reporting systems, marketing research system, marketing intelligence system and marketing models. It is suggested that whilst the MIS varies in its degree of sophistication - with many in the industrialized countries being computerized and few in the developing countries being so - a fully fledged MIS should have these components, the methods (and technologies) of collection, storing, retrieving and processing data notwithstanding.

Internal reporting systems: All enterprises which have been in operation for any

period of time have a wealth of information. However, this information often remains under-utilized because it is compartmentalized, either in the form of an individual entrepreneur or in the functional departments of larger businesses. That is, information is usually categorized according to its nature so that there are, for example, financial, production, manpower, marketing, stockholding and logistical data. Often the entrepreneurs, or various personnel working in the functional departments holding these pieces of data, do not see how it could help decision makers in other functional areas. Similarly, decision makers can fail to appreciate how information from other functional areas might help them and therefore do not request it.

The internal records that are of immediate value to marketing decisions are: orders received, stockholdings and sales invoices. These are but a few of the internal records that can be used by marketing managers, but even this small set of records is capable of generating a great deal of information. Below, is a list of some of the information that can be derived from sales invoices:•Product type, size and pack type by territory.•Product type, size and pack type by type of account.•Product type, size and pack type by industry.•Product type, size and pack type by customer.•Average value and/or volume of sale by territory•Average value and/or volume of sale by type of account•Average value and/or volume of sale by industry•Average value and/or volume of sale by sales person

By comparing orders received with invoices an enterprise can establish the extent to which it is providing an acceptable level of customer service. In the same way,

comparing stockholding records with orders received helps an enterprise ascertain whether its stocks are in line with current demand patterns.

2. Briefly explain the various stages of the marketing research process.

Ans:- Stages/Steps in marketing researchStep 1: Problem Definition

The first step in any marketing research project is to define theproblem. In defining the problem, the researcher should take intoaccount the purpose of the study, the relevant backgroundinformation, what information is needed, and how it will be used indecision-making. Problem definition involves discussion with thedecision makers, interviews with industry experts, analysis ofsecondary data, and, perhaps, some qualitative research, such asfocus groups. Once the problem has been precisely defined, theresearch can be designed and conducted properly.

Step 2: Development of an Approach to the Problem

Development of an approach to the problem includes formulating anobjective or theoretical framework, analytical models, researchquestions, hypotheses, and identifying characteristics or factors thatcan influence the research design. This process is guided bydiscussions with management and industry experts, case studies andsimulations, analysis of secondary data, qualitative research andpragmatic considerations.

Step 3: Research Design Formulation

A research design is a framework or blueprint for conducting themarketing research project. It details the procedures necessary forobtaining the required information, and its purpose is to design a studythat will test the hypotheses of interest, determine possible answers tothe research questions, and provide the information needed fordecision making. Conducting exploratory research, precisely definingthe variables, and designing appropriate scales to measure them arealso a part of the research design. The issue of how the data should beobtained from the respondents (for example, by conducting a survey oran experiment) must be addressed. It is also necessary to design aquestionnaire and a sampling plan to select respondents for the study.More formally, formulating the research design involves the followingSteps:

1. Secondary data analysis

2. Qualitative research3. Methods of collecting quantitative data (survey, observation, andexperimentation)4. Definition of the information needed5. Measurement and scaling procedures6. Questionnaire design7. Sampling process and sample size8. Plan of data analysis

Step 4: Field Work or Data Collection

Data collection involves a field force or staff that operates either in thefield, as in the case of personal interviewing (in-home, mall intercept,or computer-assisted personal interviewing), from an office bytelephone (telephone or computer-assisted telephone interviewing), orthrough mail (traditional mail and mail panel surveys with persecutedhouseholds). Proper selection, training, supervision, and evaluation ofthe field force help minimize data-collection errors.

Step 5: Data Preparation and Analysis

Data preparation includes the editing, coding, transcription, andverification of data. Each questionnaire or observation form isinspected, or edited, and, if necessary, corrected. Number or lettercodes are assigned to represent each response to each question in thequestionnaire. The data from the questionnaires are transcribed orkeypunched on to magnetic tape, or disks or input directly into thecomputer. Verification ensures that the data from the originalquestionnaires have been accurately transcribed, while data analysis,guided by the plan of data analysis, gives meaning to the data thathave been collected. Univariate techniques are used for analyzing datawhen there is a single measurement of each element or unit in thesample, or, if there are several measurements of each element, eachRCH variable is analyzed in isolation. On the other hand, multivariatetechniques are used for analyzing data when there are two or moremeasurements on each element and the variables are analyzedsimultaneously.

Step 6: Report Preparation and Presentation

The entire project should be documented in a written report whichaddresses the specific research questions identified, describes theapproach, the research design, data collection, and data analysisprocedures adopted, and presents the results and the major findings.The findings should be presented in a comprehensible format so thatthey can be readily used in the decision making process. In addition,

an oral presentation should be made to management using tables,figures, and graphs to enhance clarity and impact.For these reasons, interviews with experts are more useful inconducting marketing research for industrial firms and for products ofa technical nature, where it is relatively easy to identify and approachthe experts. This method is also helpful in situations where littleinformation is available from other sources, as in the case of radicallynew products.

3. Compare and contrast exploratory and descriptive research designs.

Ans:- EXPLORATORY RESEARCHOBJECTIVE : Exploratory research is to explore or searchthrough a problem or situation to provide insights and

understandingUsed for following purposes:•Formulate a problem or define a problem more precisely.•Identify alternative courses of action.•Develop hypotheses.•Isolate key variables and relationships for further examination.•Gain insights for developing an approach to the problem.•Establish priorities for further research

Methods used in Exploratory Research:

•A review of academic and trade literature to identify the relevant demographic and psychographic factors that influence consumer patronage of department stores

•Interviews with retailing experts to determine trends, such asemergence of new types of outlets and shifts in consumerpatronage patterns (e.g., shopping on theInternet)

•U A comparative analysis of the three best and three worst stores of the same chain to gain some idea of the factors that influence store performance•Focus groups to determine the factors that consumers considerimportant in selecting department stores

DESCRIPTIVE RESEARCH•Descriptive Research is to describe marketcharacteristics or functions•Descriptive research is conducted for the

following reasons:•Describing the characteristics of relevant groups, such asconsumers, salespeople, organizations, or market areas.•Estimating the percentage of units in a specified population

exhibiting a certain behavior.•Determining the perceptions of product characteristics.•Determining the degree to which marketing variables areassociated.•Making specific predictions.

•Descriptive Design requires clear specificationsof :–Who—Who should be considered a patron of a particulardepartment store?–What—What information should be obtained from therespondents?–When—When should the information be obtained from therespondents?–Where—Where should the respondents be contacted to obtainthe required information?–Why—Why are we obtaining information from the respondents?Why is the marketing research project being conducted?–Way—In what way are we going to obtain information from therespondents?

4. Explain the various stages of designing a questionnaire.

Ans:- There are a few steps in the conceptual design of your questionnaire. As you progress through these steps, you determine the form that the questionnaire will eventually take. These steps are:

* Identifying your products and their features

Use the C3 Product Manager to generate a complete list of your company's products, and use this list to generate a list of product features. This list of features does not need to include every feature in every product, but it does need to include the features that can help distinguish between products. * Categorizing your features

Once you have identified your features, you need to group the features into a hierarchy. * Determining the look and feel you want your questionnaire to have

You need to decide how you want your questionnaire to look. This includes such things as how many questions should appear on each page of the questionnaire.

Identify Your Products

You base your design on your list of products and the list of features these products represent. The questionnaire is used to identify products, and it uses features to do it. Thus, the logical place to start is by making a list of your company's products. You can get this list from the C3 Product Manager. Then you use your product list to identify your feature list.

Your company may carry a large product line, and this product line might change frequently. As a result, you may need to periodically redesign your questionnaire to take these changes into account.Identify and Categorize Your Features

Once you have a complete list of your products, you can use this list to identify the features you will use in your questionnaire. Features are important because:

* You create your questions based on your features.

Since the questionnaire distinguishes between products by how their feature sets differ, you need to create questions that can isolate specific features. * Your customers will compare products based on their features.

One of the capabilities of the C3 Advisor is to display a comparison of two or more products. This comparison is based on the features you define.

Once you have created your list of features, you need to categorize them. That is, you need to group them into a hierarchy where each feature is a member of a specific feature type.

Determine the Look and Feel You Want

C3 Advisor Administration gives you a great deal of freedom in determining how your questionnaire will be organized. In particular, you can decide how many questionnaire pages will make up the questionnaire, as well as how many questions will appear on each questionnaire page. This in turn defines the customer experience.

You might decide that a customer would rather answer all possible questions on a single page, and go from that page to their final product list. This approach would only require you to create a single questionnaire page within your questionnaire.

On the other hand, you might decide that each questionnaire page should have only one question to answer, providing a wizard-like experience for your customer. In this case, you would need to create a questionnaire page for each of your questions.

These two cases are the extremes, and it is more likely that you will create a questionnaire that falls somewhere between the two. Most administrators choose to design a questionnaire that has a reasonable number of questionnaire pages, with a few questions assigned to each questionnaire page.

Whichever approach you choose to take, you need to decide ahead of time the general appearance and behavior you want your questionnaire to have.Laying Out the Questionnaire

Once you have listed your feature hierarchy and made a preliminary decision about how you want your questionnaire to appear, you need to lay the questionnaire out. The layout is a kind of tree diagram of the questionnaire that you create before you actually build the questionnaire. This layout shows each of the questionnaire pages that will be in the questionnaire, as well as the questions and answers that will appear on each questionnaire page. The layout needs to show the path from one questionnaire page to the next, as well as which products are identified by each path in the diagram. To do this, you will:

* Use your list of features to determine what questions and answers you need to create. The features can represent possible answers to the questions. * Write questions (and their answers) that map to specific features. * List the questionnaire pages that will contain these questions. * Create a story board that shows the questionnaire.

5. Explain the various probability and non-probability based methods of sampling.

Ans:- Probability Sampling

A probability sampling method is any method of sampling that utilizes some form of random selection. In order to have a random selection method, you must set up some process or procedure that assures that the different units in your population have equal probabilities of being chosen. Humans have long practiced various forms of random selection, such as picking a name out of a hat, or choosing the short straw. These days, we tend to use computers as the mechanism for generating random numbers as the basis for random selection.

Some Definitions

Before I can explain the various probability methods we have to define some basic terms. These are:

* N = the number of cases in the sampling frame * n = the number of cases in the sample * NCn = the number of combinations (subsets) of n from N * f = n/N = the sampling fraction

That's it. With those terms defined we can begin to define the different probability sampling methods.Simple Random Sampling

The simplest form of random sampling is called simple random sampling. Pretty tricky, huh? Here's the quick description of simple random sampling:

* Objective: To select n units out of N such that each NCn has an equal chance of being selected. * Procedure: Use a table of random numbers, a computer random number generator, or a mechanical device to select the sample.

Stratified Random Sampling

Stratified Random Sampling, also sometimes called proportional or quota random sampling, involves dividing your population into homogeneous subgroups and then taking a simple random sample in each subgroup. In more formal terms:

Objective: Divide the population into non-overlapping groups (i.e., strata) N1, N2, N3, ... Ni, such that N1 + N2 + N3 + ... + Ni = N. Then do a simple random sample of f = n/N in each strata.

There are several major reasons why you might prefer stratified sampling over simple random sampling. First, it assures that you will be able to represent not only the overall population, but also key subgroups of the population, especially small minority groups. If you want to be able to talk about subgroups, this may be the only way to effectively assure you'll be able to. If the subgroup is extremely small, you can use different sampling fractions (f) within the different strata to randomly over-sample the small group (although you'll then have to weight the within-group estimates using the sampling fraction whenever you want overall population estimates). When we use the same sampling fraction within strata we are conducting proportionate stratified random sampling. When we use different sampling fractions in the strata, we call this disproportionate stratified random sampling. Second, stratified random sampling will generally have more statistical precision than simple random sampling. This will only be true if the strata or groups are homogeneous. If they are, we expect that the variability within-groups is lower than the variability for the population as a whole. Stratified sampling capitalizes on that fact.

Systematic Random Sampling

Here are the steps you need to follow in order to achieve a systematic random sample:

* number the units in the population from 1 to N * decide on the n (sample size) that you want or need * k = N/n = the interval size * randomly select an integer between 1 to k * then take every kth unit

Cluster (Area) Random Sampling

The problem with random sampling methods when we have to sample a population that's disbursed across a wide geographic region is that you will have to cover a lot of ground geographically in order to get to each of the units you sampled. Imagine taking a simple random sample of all the residents of New York State in order to conduct personal interviews. By the luck of the draw you will wind up with respondents who come from all over the state. Your interviewers are going to have a lot of traveling to do. It is for precisely this problem that cluster or area random sampling was invented.

In cluster sampling, we follow these steps:

* divide population into clusters (usually along geographic boundaries) * randomly sample clusters * measure all units within sampled clusters

Multi-Stage Sampling

The four methods we've covered so far -- simple, stratified, systematic and cluster -- are the simplest random sampling strategies. In most real applied social research, we would use sampling methods that are considerably more complex than these simple variations. The most important principle here is that we can combine the simple methods described earlier in a variety of useful ways that help us address our sampling needs in the most efficient and effective manner possible. When we combine sampling methods, we call this multi-stage sampling.

Nonprobability Sampling

The difference between nonprobability and probability sampling is that nonprobability sampling does not involve random selection and probability sampling does. Does that mean that nonprobability samples aren't representative of the population? Not necessarily. But it does mean that nonprobability samples cannot depend upon the rationale of probability theory. At least with a probabilistic sample, we know the odds or probability that we have represented the population well. We are able to estimate confidence intervals for the statistic. With nonprobability samples, we may or may not represent the population well, and it

will often be hard for us to know how well we've done so. In general, researchers prefer probabilistic or random sampling methods over nonprobabilistic ones, and consider them to be more accurate and rigorous. However, in applied social research there may be circumstances where it is not feasible, practical or theoretically sensible to do random sampling. Here, we consider a wide range of nonprobabilistic alternatives.

We can divide nonprobability sampling methods into two broad types: accidental or purposive. Most sampling methods are purposive in nature because we usually approach the sampling problem with a specific plan in mind. The most important distinctions among these types of sampling methods are the ones between the different types of purposive sampling approaches.

Accidental, Haphazard or Convenience Sampling

One of the most common methods of sampling goes under the various titles listed here. I would include in this category the traditional "man on the street" (of course, now it's probably the "person on the street") interviews conducted frequently by television news programs to get a quick (although nonrepresentative) reading of public opinion. I would also argue that the typical use of college students in much psychological research is primarily a matter of convenience. (You don't really believe that psychologists use college students because they believe they're representative of the population at large, do you?). In clinical practice,we might use clients who are available to us as our sample. In many research contexts, we sample simply by asking for volunteers. Clearly, the problem with all of these types of samples is that we have no evidence that they are representative of the populations we're interested in generalizing to -- and in many cases we would clearly suspect that they are not.

Purposive Sampling

In purposive sampling, we sample with a purpose in mind. We usually would have one or more specific predefined groups we are seeking. For instance, have you ever run into people in a mall or on the street who are carrying a clipboard and who are stopping various people and asking if they could interview them? Most likely they are conducting a purposive sample (and most likely they are engaged in market research). They might be looking for Caucasian females between 30-40 years old. They size up the people passing by and anyone who looks to be in that category they stop to ask if they will participate. One of the first things they're likely to do is verify that the respondent does in fact meet the criteria for being in the sample. Purposive sampling can be very useful for situations where you need to reach a targeted sample quickly and where sampling for proportionality is not the primary concern. With a purposive sample, you are likely to get the opinions of your target population, but you are also likely to overweight subgroups in your population that are more readily accessible.

In all of these methods we know what we want -- we are sampling with a purpose.

* Modal Instance Sampling

In statistics, the mode is the most frequently occurring value in a distribution. In sampling, when we do a modal instance sample, we are sampling the most frequent case, or the "typical" case. In a lot of informal public opinion polls, for instance, they interview a "typical" voter. There are a number of problems with this sampling approach. First, how do we know what the "typical" or "modal" case is? We could say that the modal voter is a person who is of average age, educational level, and income in the population. But, it's not clear that using the averages of these is the fairest (consider the skewed distribution of income, for instance). And, how do you know that those three variables -- age, education, income -- are the only or even the most relevant for classifying the typical voter? What if religion or ethnicity is an important discriminator? Clearly, modal instance sampling is only sensible for informal sampling contexts.

* Expert Sampling

Expert sampling involves the assembling of a sample of persons with known or demonstrable experience and expertise in some area. Often, we convene such a sample under the auspices of a "panel of experts." There are actually two reasons you might do expert sampling. First, because it would be the best way to elicit the views of persons who have specific expertise. In this case, expert sampling is essentially just a specific subcase of purposive sampling. But the other reason you might use expert sampling is to provide evidence for the validity of another sampling approach you've chosen. For instance, let's say you do modal instance sampling and are concerned that the criteria you used for defining the modal instance are subject to criticism. You might convene an expert panel consisting of persons with acknowledged experience and insight into that field or topic and ask them to examine your modal definitions and comment on their appropriateness and validity. The advantage of doing this is that you aren't out on your own trying to defend your decisions -- you have some acknowledged experts to back you. The disadvantage is that even the experts can be, and often are, wrong.

* Quota Sampling

In quota sampling, you select people nonrandomly according to some fixed quota. There are two types of quota sampling: proportional and non proportional. In proportional quota sampling you want to represent the major characteristics of the population by sampling a proportional amount of each. For instance, if you know the population has 40% women and 60% men, and that you want a total sample size of 100, you will continue sampling until you get those percentages and then you will stop. So, if you've already got the 40 women for your sample, but not the sixty men, you will continue to sample men but even if legitimate women respondents come along, you will not sample them because you have already "met your quota." The

problem here (as in much purposive sampling) is that you have to decide the specific characteristics on which you will base the quota. Will it be by gender, age, education race, religion, etc.?

Nonproportional quota sampling is a bit less restrictive. In this method, you specify the minimum number of sampled units you want in each category. here, you're not concerned with having numbers that match the proportions in the population. Instead, you simply want to have enough to assure that you will be able to talk about even small groups in the population. This method is the nonprobabilistic analogue of stratified random sampling in that it is typically used to assure that smaller groups are adequately represented in your sample.

* Heterogeneity Sampling

We sample for heterogeneity when we want to include all opinions or views, and we aren't concerned about representing these views proportionately. Another term for this is sampling for diversity. In many brainstorming or nominal group processes (including concept mapping), we would use some form of heterogeneity sampling because our primary interest is in getting broad spectrum of ideas, not identifying the "average" or "modal instance" ones. In effect, what we would like to be sampling is not people, but ideas. We imagine that there is a universe of all possible ideas relevant to some topic and that we want to sample this population, not the population of people who have the ideas. Clearly, in order to get all of the ideas, and especially the "outlier" or unusual ones, we have to include a broad and diverse range of participants. Heterogeneity sampling is, in this sense, almost the opposite of modal instance sampling.

* Snowball Sampling

In snowball sampling, you begin by identifying someone who meets the criteria for inclusion in your study. You then ask them to recommend others who they may know who also meet the criteria. Although this method would hardly lead to representative samples, there are times when it may be the best method available. Snowball sampling is especially useful when you are trying to reach populations that are inaccessible or hard to find. For instance, if you are studying the homeless, you are not likely to be able to find good lists of homeless people within a specific geographical area. However, if you go to that area and identify one or two, you may find that they know very well who the other homeless people in their vicinity are and how you can find them.

------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ASSIGNMENT-II

1. Differentiate between the univariate and multivariate techniques of data analysis.

Ans:- Multivariate Data Analysis

Multivariate Data Analysis refers to any statistical technique used to analyze data that arises from more than one variable. This essentially models reality where each situation, product, or decision involves more than a single variable. The information age has resulted in masses of data in every field. Despite the quantum of data available, the ability to obtain a clear picture of what is going on and make intelligent decisions is a challenge. When available information is stored in database tables containing rows and columns, Multivariate Analysis can be used to process the information in a meaningful fashion.

Multivariate analysis methods typically used for:

* Consumer and market research * Quality control and quality assurance across a range of industries such as food and beverage, paint, pharmaceuticals, chemicals, energy, telecommunications, etc * Process optimization and process control * Research and development

With Multivariate Analysis you can: * Obtain a summary or an overview of a table. This analysis is often called Principal Components Analysis or Factor Analysis. In the overview, it is possible to identify the dominant patterns in the data, such as groups, outliers, trends, and so on. The patterns are displayed as two plots * Analyze groups in the table, how these groups differ, and to which group individual table rows belong. This type of analysis is called Classification and Discriminant Analysis * Find relationships between columns in data tables, for instance relationships between process operation conditions and product quality. The objective is to use one set of variables (columns) to predict another, for the purpose of optimization, and to find out which columns are important in the relationship. The corresponding analysis is called Multiple Regression Analysis or Partial Least Squares (PLS), depending on the size of the data table.

Univariate statistics

* SPSS Procedures for computing univariate statistics, o available under the Analyze Menu, then under "Descriptive Statistics" + Frequencies for discrete variables # Gives counts and percents for each value of variable. # A "Graph" option offers three types of graphs * Bar charts for discrete variables * Pie charts also for discrete variables * histograms for continuous variables.

# A "statistics" option offers various summary statistics: * Three measures of central tendency: mean, median, and mode * Three measures of dispersion: standard deviation, variance, and range # You can suppress the frequency table for continuous or "quasi-continuous" variables, or choose + Descriptives for continuous variables * Summarizing distributions of single variables o Measures of central tendency: + Mode: most frequent value, applies to all types of data + Median: value that divides the cases into two halves, applies to all but nominal data + Mean: sum of all values divided by number of cases, strictly speaking, it applies only to interval and ratio data, but practically is used for discrete orderable data also o Measures of dispersion: + Measures for nominal data: # "Variation" in nominal variables is usually determined by inspecting the frequency distribution. * Summary measures of variation are tyically based on the proportion of cases in the mode. * One such measure is the Variation Ratio

+ Easy to understand measures for continuous variables # Range

# (Semi-) Interquartile Range

# Average (mean) deviation

o Harder to understand measures, but most important ones + Sums of squares

+ Variance

+ Standard deviation

* Standardizing the dispersion among variables: dividing raw values by their means and standard deviations to produce z-scores: o Computation:

z-score =

o Properties of z-scores, they + have a mean of 0 and a + Standard deviation of 1 (therefore a variance of 1)

IV. Shapes of univariate distributions

* The normal distribution o Bell-shaped + symmetrical + unimodal o Properties: contains known % of cases within specified standard deviations of the mean

± 1 s.d embraces

_____ % of the cases

± 2 s.d. embraces

_____ % of the cases

± 3s.d. embraces

_____ % of the cases

o These % are reported in tables of areas under the normal curve and they are used in testing observed statistics against expectations under the null hypothesis. * Non-normal distributions: o Asymmetrical distributions are skewed. + Defined as positively or negatively skewed by location of tail. + Measured by the "third moment" of deviation from the mean. o Symmetrical distributions that are too flat (platykurdic) or too peaked (leptokurdic) are measured by kurtosis. + Measured by the "fourth moment" of deviation from the mean. + Both measures of skewness and kurtosis can be computed by frequencies and are expressed as deviations from 0.

* Some types of nonlinear transformations help "normalize" a non-normal distribution. o Squaring X helps normalize a distribution skewed to the left. o Taking the square root helps normalize a distribution skewed right. o Taking the logarithm of X also helps normalize a right-skewed distribution.

2. What are the four types of scales used in measuring data?

Ans:- Normally, when one hears the term measurement, they may think in terms of measuring the length of something (ie. the length of a piece of wood) or measuring a quantity of something (ie. a cup of flour). This represents a limited use of the term measurement. In statistics, the term measurement is used more broadly and is more appropriately termed scales of measurement. Scales of measurement refer to ways in which variables/numbers are defined and categorized. Each scale of measurement has certain properties which in turn determines the appropriateness for use of certain statistical analyses. The four scales of measurement are nominal, ordinal, interval, and ratio.

Nominal: Categorical data and numbers that are simply used as identifiers or names represent a nominal scale of measurement. Numbers on the back of a baseball jersey (St. Louis Cardinals 1 = Ozzie Smith) and your social security number are examples of nominal data. If I conduct a study and I'm including gender as a variable, I will code Female as 1 and Male as 2 or visa versa when I enter my data into the computer. Thus, I am using the numbers 1 and 2 to represent categories of data.

Ordinal: An ordinal scale of measurement represents an ordered series of relationships or rank order. Individuals competing in a contest may be fortunate to achieve first, second, or third place. First, second, and third place represent ordinal data. If Roscoe takes first and Wilbur takes second, we do not know if the competition was close; we only know that Roscoe outperformed Wilbur. Likert-type scales (such as "On a scale of 1 to 10 with one being no pain and ten being high pain, how much pain are you in today?") also represent ordinal data. Fundamentally, these scales do not represent a measurable quantity. An individual may respond 8 to this question and be in less pain than someone else who responded 5. A person may not be in half as much pain if they responded 4 than if they responded 8. All we know from this data is that an individual who responds 6 is in less pain than if they responded 8 and in more pain than if they responded 4. Therefore, Likert-type scales only represent a rank ordering.

Interval: A scale which represents quantity and has equal units but for which zero represents simply an additional point of measurement is an interval scale. The Fahrenheit scale is a clear example of the interval scale of measurement. Thus, 60 degree Fahrenheit or -10 degrees Fahrenheit are interval data. Measurement of Sea Level is another example of an interval scale. With each of these scales there is

direct, measurable quantity with equality of units. In addition, zero does not represent the absolute lowest value. Rather, it is point on the scale with numbers both above and below it (for example, -10 degrees Fahrenheit).

Ratio: The ratio scale of measurement is similar to the interval scale in that it also represents quantity and has equality of units. However, this scale also has an absolute zero (no numbers exist below the zero). Very often, physical measures will represent ratio data (for example, height and weight). If one is measuring the length of a piece of wood in centimeters, there is quantity, equal units, and that measure can not go below zero centimeters. A negative length is not possible.

The table below will help clarify the fundamental differences between the four scales of measurement.

Indications Difference Indicates Direction Indicates Amount Absolute ZeroOf difference Of difference

Nominal XOrdinal X XInterval X X XRatio X X X X

You will notice in the above table that only the ratio scale meets the criteria for all four properties of scales of measurement.

Interval and Ratio data are sometimes referred to as parametric and Nominal and Ordinal data are referred to as nonparametric. Parametric means that it meets certain requirements with respect to parameters of the population (for example, the data will be normal - the distribution parallels the normal or bell curve). In addition, it means that numbers can be added, subtracted, multiplied, and divided. Parametric data are analyzed using statistical techniques identified as Parametric Statistics. As a rule, there are more statistical technique options for the analysis of parametric data and parametric statistics are considered more powerful than nonparametric statistics. Nonparametric data are lacking those same parameters and can not be added, subtracted, multiplied, and divided. For example, it does not make sense to add Social Security numbers to get a third person. Nonparametric data are analyzed by using Nonparametric Statistics.

As a rule, ordinal data is considered nonparametric and can not be added, etc.. Again, it does not make sense to add together first and second place in a race - one does not get third place. However, many assessment devices within the behavioral and social sciences (for example, intelligence scales) as well as Likert-type scales represent ordinal data but are often treated as if they are interval data. For example, the "average" amount of pain that a person reports on a Likert-type scale over the course of a day would be computed by adding the reported pain levels taken over the course of the day and dividing by the number of times the question

was answered. Theoretically, as this represents ordinal data, this computation should not be done.

As stated above, many measures (ie. personality, intelligence, psycho-social, etc.) within the behavioral and social sciences represent ordinal data. IQ scores may be computed for a group of individuals. They will represent differences between individuals and the direction of those differences but they lack the property of indicating the amount of the differences. Psychologists have no way of truly measuring and quantifying intelligence. An individual with an IQ of 70 does not have exactly half of the intelligence of an individual with an IQ of 140. Therefore, IQ scales should theoretically be treated as ordinal data.

In both of the above illustrations, the statement is make that they should be theoretically treated as ordinal data. In practice, however, they are usually treated as if they represent parametric (interval or ratio) data. This opens up the possibility for use of parametric statistical techniques with these data and the benefits associated with the use of techniques.

3. The purchase behaviour of a customer and his psychological make-up can be an important basis for segmenting customers. Discuss how.

Ans:- Market segmentation is the identification of portions of the market that are different from one another. Segmentation allows the firm to better satisfy the needs of its potential customers.The Need for Market Segmentation

The marketing concept calls for understanding customers and satisfying their needs better than the competition. But different customers have different needs, and it rarely is possible to satisfy all customers by treating them alike.

Mass marketing refers to treatment of the market as a homogenous group and offering the same marketing mix to all customers. Mass marketing allows economies of scale to be realized through mass production, mass distribution, and mass communication. The drawback of mass marketing is that customer needs and preferences differ and the same offering is unlikely to be viewed as optimal by all customers. If firms ignored the differing customer needs, another firm likely would enter the market with a product that serves a specific group, and the incumbant firms would lose those customers.

Target marketing on the other hand recognizes the diversity of customers and does not try to please all of them with the same offering. The first step in target marketing is to identify different market segments and their needs.

Bases for Segmentation in Consumer Markets

Consumer markets can be segmented on the following customer characteristics.

* Geographic * Demographic * Psychographic * Behavioralistic

Psychographic Segmentation

Psychographic segmentation groups customers according to their lifestyle. Activities, interests, and opinions (AIO) surveys are one tool for measuring lifestyle. Some psychographic variables include:

* Activities * Interests * Opinions * Attitudes * Values

Behavioralistic Segmentation

Behavioral segmentation is based on actual customer behavior toward products. Some behavioralistic variables include:

* Benefits sought * Usage rate * Brand loyalty * User status: potential, first-time, regular, etc. * Readiness to buy * Occasions: holidays and events that stimulate purchases

Behavioral segmentation has the advantage of using variables that are closely related to the product itself. It is a fairly direct starting point for market segmentation.

4. Explain the various approaches used in test marketing.

Ans:- A test market, in the field of business and marketing, is a geographic region or demographic group used to gauge the viability of a product or service in the mass market prior to a wide scale roll-out. The criteria used to judge the acceptability of a test market region or group include:

1. a population that is demographically similar to the proposed target market; and 2. relative isolation from densely populated media markets so that advertising to the test audience can be efficient and economical.

The test market ideally aims to duplicate 'everything' - promotion and distribution as well as 'product' - on a smaller scale. The technique replicates, typically in one area, what is planned to occur in a national launch; and the results are very carefully monitored, so that they can be extrapolated to projected national results. The `area' may be any one of the following:

* Television area * Internet online test * Test town * Residential neighborhood * Test site

A number of decisions have to be taken about any test market:

* Which test market? * What is to be tested? * How long a test? * What are the success criteria?

The simple go or no-go decision, together with the related reduction of risk, is normally the main justification for the expense of test markets. At the same time, however, such test markets can be used to test specific elements of a new product's marketing mix; possibly the version of the product itself, the promotional message and media spend, the distribution channels and the price. In this case, several `matched' test markets (usually small ones) may be used, each testing different marketing mixes.

Clearly, all test markets provide additional information in advance of a launch and may ensure that launch is successful: it is reported that, even at such a late stage, half the products entering test markets do not justify a subsequent national launch. However, all test markets do suffer from a number of disadvantages:

1. Replicability - Even the largest test market is not totally representative of the national market, and the smaller ones may introduce gross distortions. Test market results therefore have to be treated with reservations, in exactly the same way as other market research. 2. Effectiveness - In many cases the major part of the investment has already been made (in development and in plant, for example) before the `product' is ready to be test marketed. Therefore, the reduction in risk may be minimal; and not worth the delays involved. 'Competitor warning'. All test markets give competitors advance warning of your intentions, and the time to react. They may even be able to go national with their own product before your own test is complete. They may also interfere with your test, by changing their promotional activities (usually by massively increasing them) to the extent that your results are meaningless.

3. Cost- Although the main objective of test markets is to reduce the amount of investment put at risk, they may still involve significant costs.

5. Explain the various methods of pre-testing and post-testing advertisements.

Ans:- Pre Testing Advertising Campaigns

Advertisements can be researched prior to their release (pre-test) or after they have been released (post-test). Pre-tests are sometimes referred to as copy tests.The methods used to pre-test advertisements are based upon either qualitative or quantitative criteria. The most common methods used to pre-test advertisements are concept testing, focus groups, consumer juries, dummy vehicles, readability, theatre and physiological tests. Focus groups are the main qualitative method used and theatre or hall tests, the main quantitative tests.The primary purpose of testingadvertisements during the developmental process is to ensure that the final creative will meet the advertising objectives.

The practical objective of pre-testing unfinished and finished creative work is that it is more effective for an advertiser to terminate an advertisement before costs become so large and commitment too final. Changes to an advertisement that are made too late may be resisted partly because of the sunk costs and partly because of the political consequences that ‘pulling’ an advertisement might have.Once a series ofadvertisements has been roughed or developed so that its messages can be clearly understood, advertisers seek reassurance and guidance regarding which of the alternatives should be developed further.

Concept tests, in-depth interviews, focus groups and consumer juries can be used to determine which of the proposed advertisements are the better ones by using ranking and prioritization procedures. Of those selected, further testing can be used to reveal the extent to which the intended message is accurately decoded. These comprehension and reaction tests are designed to prevent inappropriateadvertisements reaching the finished stage.

Advertising Post-Testing

The projective techniques are used to overcome the barriers of rationality, logicality and politeness, which often play an important role in case of direct questioning. In direct questioning people often tend to give politically correct answers that are considered right by many. Also they try not to hurt the researcher and thus avoid negative answers. In case of projective techniques, an indirect approach is adopted. Instead of asking questions, the respondents are subjected to different test. These

include the associations test, sentence completion test and thematic appreciation test.

Association tests attempts to get an immediate response to a stimulus such to get an immediate responses to a stimulus such as a word or picture by asking the respondent to say the first thing that comes to his mind.

Sentence completion tests are an extension of the association test. Here the respondents are given incomplete test use pictures, which are shown to respondents. They are asked to tell stories about the pictures. These descriptions and interpretations are analyzed to find out about their attitudes.

In depth interviewing the respondent is first put at ease by the researcher while he tries to build up a rapport with the respondents. Then the respondents are asked leading or probing questions to bring out his underlying subconscious reaction to the brand or organization advertised. The questions are never structures and the interview is always conducted in a free and cordial manner. The flexibility and freeness brings out many facts. Which usually are hidden beneath the conscious mind of the respondent? Depth interviewing needs to be conducted by highly skilled and trained psychologists to be able to fully explore the attitude of respondents.

One often face the problem of artificiality a while conducting pre-testing. This problem is easily overcome during post-testing. Post-tests attempt to measure the actual effect of real advertisements in real situations. This is a more practical approach to measure the effectiveness of car mat advertisements. Different types are conducted as part of post-testing advertisements. Whatever the purpose of a car mat advertisement, its first task is to be seen, read, or heard. Every advertisement uses some means or other to get attention and hold it. Here comes the first big hurdle recognition. This is simply a matter of identifying an advertisement that one has seen before. Recognition is a necessary condition for effective advertising. If advertisements cannot pass this hurdle, it will probably not be effective. Recognition tests are usually used for print ads.

While many types of recognition have been designed for the car mats advertisements. The starch recognitions test sends newspaper or magazine to respondents and then sends interviews to conduct the tests. Starch tests usually finds out the recognition rates of various elements of the ads like the visual or illustration, headline, logo, body copy, color, size, shape etc.------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

ASSIGNMENT-III

1. How does sales forecasting affect the other decisions of a company? Briefly discuss the factors that lead to an accurate sales forecast.

Ans:- Sales forecasts are common and essential tools used for business planning, marketing, and general management decision making. A sales forecast is a projection of the expected customer demand for products or services at a specific company, for a specific time horizon, and with certain underlying assumptions.

A separate but related projection is the market forecast, which is an attempt to gauge the size of the entire market for a certain class of goods or services from all companies serving that market. Sales and market forecasts are often prepared using different methods and for different purposes, but sales forecasts in particular are often dependent at least somewhat on market forecasts. Although the focus of this discussion will be on sales forecasting, a brief summary of market forecasting will help provide context.

A special term in studying sales and market forecasts is the word "potential." This refers to the highest possible level of purchasing, whether at the company level or at the industry or market level. In practice, full potential is almost never reached, so actual sales are typically somewhat less than potential. Hence, forecasts of potential must be distinguished from forecasts that attempt to predict sales realized.

SALES POTENTIAL AND FORECASTING

Sales forecasting is an attempt to predict what share of the market potential identified in a market forecast a particular company expects to have. For very small companies that serve only a fraction of the total market, the company forecast may not even explicitly consider the market forecast or share, although implicitly, of course, the company's sales are subsumed under the total market size. In the other extreme, a monopoly's sales forecast is essentially the same as the market forecast.

Forecasts of different kinds are often prepared at different levels of a corporate enterprise. Managers of different stripes use forecasts for a variety of purposes, including marketing planning, resource\investment allocation, production scheduling, and labor recruitment. In some cases the uses are simply informational, but in many cases forecasts are the basis for major decisions like:

* what product lines to pursue * how much to spend on production and in what ways * how aggressively to advertise or promote the products * how best to get the products to market in order to fulfill the projected demand

Yet sales forecasts are conditional in that they are only estimations and are highly interdependent with corporate strategy and actions. Some forecasts are developed before strategies and action plans are formulated; others are created to gauge the anticipated effects of an existing strategy.

A sales forecast may cause management to adjust some of its assumptions or decisions about production and marketing if the forecast indicates that (1) the current production capacity is grossly inadequate or excessive and (2) sales and marketing efforts are inconsistent with the expected outcomes. Management therefore has the opportunity to examine a series of alternate plans for changes in resource commitments (such as plant capacity, promotional programs, and market activities), changes in prices, or changes in production scheduling. Indeed, when a company is evaluating different courses of action it may develop separate forecasts for each option in order to assess the implications of each.

2. What are the objectives of the Market Research Society of India (MRSI)? Briefly describe the significance of television ratings as a source of information.

Ans:- Market Research Society of India (MRSI), a unique non-profit autonomous market research body formed by a large fraternity of research suppliers and users spread across India. Established in January 1988, the MRSI is at the forefront of maintaining standards of excellence in the market research industry. It is a proactive, dynamic and neutral society, continually striving to promote the needs of market research in India.

The Objectives of the MRSI

(a) To promote, protect, improve, market research in all its branches

(b) To organize or form organizations for the development and regulation of the field of market research and to afford opportunities in the field of market research to secure the recognition for the art and science of market research from the public, advertisers, advertising agencies, publishers and the Government

(c) To organize and hold exhibitions, lectures, classes, debates, conferences, tours, excursions or any other functions for the furtherance of the objects of the Society

(d) To promote the art and science of marketing research for diffusion of knowledge acquired by such research to advertisers, publishers and public, and like minded institutions

(e) To provide and maintain libraries, and such other services and protect the field of market research

(f) To collect, classify, circulate and / or publish statistics and other information relating to commercial interests, so as to diffuse commercial information and knowledge amongst members

(g) To establish just and equitable principles in the field of market research and regulate or restrict the conduct in the field of market research and to deal with such matters

(h) To take all steps which may be necessary for promoting, supporting or proposing legislation, notifications, orders or other instruments affecting the aforesaid interest by the Government, or any other department thereof, or by any local bodies and in general to take the initiative to secure the welfare of the market research community in all respects

(i) To institute and establish scholarships, rewards, grants and prizes to encourage the schemes of instruction in market research

(j) To co-operate with Universities, educational and research institutions or bodies and to make payment for any charitable or useful purposes

(k) To co-operate, associate or amalgamate with any other Association or Society or to become affiliated to any Association or Federation having objects altogether or in any part similar to those of this Society

(l) To do all such other lawful things as are incidental or conducive to the attainment of the above objects

(m) To carry out surveys in cities, towns and villages to investigate use of family planning aids presently being used to enhance their use by finding out reasons for refusal or reluctance to take to family planning and convey this data to the Union and State Ministry of health and social welfare as well as the family planning association of India, educational institutes, and other related organizations

(n) To carry out surveys in cities of those categories coming under the term disabled namely deaf, blind, dumb, spastics, orthopedically handicapped, mentally handicapped and convey this data to the Ministries both at the central and state levels as well as educational and Social Welfare Institutions and organizations working for the welfare of the handicapped

(o) To carry out surveys in cities in locations where drug usage is widespread, to gauge extent of drug addiction among various strata of society, their availability and prices at different locations and convey this information to the concerned bodies

(p) To aid other charitable organisations with a view to furthering their aims and activities.

Television content rating systems give television viewers an idea of the suitability of a television programme for children and/or adults. Many countries have their own television rating system and each country's rating process may differ due to local

priorities. Programs are rated by either the organization that manages the system, the broadcaster or by the content producers themselves.

A rating is usually set for each individual episode of a television series. The rating can change per episode, network, rerun and per country. As such it is impossible to state what kind of rating a programme has, without stating when and where this rating applied.

Ratings

Many advertisers and viewers think of ratings simply as a measure of a particular show’s popularity. That’s only the surface of a critical element in advertising. Ratings are expressed in points, and it’s true that the more rating points a show posts the more viewers it has. The actual meaning to an advertiser is much more important. Each rating point is one percent of the total TV audience in the market. For example, if there are 100,000 potential TV viewers in a market, one rating point means that 1,000 of them were watching. The more rating points a station delivers for a TV spot, the more people are exposed to its offer.Gross Rating Point

GRPs measure the total exposure a spot receives. If a spot runs in a show that has a 7 rating, then another show with a 10 rating, followed by another that has a 9 rating, the spot has accumulated 26 GRPs. That doesn’t mean that 26 percent of the potential total viewership has seen it, because some viewers will have seen it each time. That’s why many advertisers feel they need at least 300 GRPs to give their entire target segment an opportunity to see their message. More is better, and some advertisers prefer schedules with 500 to 700 GRPs to make certain their message is seen, and seen often.

Share

Obviously, not all potential viewers are watching TV all the time. It’s useful to measure a show’s popularity in terms of its proportion of all viewers watching TV at the time. For example, if a show has 32 share, that means it has nearly a third of all the viewers who are watching TV at that time.Frequency

Repetition is one of the foundations of advertising. A rule of thumb is that it takes at least five to seven repetitions of a spot for a viewer to recall the message and, ideally, act on it through purchasing behavior. In TV ad speak, frequency denotes the average number of times a household or person saw the spot in a specific period of time. Look for a schedule that features the highest frequency possible for the cost.Reach

This measure indicates the unduplicated number of households or individuals who were exposed to a spot during the schedule, usually expressed as a percentage. If the

schedule shows a reach of 74, for example, nearly three-quarters of all potential viewers were exposed to the spot. The higher the reach, the more of the entire audience the spot has touched.Cost Per Point and Cost Per Thousand

These are straightforward ways to quantify how much viewership a spot gets for the dollars spent airing it. These measures allow comparisons of stations' advertising prices to make most efficient use of budgets. Cost per point is the cost for each rating point purchased. Cost per thousand, abbreviated as CPM, reflects the advertising cost per thousand viewers exposed to a spot.

3. What are the characteristics of a good questionnaire? ABC Ltd is planning to launch a new brand of fruit juices.They want to conduct a survey to understand the preferences of the consumers. Design a questionnaire to address this research problem.

Ans:- Characteristics of a Good Questionnaire

Questions worded simply and clearly, not ambiguous or vague, must be objective· Attractive in appearance (questions spaced out, and neatly arranged)· Write a descriptive title for the questionnaire· Write an introduction to the questionnaire· Order questions in logical sequence· Keep questionnaire uncluttered and easy to complete· Delicate questions last (especially demographic questions)· Design for easy tabulation· Design to achieve objectives· Define terms· Avoid double negatives (I haven't no money)· Avoid double barreled questions (this AND that)· Avoid loaded questions ("Have you stopped beating your wife?")· Phrase questions for all respondents

Usual Food ChoicesThese questions are about the types of foods you ate during ____________________________________.

4. How is the target population defined in a research design? How is the size of the sample determined? You have been asked to carry out a product research on shaving blades in Andhra Pradesh and Maharashtra. What would be your target population?

Ans:- It is incumbent on the researcher to clearly define the target population. There are no strict rules to follow, and the researcher must rely on logic and judgment. The population is defined in keeping with the objectives of the study.

Sometimes, the entire population will be sufficiently small, and the researcher can include the entire population in the study. This type of research is called a census study because data is gathered on every member of the population.

Usually, the population is too large for the researcher to attempt to survey all of its members. A small, but carefully chosen sample can be used to represent the population. The sample reflects the characteristics of the population from which it is drawn.

Sampling methods are classified as either probability or nonprobability. In probability samples, each member of the population has a known probability of being selected. Probability methods include random sampling, systematic sampling, and stratified sampling. In nonprobability sampling, members are selected from the population in some nonrandom manner. These include convenience sampling, judgment sampling, quota sampling, and snowball sampling. The other common form of nonprobability sampling occurs by accident when the researcher inadvertently introduces nonrandomness into the sample selection process. The advantage of probability sampling is that sampling error can be calculated. Sampling error is the degree to which a sample might differ from the population. When inferring to the population, results are reported plus or minus the sampling error. In nonprobability sampling, the degree to which the sample differs from the population remains unknown. (McDaniel and Gates, 1991)

Random sampling is the purest form of probability sampling. Each member of the population has an equal chance of being selected. When there are very large populations, it is often difficult or impossible to identify every member of the population, so the pool of available subjects becomes biased. Random sampling is frequently used to select a specified number of records from a computer file.

Systematic sampling is often used instead of random sampling. It is also called an Nth name selection technique. After the required sample size has been calculated, every Nth record is selected from a list of population members. As long as the list does not contain any hidden order, this sampling method is as good as the random sampling method. Its only advantage over the random sampling technique is simplicity.

Stratified sampling is commonly used probability method that is superior to random sampling because it reduces sampling error. A stratum is a subset of the population that share at least one common characteristic. The researcher first identifies the relevant stratums and their actual representation in the population. Random sampling is then used to select subjects for each stratum until the number of subjects in that stratum is proportional to its frequency in the population.

Convenience sampling is used in exploratory research where the researcher is interested in getting an inexpensive approximation of the truth. As the name implies, the sample is selected because they are convenient. This nonprobability method is often used during preliminary research efforts to get a gross estimate of the results, without incurring the cost or time required to select a random sample.

Judgment sampling is a common nonprobability method. The researcher selects the sample based on judgment. This is usually and extension of convenience sampling. For example, a researcher may decide to draw the entire sample from one "representative" city, even though the population includes all cities. When using this method, the researcher must be confident that the chosen sample is truly representative of the entire population.

Quota sampling is the nonprobability equivalent of stratified sampling. Like stratified sampling, the researcher first identifies the stratums and their proportions as they are represented in the population. Then convenience or judgment sampling is used to select the required number of subjects from each stratum. This differs from stratified sampling, where the stratums are filled by random sampling.

Snowball sampling is a special nonprobability method used when the desired sample characteristic is rare. It may be extremely difficult or cost prohibitive to locate respondents in these situations. Snowball sampling relies on referrals from initial subjects to generate additional subjects. While this technique can dramatically lower search costs, it comes at the expense of introducing bias because the technique itself reduces the likelihood that the sample will represent a good cross section from the population.

5. Explain the role of marketing research in new product development. What are the research methods used to test the feasibility of a new product launch?

Ans:- The role of marketing research

"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.------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

CASE - 1

Questions:1. Evaluate the market for shampoos in terms of the potential of various pack sizes in the rural and urban markets.

Ans:- The shampoo market in India has changed significantly since the 1960s when it first became a lifestyle product in urban homes. As of 2008, it was a very competitive market with dominant players such as Hindustan Unilever Ltd. and Procter & Gamble Company. Analysts expect competition in the market to intensify further with the entry of companies such as ITC Ltd. The market is marked by intense competition from domestic as well as multinational companies. The changing dynamics in the industry coupled with comparatively low penetration rates offer the players in this market the opportunity to grow in both the top and bottom ends of the market, according to analysts. Shampoos for hair care are

comparatively of recent origin in India. Penetration of shampoos in urban areas has grown from 240 households (hhs) per 1,000 in 1992-1993 to 810 hhs per 1,000 in 2001-2002. In rural India, penetration of shampoos has risen from 50 hhs to 239 hhs. In urban lower middle income class, penetration has increased from 215 hhs to 777 hhs.

Penetration is expected to soar by nearly 100 percent in urban middle, upper middle, and high classes by 2006-2007. The shampoo market in India is valued at Rs 4.5 bn with the penetration level at 13% only. The market is expected to increase due to lower duties and aggressive marketing by players Shampoo is also available in a sachet, which is affordable and makes upto 40% of the total shampoo sale.

The Indian shampoo market is characterised by a twin-benefit platform: cosmetic and anti-dandruff. It is basically an upper middle class product, as more than 50% of the consumers use ordinary toilet soap for washing hair.

While the awareness level is high, the penetration level is very low even in the metros which is only 30%. Urban markets account for 80% of the total shampoo market, The penetration level is rapidly increasing due to decline in excise duty, which was 120% in 1993 to 30% currently.

2. Critically evaluate the performance of Clinic Plus in different markets.

Ans:- launching clinic plus in india• Understand the issues and challenges in launching a brand in themarket.» Study the hair care market in India and examine how UnileverLaunched Clinic Plus in the country.

» Analyze the promotional strategies adopted by Unilever to promote the Clinic Plus brand in India, particularly the‘Hairapy’ and the global ‘Life Can’t Wait’ campaign.

» Analyze the future prospects of Clinic Plus brand in India andexplore strategies that the company can adopt.

Largest beauty shampoo brand in the country. Positioned as the 'Hair Expert'

It was launched in India in 1964. In the initial years in India, Clinic plus was a cosmetic beauty shampoo. Within ten years of its launch in India Clinic Plus launched a tonic shampoo for dandruff, which was the first anti-dandruff shampoo in India.

In the India, Unilever’s goal was to position clinic plus as a brand that understood the problems faced by women and their needs and preferences.

HINDUSTAN UNILEVER claims to practice value-based pricing in which the customers’ perception of the product’s price provides a starting point for developing the marketing mix of the product. The research department determines this price usually by using focus groups. The price of Re 1 and 2 for Clinic plus shampoo sachets shows how the price also reflects a concern to make the purchase more convenient, since the rupee is denoted in this value.

3. In order to increase HLL’s market share, suggest an appropriate strategy in terms of the markets, the consumers, the pack sizes, etc., to focus on.

Ans:- Shampoo is the personal hygienic product and has a large market. So, it is important to determine which factors play the pivotal role to influence the consumer purchasing behaviour. In this assignment, the first factor is quality, country of origin-brand, theory of consumer ethnocentrism, and the social influence. These variables form a combination to produce an impact as to manifest our different behaviour of a consumer.

OPPORTUNITIES

•Population expanding at a rapid rate.•Consumers are becoming more quality conscious•Current capacity utilization is 80%, which can be further broadened with the increase in demand.•Customer base is increasing with effective marketing.•Baby shampoo is another area where HINDUSTAN UNILEVERs can make huge gains.•Shampoo plus conditioner and anti-dandruff shampoos are another area where HINDUSTAN UNILEVER can earn huge profits.

Rural areas are a large prospective market where they can introduce Clinic plus.

PROMOTION•Build top of the line consumers’ awareness.•Creating a personality of the brand.

Besides having these general objectives, the advertising objectives are set avoiding to the advertising strategy for each product, e.g. Clinic plus advertising objectives since it was being re-launched were:

•To increase the usage.•Conditioning benefits.•Makes the hair appear clean and shiny.•Imparts a feeling of freshness-due to fragrance.

•Easy to manage, silky, soft hair.•Unique shampoo for every hair type.•Effectively communicate brand promise.

RECOMMENDATIONS

Emphasis on quality and resultsBy adding free products or offeringsAttractive packagingNew emerging countriesGlobal expansionShampoos for seniors and male segment after doing hormonal and environmental

research. If dermatologist consult must be there which helps company to formulate new Shampoos

------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------CASE - 2Questions:(i) What type of study is this?(ii) What sample design should be used by the Company?(iii) Design a suitable questionnaire.

Ans:- Q1. From which place you generally buy the food products. ?Ans. i) Hawkers [ ] ii) Convenience store [ ]

iii) Kiryana store [ ] iv) Others, plz specify…

Q2. What is your preference for food products. ?Ans. i) Prefer packed/ branded items. [ ]ii) prefer packed/ without brand. [ ]iii)Prefer unpacked/ without brand items. [ ]

Q3.Have you ever experienced sales promotions in store. ?Ans. i) yes [ ] ii) No [ ]

Q4. Do you like the sales promotions plans ?Ans. i) Yes [ ] ii) No [ ]

Q5. Tick ,the sales promotions plans which you prefer most ?Ans. Most preferred Neutral Less Preferred Least

Preferred Preferred

i) Buy more and save

ii) Two or more packs attached

iii) Home delivery service

iv) Buy one get one free

v) Provide a chance to win large prizes

vi) Price off

vii) Bulk purchase price offers (BPP)

viii) Welcome drinks

Q6.Demographic Profile-:

Gender i. Male [ ] ii. Female [ ]Marital status i. Single [ ] ii. Married [ ]Age i. Below 20 yrs [ ] ii. 21-35 yrs [ ]

iii. 36-45 yrs [ ] iv. Above 45 yrs [ ]

Educationi. Under Graduate [ ] ii. Graduate [ ]iii. Post Graduate [ ] iv. Doctrate [ ]Anyother,please specify…………………………………………………….

Q7.Which is the stage of your family in family life cycle ?Ans. i) Unmarried/single [ ] ii) Married couple with no

child [ ]iii) Parents with young child [ ]iv)Parents with working child [ ]v) Retired/independent children [ ]vi)Anyother………………………………………

Q8. Whether your wife/or mother is working ?Ans. i) Yes [ ] ii) No [ ]

Q9.Kindly specify your annual family income. ?Ans. i) Uptp 2 lakh [ ] ii) 2 lakh-4lakh Rs [ ]iii) 4lakh-6lakh Rs [ ] iv) above 6 lakh Rs [ ]vi)Please, specify others…………………………………………………….

Q10. What is your occupation status ?Ans. i) Business [ ] ii) Self employeed [ ]iii) Farmer [ ]iv) Govt job [ ] v) Student [ ]vi) Professional [ ] vi) Please specify

other………………………………………