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  • 1. 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.
  • 2. Marketing Plan 􀂙 What is a marketing plan ? - A marketing plan is a written document that summarizes what the marketer has learned about the marketplace and indicates how the firm plans to reach its marketing objectives. - It is the act of putting together in a plan, the various elements of the marketing mix in a forecasted / futuristic approach �
  • 3. 􀂙 Components of MIS : - Internal company records - Marketing intelligence system - Marketing research 􀂙 MIS provides information on: - Buyer wants, preferences and behaviour - Consumption patterns across geographic areas Thus the companies can : - Choose its markets better, develop better offerings, and execute better planning
  • 4. Marketing information system A marketing information system consists of people, equipment , procedures to gather, sort, analyse, evaluate & distribute needed, timely and accurate information to marketing decision makers.
  • 5. What is ?
  • 6. Research means – 1. A systematic search for facts 2. Answers to questions and solutions to problems
  • 7.  1. What is marketing research ?  The systematic gathering, recording and analysing of data about problems related to the marketing of goods and services
  • 8. 2. Purpose of research : - Decision making tool - facilitation - Risk reduction - Discovering profitable opportunities 3. Marketing research acts as a marketing tool in the following areas of sales and marketing. - Study of consumer behaviour - Product design - Designing distribution channels - Advertising design – through consumer perception - Social marketing
  • 9. 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 future objective
  • 10. 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.
  • 11. 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.
  • 12. 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.
  • 13. 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.
  • 14. Formulation of a research problem is far more essential than its solution Albert Einstein 1938
  • 15.  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
  • 16.  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
  • 17. 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.
  • 18. 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
  • 19.  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.
  • 20.  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.
  • 21. 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.
  • 22.  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
  • 23.  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.
  • 24. 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
  • 25.  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.
  • 26. Sampling methods or Sampling techniques Sampling Designs:  Two generic types: 1. Probability or random sampling, and 2. Non-probability or Non-random sampling
  • 27. Probability or random sampling A. Simple designs 1. Simple random sampling 2. Stratified random sampling 3. Systematic random sampling B. Complex designs 1. Cluster sampling 2. Area sampling 3. Multi-stage and sub-sampling 4. Random sampling with probability proportional to size 5. Double sampling and multiphase sampling 6. Replicated or interpenetrating sampling
  • 28. Non-probability or Non-random sampling A. Simple designs  Convenience or accidental sampling  Purposive (or Judgement ) sampling B. Complex designs 1. Quota sampling 2. Snow-ball sampling
  • 29.  Reasons for choosing different sampling designs. 1. Nature of population 2. Simplicity in adoption 3. Availability of frame 4. Representativeness 5. Nature of sampling unit 6. Cost of enumeration 7. Precision criterion
  • 30. Probability or random sampling A. Simple designs 1. 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.
  • 31. 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.
  • 32. 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.
  • 33. B. Complex designs 1. 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
  • 34. 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.
  • 35. 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
  • 36.  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.
  • 37. Non-probability or Non-random sampling A. Simple designs 1. Convenience or accidental sampling 2. Judgment sampling B. Complex designs 1. Quota sampling 2. Snow-ball sampling
  • 38. Non-probability or Non-random sampling A. Simple designs 1. 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
  • 39. 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.
  • 40. Complex designs 1. 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
  • 41. 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.
  • 42. Data Collection  Data are facts, figures and other relevant materials, past and present serving as basis for study and analysis.  Types of sources of data 1. Primary data 2. Secondary Data
  • 43. 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.
  • 44. 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.
  • 45. 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
  • 46. 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
  • 47. 1. Observation 2. Interviewing 3. Mail survey 4. Experimentation 5. Simulation 6. Projective technique
  • 48.  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
  • 49. Observation ParticipantParticipant observationobservation Non- participantNon- participant observationobservation DirectDirect observationobservation IndirectIndirect observationobservation ControlledControlled observationobservation Un-controlledUn-controlled observationobservation Researcher’s Role Mode of Observation System Adopted
  • 50. 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
  • 51.  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.
  • 52. 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.
  • 53.  Types of questions 1. 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
  • 54.  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
  • 55.  Question sequence 1. 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
  • 56.  Research Design  - Data collection  Observational research  Ethnographic group Research  Focus group Research  Survey research  Behavioral data  Experimental research( cause & effect relationships)
  • 57.  - Research instrument  Questionnaires: Close-end Open-end  Mechanical instruments: like,  Galvanometers-emotions  Tachistoscopes flashes  Eye cameras  Audiometer-TV  - Sampling plan
  • 58.  Field work  - Planning and supervision  Data Analysis  - Classifying raw data  - Summarising data  - Analytical methods to analyse and then make an inference
  • 59.  Application of research :  - Sales and market analysis  - Product research  - Corporate research  - Advertising research
  • 60. 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.
  • 61.  Forecasting and Demand measurement
  • 62. 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.
  • 63. Types of sales forecastTypes of sales forecast Product Level Time Period Geographic Area Salespersons 1. Total Sales 2. Industry sales 3. Company sales 4. Product line sales 5. Product variant sales 6. Product item sales 1. Long range 2. Medium range 3. Short range 1. World 2. Nation 3. Region 4. Territory 5. Customer
  • 64. Sales Forecasting  Sales forecasting is necessary for the other functions as follows: 1. Planning production 2. Raising finance 3. Purchase function 4. Human resources  Hence sales forecast is the forerunner for all other to all planning
  • 65. Terms used in sales forecast 1. Market potential 2. Market forecast 3. Sales potential 4. Sales forecast 5. Sales budget 6. Sales quota
  • 66. Methods of sales forecasting  Qualitative methods 1. Executive opinion method 2. Delphi method-Rand corporation by 1940 3. Sales force composite method 4. Test marketing method: full blown test market, controlled test marketing, simulated test marketing
  • 67. Quantitative methods 1. Moving average method: Actual sales for past 3 or 6 years Number of years 2. 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
  • 68. 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 series Sales forecast for next year= Actual sales of this year x Actual sales of this year Actual sales of last year
  • 69. 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.
  • 70. To improve forecasting accuracy: 1. Use multiple forecasting methods 2. Identify suitable method 3. Obtain a range of forecasts 4. Use computer hardware and software.
  • 71. Steps in sales forecasting As per the conference board of America report 1978, 10 steps are listed. 1. Determine the Purpose for which Forecasts are used 2. Divide the company products into homogenous groups 3. Determine the factors affecting the sales of each product and their relative importance 4. Choose the forecasting methods 5. Gather the available data 6. Analyse the data 7. Check and recheck the deductions 8. Make assumptions regarding other factors 9. Convert deductions and assumptions into forecasts
  • 72. 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
  • 73. Sales Budget Sales volume budget Sales department Administrative budget Selling expense budget
  • 74. 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
  • 75. 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
  • 76. Review Situation Communication Subordinate budgets Approval of budget Other departments Sales Budget Process