Mm23

MODULE 2: MARKETING TRENDS

1. Scanning the environment, 2. Marketing intelligence and

information system, 3. Market research system, 4. Demand measurement

and forecasting, 5. Data warehousing, 6. Data mining, 7. Changing consumption

pattern of global consumer and Indian consumer.

4. Six Steps in marketing research- Problem definition- Research design/plan- Field work/Collect information- Data Analysis- Report presentation- Make the decision

Problem definition –- Define the issue on hand- Give a correct overview of current scenario and futureobjective

1. Formulating research problem One should understand the problem

thoroughly and subsequently rephrase the same into meaningful terms.

The statement is important in a research because it determines the method of research, data to be collected, relations to be explored, techniques to be employed and the form of final report.

2. Review of Literature Reading books literature, earlier

thesis, journals, periodicals etc to find out if any work has already been carried out

If a similar work has been carried out the ‘research gap’ has to be found out and try to fill the gap.

5. Determining the sample design Random or probability sampling

and non-random or non-probability sampling

The units drawn from the universe or population to form a sample is called sampling.

6. Collecting data Generally the data in hand will not be

sufficient and hence additional data needs to be collected for research.

Primary data can be collected by observation, personal interview, questionnaires, schedules, video conferencing, etc

Secondary data can be gathered from published materials, articles, survey reports, journals, internet, etc.

Formulation of a research problem is far more essential than its solution

Albert Einstein 1938

Formulating research problem: Select the topic and formulate the research problem.

Research starts with a problem and the problem statement is the axis, around which the whole research revolves.

Problem formulation is the anchor of a research problem

The choice of a good research problem depends on the intuition, knowledge and expertise of the researcher.

Problem and purpose are different. If there is no clear problem

formulation, the purpose and methods are meaningless

Research Design After the formulation of the problem next

task is to build up a Research design to streamline the research

It determines ‘what and ‘how’ the researcher hopes to find the best solution to he problem.

Research design is about organising research activity, including collection of data in ways that are most likely to achieve the resarch goals and objectives.

Sampling

A sample as the name implies is smaller representative of a larger whole.

The method of selecting a portion of the universe for the study is known as sampling.

It helps to draw conclusions about the said universe

The entire group from which a sample is chosen is known as the population or universe

Census: A complete enumeration of all items in the population is known as census enquiry

Sampling frame: It is a list of items from which the sample is to be drawn.

Census is appropriate when the population size is small.

Also when the information is needed from each and every individual object suct as population census, industrial census, etc.

Sampling is the best course to adopt if the population size is large and if both the cost and time associated is limited.

Besides in destructive tests, sample can only be considered.

Survey

A survey is a planned observation of objects that are not controlled by the observer.

These objects are not themselves treated but the ‘Nature’ is assumed to have applied the treatments and all that analysts can do it to observe the consequences.

A survey is a process by which certain quantitative/qualitative facts pertaining to certain field of enquiry are collected to throw light on the objectives of a research problem.

A descriptive surveys are fact finding surveys

An analytical surveys deal with interrelations among different variables of interest and their interaction

A Survey of complete enumeration of population of interest is called Census.

A Survey based on a subset of the population which is also called as a sample is termed as sample survey.

Sampling or Sampling techniques

A sample as the name implies is smaller representative of a larger whole.

The method of selecting a portion of the universe for the study is known as sampling.

It helps to draw conclusions about the said universe

The entire group from which a sample is chosen is known as the population or universe

Census: A complete enumeration of all items in the population is known as census enquiry

Sampling frame: It is a list of items from which the sample is to be drawn.

Sampling methods or Sampling techniques Sampling Designs:

Two generic types:1. Probability or random sampling,

and 2. Non-probability or Non-random

sampling

Probability or random sampling

A. Simple designs1. Simple random sampling2. Stratified random sampling3. Systematic random samplingB. Complex designs1. Cluster sampling2. Area sampling3. Multi-stage and sub-sampling4. Random sampling with probability proportional to

size5. Double sampling and multiphase sampling6. Replicated or interpenetrating sampling

Non-probability or Non-random sampling

A. Simple designs Convenience or accidental

sampling Purposive (or Judgement ) samplingB. Complex designs1. Quota sampling2. Snow-ball sampling

Reasons for choosing different sampling designs.

1. Nature of population2. Simplicity in adoption3. Availability of frame4. Representativeness5. Nature of sampling unit6. Cost of enumeration7. Precision criterion

Probability or random sampling

A. Simple designs1. Simple random sampling Simple random sampling is the simplest of

all sampling designs Each and every item in the population has

an equal and independent chance of inclusion

This can be done for a homogenous population.

However for heterogeneous population a simple random sampling may not give the desired results.

2. Stratified random sampling This is used for a heterogeneous population. Here the population is stratified (Grouped)

into a number of overlapping sub-populations or strata and sample items are selected from each stratum.

Ex: In survey of business establishments, one may form large, medium and small establishments.

Further the sample selection from each strata is based on simple random selection.

3. Systematic random sampling Only the first unit is selected randomly and the

remaining units of the sample are selected at fixed intervals.

Ex: To choose every 10th name or 15th item and so on

In this method the entire list of the universe is given numbers

It is easier and less expensive It is spread more evenly over the entire population The main disadvantage is if there is a hidden

periodicity in the population, this may prove inefficient.

B. Complex designs1. Cluster sampling : This involves grouping of population and

then selecting the groups or clusters rather than individual elements for inclusion in the sample.

That is the total population is divided into a number of relatively small subdivisions which are themselves clusters of smaller units.

Further some of these clusters are randomly selected for inclusion in the overall selection

2. Area sampling Cluster sampling in the form of grids

imposed on maps in certain forms are is termed as Area sampling.

It will not be grouped by type of establishments like villages, industries, hospitals etc but based on areas.

Ex: National population or well defined political or natural boundaries.

Non-probability sampling This sampling does not provide a chance

of selection to each population The selection probability is known A non-probability sample may not be true

representative Population parameters cannot be

estimated from the sample values It suffers from sampling bias which

suffers from bias. Hence generally not advisable

When there is no other feasible method for collection of data or non-availability of population for collection of data.

When study does not need generalisation of conditions

When cost is a consideration When probability sampling needs more

time.

Non-probability or Non-random sampling

A. Simple designs1. Convenience or accidental

sampling2. Judgment samplingB. Complex designs1. Quota sampling2. Snow-ball sampling

Non-probability or Non-random sampling

A. Simple designs1. Convenience or accidental sampling: This method is employed to get

information quickly and inexpensively Depends on the convenience of the

researcher Keeps in view of the general

population

3.Judgment sampling: Judgment sampling is very appropriate

when it is necessary to reach small and specialized populations.

The researcher uses judgment to identify representative samples

A judgmental sampling is likely to be more reliable and representative than a probability sample.

However unwelcome bias might creep into results if not honestly judged.

Complex designs1. Quota sampling: We observe the responding units

non-randomly according to some fixed quota

It is to assure that the smaller groups are adequately represented

Bias can exist

2. Snow-ball sampling First someone is identified who meets

the criteria and further asked to include others.

Useful where representatives are inaccessible or hard to find

Inherent problem is one who is socially visible are likely to be selected.

Data Collection

Data are facts, figures and other relevant materials, past and present serving as basis for study and analysis.

Types of sources of data1. Primary data2. Secondary Data

1. Primary data are those which are collected afresh and for the first time and thus happens to be original in character

2. Secondary data are those which have already been collected by someone else and which have salready been passed through statistical process.

Primary data

1. Primary data Primary data are those which are collected afresh, for the first time and thus happens to be original in character.

2. First formal appearance of results in the print or electronic literature.

Secondary data

1. Secondary data are those which have already been collected by someone else and which have already been passed through statistical process.

2. Secondary sources are works that describe, interpret, analyse primary data

3. Comments and discussion of the evidence provided by primary sources

Methods of collecting Primary data.

In many cases the secondary data are inappropriate, inadequate or obsolete, primary data have to be gathered.

Primary data are directly collected by the researcher from their original source

Method is different from a tool One or more methods can be chosen No method is universal but has its own

uniqueness

1. Observation2. Interviewing3. Mail survey4. Experimentation5. Simulation6. Projective technique

Observation: Observation is defined as a systematic

viewing of a specific phenomenon in its proper setting for the specific purpose of gathering data for a particular study.

Observation includes both seeing and hearing.

The main body of knowledge has been developed by observing the nature

Observation

Participant Participant observationobservation

Non- participant Non- participant observationobservation

DirectDirect observationobservation

Indirect Indirect observationobservation

Controlled Controlled observationobservation

Un-controlled Un-controlled observationobservation

Researcher’s Role

Mode of Observation

System Adopted

Interviewing

One of the prominent method of data collection People are generally more willing to talk than to

write It is two way systematic conversation between

an investigator and an informant initiated for obtaining information relevant to a specific study.

It is not only conversation, but also learning from the respondent's gestures, expressions, pauses and environment

It is carried out in a structured schedule It calls for interviewing skills

Interviewing can be used as a main method or a supplementary method

It is the only method for gathering information from illiterate and uneducated method.

It can be used for collecting personal and intimate information relating to a person’s opinions, attitudes, values, future intentions etc.

Questionnaire

A questionnaire is a series of questions asked to individuals to obtain statistically useful information about a given topic.

When properly constructed and responsibly administered, questionnaires become a vital instrument

Questionnaires are frequently used in quantitative research.

They are a valuable method of collecting a wide range of information from a large number of individuals, often referred to as respondents. Good questionnaire construction is critical to the success of a survey.

Types of questions1. Contingency questions - A question that is

answered only if the respondent gives a particular response to a previous question. This avoids asking questions of people that do not apply to them

2. Matrix questions - Identical response categories are assigned to multiple questions.

3. Closed ended questions - Respondents’ answers are limited to a fixed set of responses. Most scales are closed ended. Other types of closed ended questions include:

1. Yes/no questions - The respondent answers with a “yes” or a “no”.

2. Multiple choice - The respondent has several option from which to choose.

3. Scaled questions - Responses are graded on a continuum (example : rate the appearance of the product on a scale from 1 to 10, with 10 being the most preferred appearance). Examples of types of scales include the Likert scale, semantic differential scale, etc

Open ended questions - No options or predefined categories are suggested. The respondent supplies their own answer without being constrained by a fixed set of possible responses. Examples of types of open ended questions include:

1. Completely unstructured - For example, “What is your opinion of questionnaires?”

2. Word association - Words are presented and the respondent mentions the first word that comes to mind.

3. Sentence completion - Respondents complete an incomplete sentence. For example, “The most important consideration in my decision to buy a new house is . . .”

4. Story completion - Respondents complete an incomplete story.

5. Picture completion - Respondents fill in an empty conversation.

6. Thematic apperception test - Respondents explain a picture or make up a story about what they think is happening in the picture

Question sequence1. Questions should flow logically from one to the

next. 2. The researcher must ensure that the answer to a

question is not influenced by previous questions. 3. Questions should flow from the more general to

the more specific. 4. Questions should flow from the least sensitive to

the most sensitive. 5. Questions should flow from factual and behavioral

questions to attitudinal and opinion questions. 6. Questions should flow from unaided to aided

questions. 7. The sandwich theory - three stage theory : Initial

questions should be screening and rapport questions. Then in the second stage you ask all the product specific questions. In the last stage you ask demographic questions

Research Design - Data collection Observational research Ethnographic group Research Focus group Research Survey research Behavioral data Experimental research( cause & effect

relationships)

- Research instrument Questionnaires:Close-endOpen-end Mechanical instruments: like, Galvanometers-emotions Tachistoscopes flashes Eye cameras Audiometer-TV - Sampling plan

Field work - Planning and supervision Data Analysis - Classifying raw data - Summarising data - Analytical methods to analyse

and then make an inference

Application of research : - Sales and market analysis - Product research - Corporate research - Advertising research

Barriers to the use of MR A narrow conception of Marketing

Research Uneven caliber of Marketing

researchers Poor framing of the problem Late and erroneous findings by

marketing research Personality and presentational

differences.

Forecasting and Demand measurement

Sales Forecasting

Forecasting is systematic attempt to predict the future by inference from the known facts.

Sales forecasting is an attempt to determine the value of sales which can be reasonably be expected at some future date on a scientific basis.

Types of sales forecastTypes of sales forecast

Product Level

Time PeriodGeographic

Area

Salespersons

1. Total Sales2. Industry sales3. Company sales4. Product line sales5. Product variant sales6. Product item sales

1. Long range2. Medium range3. Short range

1. World2. Nation3. Region4. Territory5. Customer

Sales Forecasting

Sales forecasting is necessary for the other functions as follows:

1. Planning production2. Raising finance3. Purchase function4. Human resources Hence sales forecast is the

forerunner for all other to all planning

Terms used in sales forecast

1. Market potential2. Market forecast3. Sales potential4. Sales forecast5. Sales budget6. Sales quota

Methods of sales forecasting

Qualitative methods1. Executive opinion method2. Delphi method-Rand corporation by 19403. Sales force composite method 4. Test marketing method: full blown test

market, controlled test marketing, simulated test marketing

Quantitative methods

1. Moving average method:Actual sales for past 3 or 6 yearsNumber of years2. Exponential smoothing method:Sales forecast for the next year=Actual

sales this year x (L) + (1-L) x (this years sales forecast)

L- smoothing constant or probability weighing factor 0.8 – 0.2

Quantitative Method

3. Decomposition method:The company’s previous periods sales

data is broken into four major components Trend, cycle, seasonal and erratic

4. Naive/Ratio method: Time seriesSales forecast for next year=Actual sales of this year x Actual sales of this year

Actual sales of last year

6. Regression analysis: Company sale is dependent on many factors such as price, promotional expenditure, population etc. Statistical forecasting - SPSS used- Multiple regression analysis is used

7. Econometric analysis : Many regression equations are built to forecast industry sales. A forecast is prepared by solving these equations on computer software.

To improve forecasting accuracy:

1. Use multiple forecasting methods2. Identify suitable method3. Obtain a range of forecasts4. Use computer hardware and

software.

Steps in sales forecastingAs per the conference board of America report 1978, 10 steps are listed.

1. Determine the Purpose for which Forecasts are used2. Divide the company products into homogenous

groups3. Determine the factors affecting the sales of each

product and their relative importance4. Choose the forecasting methods5. Gather the available data6. Analyse the data7. Check and recheck the deductions8. Make assumptions regarding other factors9. Convert deductions and assumptions into forecasts10. Apply the forecast to company operations

Sales Budget

A sales budget consists of estimates of expected volume of sales and selling expenses.

Sales budget is generally fixed slightly lower than the sales forecast to avoid risk

Selling expense budget consists of the selling expense budget and sales department administrative budget

The sales budget is the key factor for the successful performance of the sales department

Sales Budget

Sales volume budgetSales department

Administrative budget Selling expense budget

Purposes of the sales budget

1. Planning: From total corporate plan marketing and sales budgets are developed considering sales goals, sales strategy, action plan, expense, etc.

2. Coordination: Coordinating among various functions

3. Control : Evaluation of performance

Methods used for deciding sales expenditure budget

Sales managers are required to decide expenditure levels for each item of selling expenses.

1. Percentage of sales method

2. Executive judgment method

3. Objective and task method

Review Situation

Communication

Subordinate budgets

Approval of budget

Other departments

Sales Budget Process