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PART 1

PART 1. INSERT COURSE OUTLINE. MARKETING CASE REPORT FORMAT. Executive Summary: Self-Contained Document, one to two pages Statement of Purpose and Issues to be Addressed Research Method Used to Address Issues Salient Findings (Appears before Table of Contents). Table of Contents

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PART 1

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  1. PART 1

  2. INSERT COURSE OUTLINE

  3. MARKETING CASE REPORT FORMAT • Executive Summary: Self-Contained Document, one to two pages • Statement of Purpose and Issues to be Addressed • Research Method Used to Address Issues • Salient Findings (Appears before Table of Contents)

  4. Table of Contents • Subject and Page Numbers Including All Exhibit References • Introduction • Background • Purpose and/or Problem Definition • Objectives of Report • Methodology • Specific Methodology – Why!!! • Data/Information to be Studied • Case Analysis • Application of Specific Methodology to Case • Discussion/Explanation of Analysis • Interpretation of Tables and Charts. (It is not acceptable to merely refer to Tables, e.g., see Table X)

  5. Findings and/or Conclusions • Appendices • Other Requirements • Paragraph and Sub Paragraph headings • Identification of all exhibits which are to be explained and referenced in text • No Misspellings!!!! • Proper Grammar • Interesting Style • On Time Delivery of Oral and Written Report

  6. Marketing Research and the Four Ps • Products • New Products • Evaluating Packaging and Brand Designs • Compassion Studies With Competitor’s Products • Consumer Evaluation of Current Products • Place (Distribution Channels) • Analysis of Different Storage or Transportation Methods • Analysis of Alternative Sites • Determination Of Inventory Levels • Growth Rates of Different Channels • Promotion • Testing Different Ad. Messages • Establishing Sales Territories • Selecting Media • Evaluating Ad. Effectiveness • Pricing

  7. Research on Markets • Forecasting Demand • Providing Information of General Trends • Providing Information For Segmenting Markets • Developing Customer Profiles • Identifying New Markets For Existing Products • Identifying New Product Needs • Foreign Markets

  8. Price Place Product Promotion Elements Of The Marketing Mix That Compose A Cohesive Marketing Program Marketing Manager Product Features Brand name Packaging Service Warranty Place Outlets Channels Coverage Transportation Stock level Promotion Advertising Personal selling Sales promotion Publicity Price List price Discounts Allowances Credit terms Payment period

  9. PART 2

  10. Introduction to Marketing Research Dr. Doherty Tobin College of Business St. John’s University

  11. Marketing Research • Definition: • A scientific approach to • (a) the collection; (b) analysis; and (c) presentation • of data/information to be used in the management decision making process Three Generic Approaches • Exploratory • Descriptive • Casual/Experimental Applications: See Tables 1 and 2

  12. The Exploratory Approach Purpose: Identify Potential Relevant Factors (Don’t try to solve the problem!) • Develop Hypothesis • Establish priorities for further research • Identify information and data sources • Clarify concepts • Increase analysts’ familiarity with problem(s) • Identify potential causes

  13. The Exploratory Approach Five Popular Exploratory Approaches: • Literature Search • Experience Survey • Analysis of Selected Cases • Focus Groups • “Small” Sample/Surveys/Interviews

  14. The Descriptive Approach Purpose: Test Hypothesis • Analyze Data • Develop Findings/Conclusions Two Types (Depending on Type of Data) • Longitudinal (Time Series) • True Panel • Omnibus Panel • Cross Sectional • Field Survey • Field Study

  15. True Panel Application The Brand Switching Matrix or Turnover Table (see your textbook!)

  16. Applications of Turnover Table Evaluating: • Price Changes • Promotional Campaigns • New Packaging • New Products • Results can be integrated with other databases to determine customer profiles and media habits

  17. Causal/ExperimentalResearch Design • Scientific Criteria • Concomitant Variation • Time Sequence • Elimination of Other Causes • Controlled Experiment • Reflects 1. • Lab vs. Field • Validation • Two Groups: Experimental and Control • Basic Concepts Defined • Experiment : Process • Treatments : Alternatives • Test Units : Entities • Dependent Variables : Measures • Extraneous Variables • Hold Constant • Randomize Assignment of Treatments • Specific Design • ANCOVA

  18. Types of Evidence That Support a Causal Inference • Concomitant Variation– evidence of the extent to which X and Y occur together or vary together in the way predicted by the hypothesis • Time order of occurrence of variables- evidence that shows X occurs before Y • Elimination of other possible causal factors- evidence that allows the elimination of factors other than X as the cause of Y X– the presumed cause Y– the presumed effect

  19. Types of Experiments Laboratory Experiment Research investigation in which investigator creates a situation with exact conditions so as to control some, and manipulate other, variables. Experiment Scientific investigation in which an investigator manipulates and controls one or more independent variables and observes the dependent variable for variation concomitant to the manipulation of the independent variables Field Experiment Research study in a realistic situation in which one or more independent variables are manipulated by the experimenter under as carefully controlled conditions as the situation will permit.

  20. Types of Extraneous Factors That Can Contaminate Research Results History—Specific events external to an experiment, but occurring at the same time, which may affect the criterion or response variable. Maturation—Processes operating within the test units in an experiment as a function of the passage of time per se. Testing—Contaminating effect in an experiment due to the fact that the process of experimentation itself affected the observed response. Main testing effect—The impact of a prior observation on a later observation. Interactive testing effect—The condition when a prior measurement affects the test unit’s response to the experimental variable. Instrument Variation—Any and all changes in the measuring device used in an experiment that might account for differences in two or more measurements. Statistical Regression—Tendency of extreme cases of a phenomenon to move toward a more central position during the course of an experiment. Selection Bias—Contaminating influence in an experiment occurring when there is no way of certifying that groups of test units were equivalent at some prior time. Experimental Mortality—Experimental condition in which test units are lost during the course of an experiment.

  21. Test Marketing • Who? • Objectives • Forecasts: Sales, Market Share; CANNALBALISTIC EFFECTS • Pretest Market Mix • Serendipity • Key Decisions • How Many Cities? • 2 To 6 • Importance of Regional Differences Degree of Uncertainty • Which Cities? Syracuse Leonia Dayton Des Moines • Length Of Test? • 2 Months to 2 Years • Average Repurchase Period • Competition Concern • First to Market Importance

  22. Test Marketing Cont’d • What Data? • Warehouse Shipments • Store Audits • Consumer Panels • Buyer Surveys • Trade Attitudes • What Action?

  23. BAYESIAN WORK TABLE

  24. Computation of Expected Values From BAYESIAN Work Table Given Z1 (Test MKT. Results show Light D) EV(A1)= 100(.858) + 50 (.122) + -50(.02)= $90.9M EV(A2)= 50 (.858) + 100(.122) + -25(.02)= $54.6M EV(A3)= -50 (.858) + 0 (.122) + 80 (.02)= -$41.3M Z2 (Test MKT. Results Show Moderate D) EV(A1)= 100(.364) + 50 (.545) + -50(.091)= $59.1M EV(A2)= 50 (.364) + 100(.545) + -25(.091)= $70.4M EV(A3)= -50 (.364) + 0 (.545) + 80 (.091)= -$10.9M Z3 (Test MKT. Results Show Heavy D) EV(A1)= 100(.333) + 50 (.333) + -50(.333)= $33.3M EV(A2)= 50 (.333) + 100(.333) + -25(.333)= $41.6M EV(A3)= -50 (.333) + 0 (.333) + 80 (.333)= $10.0M

  25. Prob. OF Obtaining Each Test MKT. Result P(Zk) = j=1 k P(Sj) P(Zk/Sj) P(Z1) = P(S1)P(Z1/S1) + P(S2)P(Z1/S2) +P(S3)P(Z1/S3) = (.6) (.7) + .3(.2) + .1(.1) = 0.49 P(Z2) = P(S1)P(Z2/S1) + P(S2)P(Z2/S2) +P(S3)P(Z2/S3) = .6(.2) + .3(.6) + .1(.3) = 0.33 P(Z3) = P(S1)P(Z3/S1) + P(S2)P(Z3/S2) +P(S3)P(Z3/S3) = .6(.1) + .3(.2) + .1(.6) = 0.18

  26. Prob. OF Obtaining Each Test MKT. Result FORECASTS Decision Acts Opt. EV Prob. Z1 A1 90.9 0.49 Z2 A2 70.4 0.33 Z3 A3 41.6 0.18 EV(Research) = 90.9(.49) + 704.(.33) + 41.6(.18) = $75.26M EV(U) = ’70.0M Max Price For Res. = EV(R)-EV(U)= 75.26 – 70.0 = $5.26M

  27. Causal/ExperimentalResearch Design • Validation • Internal vs. External • Internal • History • Maturation • Mortality • Regression • Instrumentation • Selection Bias • Main Testing Effect • Interactive Testing Effect • Four Types of Experimental Research Designs • Pre Exp (3) • True Exp (3) • Quasi (3) • Advanced Statistical Design (4)

  28. Causal/ExperimentalResearch Design • Pre-Exp. Design (3) • After Only: X O • Before After: O X O • Static Group Comparisons: X O1 O2 Major Errors: H, SB

  29. Causal/ExperimentalResearch Design • True Experimental Design • Solomon 4 Group • Before/After with Randomization (R) and Control (C) EXT = ? ITE = ? X = ? • After Only with R and C Problem O1 = 100 O2 – 160 O3 = 106 O4 = 140 O5 = 150 O6 = 135

  30. Causal/ExperimentalResearch Design • Quasi Exp (3) • Single Time Series O1 O2 O3 X O4 O5 O6 • Multiple Time Series O'1 O'2 O'3 X O'4 O'5 O'6 • Separate Sample Before/After Design: Main Problem of Quasi Approach: History (Note: 9A is typical of consumer panel investigation data.)

  31. Causal/ExperimentalResearch Design • Advanced Statistical Design (4) • CRD • RBD • LSD • Factorial

  32. Part 2ADecision Making Under Uncertainty Criteria for Selecting the Best Option MAX/MIN MAX/MAX MIN/MAX-REGRET EXPECTED VALUE

  33. Value of Information • Payoff (Decision) Table AI : Decision Acts Ej : Events (or Sj = States of Nature) Eij : Payoff or Consequences Pj : Prob. Associated with Ej

  34. ILLUSTRATION

  35. Regret Table

  36. Part 2B Marketing Research Case Study Bayesian Analysis

  37. Bayesian Case Objective: Determine Value of Research

  38. Conditional Prob. Matrix

  39. Bayesian Work Table

  40. Computation of Expected Values from BAYESIAN Work Table Given: Z1 (Test MKT. Results show Light D) EV(A1) = 100(.858) + 50(.122) + -50(.02) = $90.9M EV(A2) = 50(.858) + 100(.122) + -25(.02) = $54.6M EV(A3) = -50(.858) + 0(.122) + 80(.02) = $-41.3M Z2 (Test MKT. Results show Moderate D) EV(A1) = 100(.364) + 50(.545) + -50(.091) = $59.1M EV(A2) = 50(.364) + 100(.545) + -25(.091) = $70.4M EV(A3) = -50(.364) + 0(.545) + 80(.091) = $-10.9M Z3 (Test MKT. Results show Heavy D) EV(A1) = 100(.333) + 50(.333) + -50(.333) = $33.3M EV(A2) = 50(.333) + 100(.333) + -25(.333) = $41.6M EV(A3) = -50(.333) + 0(.333) + 80(.333) = $10.0M

  41. Probability of Obtaining Each Test MKT. Result P(Zk) = P(Sj)P(Zk/Sj) P(Z1) = P(S1)P(Z1/S1) + P(S2)P(Z1/S2) + P(S3)P(Z1/S3) = (.6)(.7) + (.3)(.2) + (.1)(.1) = 0.49 P(Z2) = P(S1)P(Z2/S1) + P(S2)P(Z2/S2) + P(S3)P(Z2/S3) = (.6)(.2) + (.3)(.6) + (.1)(.3) = 0.33 P(Z3) = P(S1)P(Z3/S1) + P(S2)P(Z3/S2) + P(S3)P(Z3/S3) = (.6)(.1) + (.3)(.2) + (.1)(.6) = 0.18

  42. Probability of Obtaining Each Test MKT. Result (cont’d) EV(Research) = 90.0(.40) + 70.4(.33) + 41.6(.18) = $75.26M EV(U) = 70.0M Max Price For Res. = EV(R) – EV(U) = 75.26 – 70.0 =$5.26M

  43. Case Description Newco is a manufacturer of natural soft drink beverages. It has recently experienced a decline in market share. To reverse this decline, management is considering a new promotional program that will cost $1 million. Management believes that the program may have three possible effects: 1. Very Favorable: 10% increase in market share; $4 million increase in profits. 2. Favorable: 5% increase in market share; $1 million increase in profits. 3. Unfavorable: (No Effect on Sales) – incremental loss of $1 million, the cost of the program.

  44. Abbey Normal, Director of Marketing Research, estimates the probability of the three events as follows: S1: Very Favorable Consumer Reaction = 0.30 S2: Favorable Consumer Reaction = 0.40 S3: Unfavorable Consumer Reaction = 0.30 Newco is considering a proposal made by Marketing Testing Experts (MTE), a private consulting firm, to asses the potential effects of the program.

  45. MTE has advised Newco that based on its past experience of assessing promotional programs that the following results on average have been obtained: MTE proposes a charge of $250,000 for conducting the research.

  46. Questions: • Construct the relevant payoff table. • What are the maximin and maximax solutions? • What is the solution according to the expected value criterion? • What is the value of perfect research information? • Should Newco except MTE’s proposal? Why? • What price would Newco be willing to pay for the study? • What probabilities are critical to the outcome of the study? • How could the various probabilities that are needed for such a study be obtained in practice? Note: There are many computer software packages, that can be run on a PC, mainframe and microcomputer that can be used to solve this problem. See, for example, D.A. Schellinck and R.N. Maddox, Marketing Research: A Computer Assisted Approach, The Dryden Press, 1987.

  47. PART 3

  48. SECONDARY SOURCES OF DATA FIVEFOLD (5) CLASSIFICATION

  49. INTERNAL • P&L • Balance Sheet • Sales Figure • Sales-Call Reports • Invoices • Inventory Records • Prior Research Studies

  50. PERIODICALS & BOOKS • Business Periodicals Index (Monthly Publications that provide a list of business articles appearing in a wide variety of business publications). • Standard & Poor’s Industry surveys (provides updated statistics and analyses of industries). • Moody’s Manuals (financial data and names of executives in major corporations). • Encyclopedia of Associations (provides information on every major trade and professional association in the U.S. • Marketing Journals • Trade Magazines (Advertising Age, Chain Store Age progressive Grocer, Sales and MKT. MGT, Stores). • Business Magazines (Fortune, Business Week, Forbes, Barrons, Harvard Business Review, etc.)

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