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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


Part 1


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)

Part 1

  • 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)

Part 1

  • 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

Marketing research and the four ps

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

Part 1

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

Elements of the marketing mix that compose a cohesive marketing program





Elements Of The Marketing Mix That Compose A Cohesive Marketing Program

Marketing Manager



Brand name









Stock level



Personal selling

Sales promotion



List price



Credit terms

Payment period

Part 2


Introduction to marketing research

Introduction to Marketing Research

Dr. Doherty

Tobin College of Business

St. John’s University

Marketing research

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

The exploratory approach

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

The exploratory approach1

The Exploratory Approach

Five Popular Exploratory Approaches:

  • Literature Search

  • Experience Survey

  • Analysis of Selected Cases

  • Focus Groups

  • “Small” Sample/Surveys/Interviews

The descriptive approach

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

True panel application

True Panel Application

The Brand Switching Matrix or Turnover Table (see your textbook!)

Applications of turnover table

Applications of Turnover Table


  • Price Changes

  • Promotional Campaigns

  • New Packaging

  • New Products

  • Results can be integrated with other databases to determine customer profiles and media habits

Causal experimental research design

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

Types of evidence that support a causal inference

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

Types of experiments

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.


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.

Types of extraneous factors that can contaminate research results

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.

Test marketing

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?

      SyracuseLeoniaDaytonDes Moines

    • Length Of Test?

      • 2 Months to 2 Years

      • Average Repurchase Period

      • Competition Concern

      • First to Market Importance

Test marketing cont d

Test Marketing Cont’d

  • What Data?

    • Warehouse Shipments

    • Store Audits

    • Consumer Panels

    • Buyer Surveys

    • Trade Attitudes

  • What Action?

  • Bayesian work table


    Computation of expected values from bayesian work table

    Computation of Expected Values From BAYESIAN Work Table


    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

    Prob of obtaining each test mkt result

    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

    Prob of obtaining each test mkt result1

    Prob. OF Obtaining Each Test MKT. Result

    FORECASTSDecision ActsOpt. EVProb.

    Z1A1 90.9 0.49

    Z2A2 70.4 0.33

    Z3A3 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

    Causal experimental research design1

    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)

    Causal experimental research design2

    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

    Causal experimental research design3

    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


    O1 = 100

    O2 – 160

    O3 = 106

    O4 = 140

    O5 = 150

    O6 = 135

    Causal experimental research design4

    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.)

    Causal experimental research design5

    Causal/ExperimentalResearch Design

    • Advanced Statistical Design (4)

      • CRD

      • RBD

      • LSD

      • Factorial

    Part 2a decision making under uncertainty

    Part 2ADecision Making Under Uncertainty

    Criteria for Selecting the Best Option





    Value of information

    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



    Regret table

    Regret Table

    Part 2b marketing research case study bayesian analysis

    Part 2B Marketing Research Case Study Bayesian Analysis

    Bayesian case

    Bayesian Case

    Objective: Determine Value of Research

    Conditional prob matrix

    Conditional Prob. Matrix

    Bayesian work table1

    Bayesian Work Table

    Computation of expected values from bayesian work table1

    Computation of Expected Values from BAYESIAN Work Table


    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

    Probability of obtaining each test mkt result

    Probability of Obtaining Each Test MKT. Result


    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

    Probability of obtaining each test mkt result cont d

    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


    Part 1

    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.

    Part 1

    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.

    Part 1

    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.

    Part 1


    • 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.

    Part 3

    PART 3

    Secondary sources of data



    Part 1


      • P&L

      • Balance Sheet

      • Sales Figure

      • Sales-Call Reports

      • Invoices

      • Inventory Records

      • Prior Research Studies

    Part 1


      • 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.)

    Part 1


      • A.C. Nielsen Co.

        • Retail Index Service (data on products and brands sold through retail outlets)

        • Scan track (Supermarket scanner data)

          Electronic Test MKT

          • Scanner Cards for Panel Members

          • Demographics

          • TV Viewers Habit of Panel Members

        • Media Research Services (Television Audience)

        • Neodata Service Inc. (Magazine Circ.)

        • Home Services – National Purchase Diary Panel

      • MRCA – National Purchase Diary Panel

        National Menu Census (data on home food consumption)

    Part 1


    • Claritas – buying habits of 250,000 U.S. neighborhoods

    • Information Resources Inc. – provide supermarket scanner data

      • (InfoScan); also

      • Promotio Scan – IMPACT of supermarket promotions


      Provides reports on warehouse withdrawals to food stores in selected market areas (SAMI reports) and supermarket scanner data (SAMSCAN)

    • SIMMONS Market Research Bureau (MRB Group)

      Provides annual reports covering television market, sporting goods, proprietary drugs.

      Giving demographic data by sex; income; age and brand preference (selective market and media reaching them)

    • Other

      Audit Bureau of Circulation Arbitron

      Audit and Surveys

      Dunn and Bradstreet

      National Family Opinion

      Standard Rate and Data Service


    Part 1


      • Statistical Abstract of MKT Sources (updated annually)

        Provides summary data on: demographic, economy, social and other aspects of the U.S. economy and society.

      • County and City Data Book (updated every three years)

        -Presented statistical information for counties, cities and other geographical units regarding:

        - population, education, employment

        - aggr. And med. Income – housing

        - bank deposit, retail sales, etc.

      • U.S. Industrial Outlook

        -Projections of industrial activity by industry and includes data on:





    Part 1

    • Marketing Information Guide

      Provides a monthly annotated bibliography of marketing information.

    • Other

      - Annual Survey of Manufacturers

      - Business Statistics

      - Census of Manufacturers

      - Census of Retail Trade, Wholesale Trade and Selected Service Industries

      - Census of Transportation

      - Federal Reserve Bulleting

      - Monthly Labor Review

      - Survey of Current Business

      - Vital Statistics Report

    Part 1


      Definition: A collection of numeric data and/or textual information that is available on computer readable form.

      e.g.: Bibliographic




      • 1990 Census Data

        Donnelly MKT


      • Nielsen Retail Product Movement


      • SPI (Strategic Planning Institute) -250 Companies


    Part 1

    Work Index:

    Sponsored by Cornell University’s School of Industrial Labor Relations and Human Resource Executive magazine, this site provides links to resources on labor relations, benefits, training, technology, staffing, recruiting, leadership, legal issues and related topics.


    Advertising World Links to resources in selected areas of marketing and advertising.

    American Association of Advertising Agencies Provides membership information, recent bulletins, and links to related resources.

    American Marketing Association Provides information on membership, publications, and conferences.

    Guerrilla Marketing Online Provides access to recent articles in marketing and links to relevant sites.

    Part 1

    Marketing Cont’d

    Institute for the Study of Business Markets (ISBM) Features current information about seminars and research projects. Includes marketing links.

    John W. Hartman Center for Sales, Advertising & Marketing History (Duke University Libraries) Center promotes study of sales, marketing, and advertising history. Features “Ad*Access,” an image database of over 7,000 advertisements printed in U.S. and Canadian newspapers between 1911 and 1955. Database allows keyword searching.

    Project 2000 Home Page Provides access to working papers, course syllabi, and related links.

    Yahoo – Business and Economy: Marketing Provides links to marketing web sites

    Marketing Information: A Bibliography

    Part 1

    Statistical Sources

    Business Resources on the Web: Economic Statistics, Government Statistics, and Business Law Maintained by Boise State University’s Albertsons Library, contains extensive links to statistics sources for the economy, population, international trade, statistics by state, etc. Primarily dedicated to statistics sources, but also contains a business law component

    Fisher College of Business Financial Data Finder Links to financial and economic data on the web and elsewhere.

    Part 3a

    PART 3A

    Dr doherty tobin college of business st john s university

    Dr. Doherty

    Tobin College of Business

    St. John’s University

    Profiling Customers



    • Dun’s Market Identifiers (DMI)

      • D&B’s market information service. A record of over 7 million establishments updated monthly

    • Enhanced DMI extends 4 digit S/C codes to 6 and 8 digits to allow clients to target specific customer groups



    • Geodemographers

      • R.L. Pole

        Product for Retailers: Vehicle Origin Survey

        Samples cars parked in retailer parking lots and identifies (from the Vehicle Registration Database) their home location. Can also match location with Census data and via their TIGER files provide a demographic profile of customers

      • Claritas

        Uses 500+ demographic variables in its Prigm (Potential Ratings for Zip markets) database to classify 250,000 neighborhoods

        40 types based on consumer behavior and lifestyle

        (shotguns, pickups, patios and pools, etc.)



    • Diary Panels

      • NPD (13,000 HHs)

        30 Product Categories

        • 29 Miniature Panels

        • Quota Sampling

        • Applications

          • Brand Shares

          • Brand Switching Behavior

          • Frequency of Purchase and Amounts

          • Evaluation of Price and Promotions

          • Changes in Channels and Distribution

          • Size of Market



    • Store Audits

      • Nielsen Retail Index

        (Drug stores, Mass media indexes and liquor stores)

      • Now Use Scanners

        Beginning Inventory and Net purchase (from wholesalers and manufactures) – Ending Inventory

        = Sales

        • Audit Includes

          • Sales

          • Purchases by retailers

          • Inventories

          • Number of Days of Supplies

          • Out-of-stock stores

          • Prices (retail and wholesale)

          • Special factory packs

          • Promotions and Advertising



    • Disaggregate data by

      • Competitors

      • Geographic area

      • Store type

    • Nielsen’s Scantrack supplements its Retail index (since 1970’s)

      • 11 digit WPC code

      • Evaluates

        • Promotions

        • Price changes

        • Channel trends

        • Product trends

      • 40,000 HHs using scanner wands



    • Behavior Scan (provided by Information Resources)

      • 3,000 HHs provided scanner cards

      • Supermarkets and Drugstores provided with scanner

      • With coorperation from Cable TV Companies It links view habits with purchase (Black Boxes)

      • Distinguishes Users from nonusers of products WRT …/promotions



    • Television

      • Nielsen TV Index

        • Audimeters attached to TV sets and tied into a central computer. Replaced by People Meters in 1988.

        • Aggregate ratings by 10 socioeconomic groups and demographic characteristics, including territory, ed. Of head of H.H., age of woman in house, etc.

    • Radio

      • Arbitron

        • Panel of HHs are randomly selected who have agreed to complete diaries. Radio marketing are rate 1-4 times age during the “Sweeps” period (April/May). Focus on age, sex, and individual (USHH) behavior

    • Print Media

      • Starch Readership Service

      • Evals. 50,000 ads in 1000 print media (mag., bus. Publications, newspapers); u=75,000 person interview

      • Recognition method: 3 degrees

        • Noted. Remembers any part of ad

        • Associated (1) plus recalls brand or advertise

        • Read Most recalls 50% or more of the written material

    Multimedia services

    Multimedia Services

    • Simmons Media/Mkt Service

      • Prob. Sample of 19,000+

      • Cross references product usage and media exposure

      • 4 different interviews with each respondent

        • Magazine, TV, Newspaper, Radio

      • Results disaggregated by sex

      • Self –administered questions covering 500 product categories

      • TV view behavior gathered by means of a personal diary; Radio via both personal and telephone interviews

      • Demographics collected

      • Application Segmentation and targeting by firms

    • Mediamark

      • Similar service, problem sample of 20,000

      • Tends to establish audience rate 10% higher than Simmons (see p 252)

    • Mail Panels

      • NFO Research

        • Quota Sample of 400,000 HHs

        • Rebuilt every two years

        • Self-adm q

      • Market Facts, Inc,

        • Quota Sample of 275,000

        • Cross Tabulation of Aug. Criterion Variable (Adv. Sales, etc) with anyone or number of demographic variables (Age, sex, automobile,…, pets ordered, etc)

    Part 3b

    PART 3B

    Determining market potential

    Determining Market Potential

    Dr. Doherty

    Tobin College of Business

    St. John’s University

    Determining market potential1

    Determining Market Potential

    • Multiple-Factor Index Method

      (“Annual Survey of Buying Power” published by Sales and Marketing Management )

      Purpose: Measure the relative consumer buying power in different region, state, and metropolitan areas.

    Determining market potential2

    Determining Market Potential

    Bi = 0.5yi + 0.3ri + 0.2pi


    Bi : % of total national buying power found in area i

    yi: % of national DI in area i

    ri: % of nat’l retail sales in area i

    pi: % of nat’l population in area i

    Example 1: drug sales

    Suppose N.Y. State has:yi = 5.0%, ri = 10.0%, pi = 8.0%

    Bi = 0.5(5.0) + 0.3 (10.0) + 0.2(8.0) = 7.1

    Thus, 7.1% of the nation’s drug sales would be expected to occur in NY. If the total drug sales are $50 Billion, sales in the NY market should be

    $50B x .071 = $3.55B

    Determining market potential3

    Determining Market Potential

    Bi = 0.5yi + 0.3ri + 0.2pi


    Bi : % of total national buying power found in area i

    yi: % of national DI in area i

    ri: % of nat’l retail sales in area i

    pi: % of nat’l population in area i

    Example 2: Actual 1992 Values for NY

    yi = 8.0%, ri = 6.7%, pi = 7.2%

    Bi = 0.5(8.0) + 0.3 (6.7) + 0.2(7.2) = 7.45

    Thus, 7.45% of the nation’s drug sales would be expected to occur in NY. If the total drug sales are $50 Billion, sales in the NY market should be

    $50B x .0745 = $3.725B

    U s population effective buying income and retail sails for selected states 1991

    U.S. Population, effective buying income, and retail sails for selected states, 1991

    Source: Adapted from “1992 Survey of Buying Power,” Part I. Sales and Marketing Management (August 24, 1992), pp. B-2, B-3, B-4.

    Part 4

    PART 4

    Measuring attitude five approaches

    Measuring Attitude: Five Approaches

    Dr. Doherty

    Measuring attitude five approaches1

    Measuring Attitude: Five Approaches

    • Self Reports

      • Most Common Procedure

    • Observation of Behavior

    • Indirect Techniques

      • Word Association

      • Sentence Completion

      • Storytelling

      • Graphics Interpretation

    • Performance of Objective Tasks

    • Physiological Reactions

      • Galvanic Skin Response Technique

      • Pupilometer

    Qualitative research techniques 1 focus group

    Qualitative Research Techniques 1. Focus Group

    Skilled moderator leads a small group (6-12) of participants in an unstructured discussion of a particular topic.

    • Advantages

      • Flexibility

      • Controllable

      • Group Interaction

      • Openness (encourages participants to be honest and direct)

      • Opportunity for quick execution

    Qualitative research techniques 1 focus group1

    Qualitative Research Techniques1. Focus Group

    Skilled moderator leads a small group (6-12) of participants in an unstructured discussion of a particular topic.

    • Disadvantages

      • Lack of scientific validity

      • Prone to bias (moderator)

      • Offers false sense of security (Results should be considered inconclusive)

      • Measurement difficulties

      • Subject to “Squeaky Wheel Syndrome”

    Qualitative research techniques 2 depth interviews

    Qualitative Research Techniques2. Depth Interviews

    Structured or Unstructured, one-on-one interview.

    • Advantages

      • Offers greater comfortability for sensitive topics

      • More detailed and revealing

      • Easier to schedule

      • Can handle more complex topics (e.g. Interviewing financial experts)

    Qualitative research techniques 2 depth interviews1

    Qualitative Research Techniques2. Depth Interviews

    Structured or Unstructured, one-on-one interview.

    • Disadvantages

      • No interaction effects

      • Expensive

      • Inconsistency among interviewers and levels of energy (Diminishing Returns)

      • Interpretational errors produce inconsistency and unreliability

      • Lack statistical validity

    Qualitative research techniques 3 projective techniques

    Qualitative Research Techniques3. Projective Techniques

    Based on the theory that people may not be aware of their innermost attitudes and/or may not wish to express certain attitudes.

    Qualitative research techniques 3 projective techniques1

    Qualitative Research Techniques3. Projective Techniques

    • Techniques

      • Word Association Ex. Detergents

    Qualitative research techniques 3 projective techniques2

    Qualitative Research Techniques3. Projective Techniques

    • Techniques

      • Picture Interpretation

        • Thematic Apperception Test (TAT)

          Respondent is shown abstract visual stimuli and describes what is going on in the pictures and what will happen

    Qualitative research techniques 3 projective techniques3

    Qualitative Research Techniques3. Projective Techniques

    • Techniques

      • Sentence Completion

        Ex. Toothpaste

        • I brush my teeth because _________.

        • I use my brand of toothpaste because _________.

        • My toothpaste tastes like _________.

        • When I brush my teeth, I _________.

    Qualitative research techniques 3 projective techniques4

    Qualitative Research Techniques3. Projective Techniques

    • Techniques

      • Third-person technique and role playing

      • Cartoons

        • Blank bubbles appear above the cartoon characters

        • Ex. New car models

    Qualitative research techniques 3 projective techniques5

    Qualitative Research Techniques3. Projective Techniques

    • Disadvantages of Projective Techniques

      • Subjectivity of scoring procedures low reliability

      • Low validity

      • Absence of substantial evidence of “Basic Assumption,” namely, that respondents project their true feelings on ambiguous stimuli

      • Small samples and unstructured formats limit generalization

    Basic measurement scale concepts

    Basic Measurement/Scale Concepts


    Assignment of numbers to characteristics of objects


    A material or physical configuration. Can be seen and/or touched


    Qualities associated with objects that give such objects identifying traits

    Measurement Scale:

    A plan that is used to assign numbers to characteristics of objects


    The “something” that is being measured

    Scales of measurement

    Scales of Measurement

    Equal appearing interval sort of the statement into categories

    Equal-Appearing Interval Sort of the Statement into Categories

    Centile formula

    Centile Formula

    Semantic differential scale

    Semantic Differential Scale

    • Origin: Research designed to investigate the underlying structure of words used to describe objects, events, processes, attitude, etc.

    • Rational: Three independent (orthogonal) dimensions can be used to describe an object using a bipolar adjective scale.

    Semantic differential scale1

    Semantic Differential Scale

    • Three Uncorrelated Dimensions

      • Potency

        • Strong - Weak

        • Shallow - Deep

        • Powerful - Powerless

      • Evaluation

        • Good – Bad

        • Sour – Sweet

        • Informative – Uninformative

        • Helpful – Unhelpful

        • Useless – Useful

      • Activity:

        • Dynamic – Static

        • Orderly – Chaotic

        • Aggressive – Non aggressive

        • Dead – Alive

        • Slow - Fast

    Semantic differential scale2

    Semantic Differential Scale

    • Marketing Application

      • Develop profiles for products, firms, markets or whatever is being measured

      • Studies often use adjective that are not anonyms or single words and use phrases to anchor scales

      • 7-Point Scale is common

    Semantic differential scale3

    Semantic Differential Scale

    • Marketing Application

      • Purification Stage (often times skipped)

      • Item Analysis. Product Moment Formula is used to compare score of each item with total score. Or,

      • T-test of significance between mean scores of “low” and “high” total scores groups on an item-by-item basis.

    Example of semantic differential scale

    Example of Semantic Differential Scale








    Likert scale

    Likert Scale

    • Allows an expression of intensity of feeling

    • Purification Stage (same as SD scale)

      • Representative Sample of Target Population

    • Final Selection of Questions

      • Same as SD Scale

    • Generally a 5-Point Scale

    • Mixes Statements as to Positive or Negative Expression

    Example of likert scale

    Example of Likert Scale

    Neither Agree nor Disagree

    Strongly Disagree

    Strongly Agree



    Stapel scale

    Stapel Scale

    • Adjectives or descriptive phrases are tested rather than bipolar adjective pairs.

    • Generally, a 10 point scale is used. Points, on scale are identified by number.

    • Results my differ according to the manner in which statement is phrased.

    Example of the stapel scale

    Example of the Stapel Scale

    Basic rating scales 3

    Basic Rating Scales (3)

    • Itemized Rating Scale:

      Most commonly used. Attitudes are measured by the choice of positions on a continuum.

    • Graphics Rating Scale:

      Attitudes are expressed along a line or graphic continuum running from one extreme to the next.

    • Comparative Rating Scale:

      Uses an explicit reference point for comparison.

      • Rank order

      • Pairwise comparison

    Examples of the rating scales itemized rating scale

    Examples of the Rating Scales:Itemized Rating Scale

    Please evaluate each of the following attributes of compact disc players according to how important the attribute is to you personally by placing an “X” in the appropriate box.

    Examples of the rating scales graphic rating scale

    Examples of the Rating Scales:Graphic Rating Scale

    Please evaluate each of the following attributes of compact disc players according to how important the attribute is to you personally by placing an “X” at the position on the horizontal line that most accurately reflects your feelings.

    Examples of the rating scales comparative rating scale

    Examples of the Rating Scales:Comparative Rating Scale

    Please divide 100 points between the following attributes of compact disc players according to the relative importance of each attribute to you.

    Q sort technique

    Q-Sort Technique

    • Similar to Thurstone approach. Respondents place questions into different piles to form a known probability distribution, e.g., normal or log normal

    • Subjects reflect their attitude toward an object

    • Focus is on individuals and not the object(s)

    • Used for cluster and segmentation applications

    Consumer decision making models attribute analysis of valence and salience properties

    Consumer Decision Making ModelsAttribute Analysis of Valence and Salience Properties

    1. Product Examples

    2. Illustration: PC

    Part 1

    3. Decision Models

    • Ideal Brand Model

    • Constrained Brand Model

    • Conjunctive Model

      Minimum attribute levels screen out competition brands to yield reduced set. Ex. PC brands equals or exceeds (7,6,7,2)

    Constrained brand model ex 6 10 10 5

    Constrained Brand ModelEx.: (6,10,10,5)

    Part 5

    PART 5

    Questionnaire anatomy

    Questionnaire: Anatomy

    Dr. Doherty

    Tobin College of Business

    St. John’s University

    Questionnaire anatomy1

    Questionnaire: Anatomy

    Definition: A formalized schedule (document) that is designed to achieve three purposes:

    • Obtain Relevant Information;

    • Direct the Questioning Process; and

    • Set the format for recording and evaluating data.

    Eight step process

    Eight Step Process

    Step 1: Define Marketing Problem

    • Write a paragraph

    • List data to be collected

    • Anticipate use of data

    • State objectives

    • Develop a Plan of Analysis

    • Client “Sign Off”

    Eight step process1

    Eight Step Process

    Step 2: Interviewing Process

    • Personal

      • Structured vs. Unstructured

      • Interviewer Administered vs. Self Administered

    • Telephone

    • Mail

    • Internet

    Eight step process2

    Eight Step Process

    Step 3: Evaluate Question Content

    Four Rules:

    • Will the Respondent understand the question?

    • Will the Respondent have the information?

    • Will the Respondent provide information?

    • Will the Analyst understand the Respondent’s response?

    Eight step process3

    Eight Step Process

    Step 4: Q/A Format

    • Open Ended

      • Free Response

      • Probing

      • Projective (e.g. association, construction, sentence completion)

    • Close Ended

      • Dichotomous

      • Multichotomous

      • Scales

      • Ranking

      • Check List

    Eight step process4

    Eight Step Process

    Step 5: Determine Wording of Question

    Three Rules:

    • Unambiguous

    • Simple and Familiar Words

    • Specific Words or Options

      Ex.) Why did you fly to Chicago on U.S. Airlines?

    Eight step process5

    Eight Step Process

    Step 6: Sequence of Questions

    • Screening (if necessary)

    • Gain Confidence and Interest

    • Groups Like Topics Together

    • Funneling

    • Demographics at End

    • Thank You!

    Eight step process6

    Eight Step Process

    Step 7: Physical Characteristics of Questionnaire (especially by mail)

    Step 8: Pretest - Revise - Formalize - Finalize

    • Personal

    • Planned Method of Administration

    Guidelines for question wording

    Guidelines for Question Wording

    • Use simple words and questions

    • Avoid ambiguous words and questions

    • Avoid leading questions

    • Avoid implicit alternatives

    • Avoid implicit assumptions

    • Avoid generalizations and estimates

    • Avoid double-barreled questions

    Communication methods

    Communication Methods









    Comparison of mail telephone and personal interview surveys

    Comparison of mail, telephone, and personal interview surveys

    Comparison of three communications media on ten factors

    Comparison of Three Communications Media on Ten Factors

    © 1987 by Prentice-Hall, Inc.

    A division of Simon & Schuster

    Englewood Cliffs, NJ 07632

    Part 6

    PART 6


    Sampling plans

    Sampling Plans

    Part 1

    Major Principles




    • From A, B, and C



    • Rewriting (1)



    • Also, from (1)


    Let =100, Z=2,andE=10

    n=(22x 1002)  102 = 400

    Let =100, Z=2,andE=5

    n=(22 x 1002)  52 = 1600


    • Solving for Sample Size


    Determinants of sample size 3

    Determinants of Sample Size (3)

    • Variance of Population

    • Error Allowance

    • Probability of Realizing Error Allowance

    Part 1


    LetP =0.2, Z=2,andE=0.02

    Suppose that P =0.3from (5)

    • From A, B, and C: Binomial




    • Similar to (3), for Binomial



    Part 1


    LetP =0.2, Z=2,andE=0.02

    Suppose that Pfound=0.3from (5)

    • From A, B, and C: Binomial




    • Similar to (3), for Binomial



    Stratified sampling

    Stratified Sampling

    1) Proportionate




    Stratified sampling1

    Stratified Sampling

    2) Disproportionate



    Stratified sampling illustration

    Stratified Sampling Illustration



    90% Confidence Level:


    1) Proportionate

    Stratified sampling illustration1

    Stratified Sampling Illustration



    90% Confidence Level:


    2) Disproportionate

    Part 7

    PART 7


    Sales performance of reps under three different sales training programs



























    Sales Performance of REPS under Three Different Sales Training Programs

    Part 1



    Accept H0

    Reject H0

    Part 1

    Step I: SST

    Step II: SSB

    Part 1

    Step III: SSE

    Note: SST = SSB + SSE

    698 = 250 + 448

    Part 1

    Step IV: Fcalc. Value

    Accept H0. No significant difference among samples at 5% level

    Chi square


    • Definition

    • Applications

    B. Goodness of Fit Test

    A. Contingency Table (r by le)

    Chi square1


    3. Illustration

    Problem: Children's Commercials:

    Does the level of Understanding (Levels I, II, and III) vary with a child's age (5-7 vs 8-10 vs. 11-12)

    Sample Test:

    Chi square2



    4. Solution

    Chi square3


    4. Solution (continued)

    Dependent samples t test

    H0: Consumers are Indifferent Between Alternatives, that is,

    Dependent Samples: t-Test

    Test Statistic:


    n = number of sample (retail outlets)

    Dependent samples t test1

    Dependent Samples: t-Test


    Dependent samples t test2

    Dependent Samples: t-Test

    Illustration (continued)

    Part 1


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