PART 1. INSERT COURSE OUTLINE MARKETING CASE REPORT FORMAT A.Executive Summary: Self-Contained...

PART 1

• INSERT COURSE OUTLINE

MARKETING CASE REPORT FORMAT

A. 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)

B. Table of Contents• Subject and Page Numbers Including All Exhibit

References

I. Introduction• Background• Purpose and/or Problem Definition• Objectives of Report

II. Methodology• Specific Methodology – Why!!!• Data/Information to be Studied

III. 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)

IV. Findings and/or Conclusions

V. Appendices

VI. 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 Ps1. Products

New Products Evaluating Packaging and Brand Designs Compassion Studies With Competitor’s Products Consumer Evaluation of Current Products

2. Place (Distribution Channels) Analysis of Different Storage or Transportation Methods Analysis of Alternative Sites Determination Of Inventory Levels Growth Rates of Different Channels

3. Promotion Testing Different Ad. Messages Establishing Sales Territories Selecting Media Evaluating Ad. Effectiveness

4. Pricing

Research on MarketsForecasting DemandProviding Information of General TrendsProviding Information For Segmenting

MarketsDeveloping Customer ProfilesIdentifying New Markets For Existing ProductsIdentifying New Product NeedsForeign Markets

Elements Of The Marketing Mix That Compose A Cohesive Marketing Program

Marketing Manager

ProductFeaturesBrand namePackagingServiceWarranty

PriceList priceDiscountsAllowancesCredit termsPayment period

PromotionAdvertisingPersonal sellingSales promotionPublicity

PlaceOutletsChannelsCoverageTransportationStock level

ProductPromotion

Price Place

PART 2

Introduction to Marketing Research

Dr. Doherty

Tobin College of Business

St. John’s University

Marketing Research

Three Generic ApproachesI. ExploratoryII. DescriptiveIII. Casual/Experimental

Applications: See Tables 1 and 2

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

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 Approach

Five Popular Exploratory Approaches:

1) Literature Search

2) Experience Survey

3) Analysis of Selected Cases

4) Focus Groups

5) “Small” Sample/Surveys/Interviews

The Descriptive Approach

Purpose: Test Hypothesis• Analyze Data• Develop Findings/Conclusions

Two Types (Depending on Type of Data)A. Longitudinal (Time Series)

True Panel Omnibus Panel

B. Cross Sectional Field Survey Field Study

True Panel Application

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

Brand T1 T2A 200 250B 300 270C 350 330D 150 150

Total 1000 1000

Time Period Brand A B C D TotalA 175 25 0 0 200

(.875)B 0 225 50 25 300

(.750)C 0 0 280 70 350

(.800)D 75 20 0 55 150

(.367)Total 250 270 330 150 1000

Time (T1)

Time (T2)

Applications of Turnover Table

Evaluating:a) Price Changes

b) Promotional Campaigns

c) New Packaging

d) New Products

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

Causal/ExperimentalResearch Design

1. Scientific Criteria– Concomitant Variation– Time Sequence– Elimination of Other Causes

2. Controlled Experiment– Reflects 1.– Lab vs. Field– Validation– Two Groups: Experimental and Control

3. 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

• 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 causeY– the presumed effect

Types of Experiments

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

Experiment

Laboratory Experiment

Research investigation in which investigator creates a situation with exact conditions so as to control some, and manipulate other, 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

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 Marketing1. Who?2. Objectives

a. Forecasts: Sales, Market Share; CANNALBALISTIC EFFECTS

b. Pretest Market Mixc. Serendipity

3. Key Decisionsa. How Many Cities?

2 To 6 Importance of Regional Differences Degree of Uncertainty

b. Which Cities?Syracuse Leonia Dayton Des Moines

c. Length Of Test? 2 Months to 2 Years Average Repurchase Period Competition Concern First to Market Importance

Test Marketing Cont’dd. What Data?

Warehouse Shipments

Store Audits Consumer Panels Buyer Surveys Trade Attitudes

4. What Action?Trial Rate

Repurchase Rate

High Low

High Go! More Adv.

Low Product Flaw Bust!

BAYESIAN WORK TABLEState of Nature (Sj or Ej)

Prior Prob. P(Sj)

Cond’l Prob. P(Zk/Sj)

Joint Prob. P(ZkSj)

Posterior Prob. P(Sj/Zk)

Z1:

S1 0.6 0.7 0.42 0.858

S2 0.3 0.2 0.06 0.122

S3 0.1 0.1 0.01 0.020

0.049 1.000Z2:

S1 0.6 0.2 0.12 0.364

S2 0.3 0.6 0.18 0.545

S3 0.1 0.3 0.03 0.091

0.33 1.000Z3:

S1 0.6 0.1 0.06 0.333

S2 0.3 0.2 0.06 0.333

S3 0.1 0.6 0.06 0.333

0.18 1.000

Computation of Expected Values From BAYESIAN Work Table

GivenZ1 (Test MKT. Results show Light D)

EV(A1)= 100(.858) + 50 (.122) + -50(.02)= $90.9MEV(A2)= 50 (.858) + 100(.122) + -25(.02)= $54.6MEV(A3)= -50 (.858) + 0 (.122) + 80 (.02)= -$41.3M

Z2 (Test MKT. Results Show Moderate D)

EV(A1)= 100(.364) + 50 (.545) + -50(.091)= $59.1MEV(A2)= 50 (.364) + 100(.545) + -25(.091)= $70.4MEV(A3)= -50 (.364) + 0 (.545) + 80 (.091)= -$10.9M

Z3 (Test MKT. Results Show Heavy D)

EV(A1)= 100(.333) + 50 (.333) + -50(.333)= $33.3MEV(A2)= 50 (.333) + 100(.333) + -25(.333)= $41.6MEV(A3)= -50 (.333) + 0 (.333) + 80 (.333)= $10.0M

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


= .6(.2) + .3(.6) + .1(.3)

= 0.33


= .6(.1) + .3(.2) + .1(.6)

= 0.18

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


4. Validation– Internal vs. External

5. Internal– History– Maturation– Mortality– Regression– Instrumentation– Selection Bias– Main Testing Effect– Interactive Testing Effect

6. Four Types of Experimental Research Designs1. Pre Exp (3)2. True Exp (3)3. Quasi (3)4. Advanced Statistical Design (4)


7. Pre-Exp. Design (3)a. After Only: X O

b. Before After: O X O

c. Static Group Comparisons: X O1 O2

Major Errors: H, SB


R Exp O1 X O2

R Control O3 O4

X = (O2 – O1) – (O4 – O3)

R Exp X O1

R Control O2

X = O1 – O2

a. Before/After with Randomization (R) and Control (C)

b. After Only with R and C

8.True Experimental Design

R O1 X O2

R O3 O4

R X O5

R O6

c. Solomon 4 Group

EXT = ?ITE = ?X = ?

O1 = 100O2 – 160O3 = 106

O4 = 140O5 = 150O6 = 135

Problem


9. Quasi Exp (3)A. Single Time Series

O1 O2 O3 X O4 O5 O6

B. Multiple Time Series

O'1 O'2 O'3 X O'4 O'5 O'6

C. Separate Sample Before/After Design:R: O1 X

R: X O2

Main Problem of Quasi Approach: History(Note: 9A is typical of consumer panel investigation data.)


10. Advanced Statistical Design (4)A. CRD

B. RBD

C. LSD

D. Factorial

Part 2ADecision Making Under

Uncertainty

Criteria for Selecting the Best Option

• MAX/MIN

• MAX/MAX

• MIN/MAX-REGRET

•EXPECTED VALUE

Value of Information• Payoff (Decision) Table

EVENTS (States of Nature)Management

OptionsE1 Ez . . . En

A1 X11 X12 X1n

A2 Xz1 X22 Xzn

An Xn1 Xnz Xnn

Prior Probabilities

(P1) (Pz) (Pn)

AI : Decision ActsEj : Events (or Sj = States of Nature)Eij : Payoff or ConsequencesPj : Prob. Associated with Ej

ILLUSTRATION

E1 E2 E3 E4

A1 80M 40 -10 -50

A2 30 40 30 10

A3 20 30 40 15

A4 5 10 30 20

Regret Table

E1 E2 E3 E4 MAX

A1 0 0 50 70 70

A2 50 0 10 10 50

A3 60 10 0 5 60

A4 75 30 10 0 75

Part 2B Marketing Research Case Study

Bayesian Analysis

Bayesian CaseObjective: Determine Value of Research

Problem

S1 S2 S3

A1 100 50 -50

A2 50 100 -25

A3 -50 0 90

Prior Probs. 0.6 0.3 0.1

P(Sj)

EV(A1)=$70M

EV(A2)=$57.5M

EV(A3)=-$22M

EV(L1)=$70M

EV(C)=$98M

EV(PI)=$28M= EV(C) – EV(U)

EV(C)= .6(100) + .3(100)+ .1(80) = $98M

EV(PI)= EV(C) – EV(U) = $98M - $70M = $28M

Conditional Prob. MatrixActual Results

Test MKT Results

S1 S2 S3

Light D Z1 0.7 0.2 0.1 Should, but not

necessary to, sum to

one.

Mod. D Z2 0.2 0.6 0.3

Heavy D Z3 0.1 0.2 0.6

Must sum to one 1.00 1.00 1.00

Bayesian Work Table

0.6 0.7 0.42 0.8570.3 0.2 0.06 0.1220.1 0.1 0.01 0.020

0.49 1.000

0.6 0.2 0.12 0.3640.3 0.6 0.18 0.5450.1 0.3 0.03 0.091

0.33 1.000

0.6 0.1 0.06 0.3330.3 0.2 0.06 0.3330.1 0.6 0.06 0.333

0.18 1.000

State of Nature

(Sj or Ej)

Prior Prob. P(Sj)

Cond’l Prob. P(Zk/Sj)

Joint Prob. P(ZkSj)

Posterior Prob. P(Sj/Zk)

Z1: S1

S2

S3

Z2: S1

S2

S3

Z3: S1

S2

S3

Computation of Expected Values from BAYESIAN Work Table

Given:Z1 (Test MKT. Results show Light D)EV(A1) = 100(.858) + 50(.122) + -50(.02) = $90.9MEV(A2) = 50(.858) + 100(.122) + -25(.02) = $54.6MEV(A3) = -50(.858) + 0(.122) + 80(.02) = $-41.3M

Z2 (Test MKT. Results show Moderate D)EV(A1) = 100(.364) + 50(.545) + -50(.091) = $59.1MEV(A2) = 50(.364) + 100(.545) + -25(.091) = $70.4MEV(A3) = -50(.364) + 0(.545) + 80(.091) = $-10.9M

Z3 (Test MKT. Results show Heavy D)EV(A1) = 100(.333) + 50(.333) + -50(.333) = $33.3MEV(A2) = 50(.333) + 100(.333) + -25(.333) = $41.6MEV(A3) = -50(.333) + 0(.333) + 80(.333) = $10.0M

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



Probability of Obtaining Each Test MKT. Result

k

j 1

Probability of Obtaining Each Test MKT. Result (cont’d)

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) = 90.0(.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

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.

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.

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.

Customer Reaction

MTE Experience Very Favorable Favorable Unfavorable

Strongly Positive 0.7 0.2 0.0

Moderately Positive

0.3 0.6 0.2

Slightly Positive 0.0 0.2 0.8

Questions:

1. Construct the relevant payoff table.

2. What are the maximin and maximax solutions?

3. What is the solution according to the expected value criterion?

4. What is the value of perfect research information?

5. Should Newco except MTE’s proposal? Why?

6. What price would Newco be willing to pay for the study?

7. What probabilities are critical to the outcome of the study?

8. 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

SECONDARY SOURCES OF DATA

FIVEFOLD (5) CLASSIFICATION

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

2. 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.)

3. COMMERCIAL DATA• A.C. Nielsen Co.

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

2) Scan track (Supermarket scanner data)Electronic Test MKTa. Scanner Cards for Panel Membersb. Demographicsc. TV Viewers Habit of Panel Members

3) Media Research Services (Television Audience)4) Neodata Service Inc. (Magazine Circ.)5) Home Services – National Purchase Diary Panel

• MRCA – National Purchase Diary Panel National Menu Census (data on home food consumption)

COMMERCIAL DATA (CONTINUED)• Claritas – buying habits of 250,000 U.S. neighborhoods• Information Resources Inc. – provide supermarket scanner data

1. (InfoScan); also2. Promotio Scan – IMPACT of supermarket promotions

• SAMI/BURKEProvides 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)

• OtherAudit Bureau of Circulation ArbitronAudit and SurveysDunn and BradstreetNational Family OpinionStandard Rate and Data ServiceStard

4. GOVERNMENT PUBLICATION• 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:

production

sales

shipment

employment

• Marketing Information GuideProvides 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

5. COMPUTERIZED DATA BASEDefinition: A collection of numeric data and/or textual information that is available on computer readable form.

e.g.: BibliographicABI/INFORMPredicastNumeric

1. 1990 Census DataDonnelly MKTDRI

2. Nielsen Retail Product MovementSAMI

3. SPI (Strategic Planning Institute) -250 CompaniesPIMS

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.

MarketingAdvertising 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.

Marketing Cont’dInstitute 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

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

Profiling Customers

Dr. Doherty



Industrial

• 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

Consumer• Geodemographers

– R.L. PoleProduct 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

– ClaritasUses 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.)

Consumer

• 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

Consumer• Store Audits

– Nielsen Retail Index(Drug stores, Mass media indexes and liquor stores)

– Now Use ScannersBeginning 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

Consumer

– 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

Consumer

• 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

Consumer• 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

1. Noted. Remembers any part of ad2. Associated (1) plus recalls brand or advertise3. Read Most recalls 50% or more of the written material

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

Determining Market Potential

Dr. Doherty



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 PotentialBi = 0.5yi + 0.3ri + 0.2pi

where

Bi : % of total national buying power found in area iyi: % of national DI in area iri: % of nat’l retail sales in area ipi: % 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) = 7.1Thus, 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 PotentialBi = 0.5yi + 0.3ri + 0.2pi

where

Bi : % of total national buying power found in area iyi: % of national DI in area iri: % of nat’l retail sales in area ipi: % 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) = 7.45Thus, 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

1991 Total Population (thousands)

Percentage of U.S.

1991 Total EBI ($000)

Percentage of U.S.

1991 Total Retail Sales

Percentage of U.S.

Middle Atlantic 37,947.9 14.9621 632,218,683 16.9542 266,597,624 14.6370New Jersey 7,813.5 3.0807 155,172,906 4.1613 63,209,987 3.4704

New York 18,166.3 7.1626 298,926,889 8.0163 122,445,952 6.7227Pennsylvania 11,968.1 4.7188 178,118,888 4.7766 80,941,685 4.4439

Region State

1991 Regional State Summaries of …

Population Effective Buying Income Retail Sales

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

Measuring Attitude: Five Approaches

Dr. Doherty

Measuring Attitude: Five Approaches

1. Self Reports– Most Common Procedure

2. Observation of Behavior3. Indirect Techniques

– Word Association– Sentence Completion– Storytelling– Graphics Interpretation

4. Performance of Objective Tasks5. Physiological Reactions

– Galvanic Skin Response Technique– Pupilometer

Qualitative Research Techniques 1. Focus Group

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

A. Advantages1) Flexibility

2) Controllable

3) Group Interaction

4) Openness (encourages participants to be honest and direct)

5) Opportunity for quick execution

Qualitative Research Techniques1. Focus Group

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

B. Disadvantages1) Lack of scientific validity

2) Prone to bias (moderator)

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

4) Measurement difficulties

5) Subject to “Squeaky Wheel Syndrome”

Qualitative Research Techniques2. Depth Interviews

Structured or Unstructured, one-on-one interview.

A. Advantages1) Offers greater comfortability for sensitive

topics

2) More detailed and revealing

3) Easier to schedule

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

Qualitative Research Techniques2. Depth Interviews

Structured or Unstructured, one-on-one interview.

B. Disadvantages1) No interaction effects

2) Expensive

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

4) Interpretational errors produce inconsistency and unreliability

5) Lack statistical validity

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.


A. Techniques1) Word Association Ex. Detergents

Respondents Stimulus Words A B Washday Everyday Ironing Fresh and sweet Clean Pure Air Soiled Scrub Don’t Clean Filth This neighborhood Dirt Bubbles Bath Soap and Water Family Squabbles Children Towels Dirty Wash


A. Techniques2) 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


A. Techniques3) 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 _________.


A. Techniques4) Third-person technique and role playing

5) Cartoons• Blank bubbles appear above the cartoon

characters• Ex. New car models


B. Disadvantages of Projective Techniques1) Subjectivity of scoring procedures low

reliability

2) Low validity

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

4) Small samples and unstructured formats limit generalization

Basic Measurement/Scale Concepts

Measure:Assignment of numbers to characteristics of objects

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

Characteristics:Qualities associated with objects that give such objects identifying

traits

Measurement Scale:A plan that is used to assign numbers to characteristics of objects

Construct:The “something” that is being measured

Scales of Measurement

Scale Basic Comparisons

Typical Examples Measures of Average

Male-femaleUser-nonuserOccupationsUniform numbers

Preference for brandsSocial classHardness of mineralsGraded quality of lumber

Temperature scaleGrade point averageAttitude toward brandsAwareness of advertising

Units sold Geometric meanNumber of purchasers Harmonic meanProbability of purchaseWeight

Nominal Identity Mode

Ordinal Order Median

Interval Comparison of intervals

Mean

Ratio Comparison of absolute magnitudes

Equal-Appearing Interval Sort of the Statement into Categories

A B C D E F G H I J K Scale Q1 2 3 4 5 6 7 8 9 10 11 Value Value

f 0 8 10 30 60 60 14 12 60 0 01 p 0.00 0.04 0.05 0.15 0.30 0.30 0.07 0.06 0.03 0.00 0.00 5.4 1.7

cp 0.00 0.04 0.09 0.24 0.54 0.84 0.91 0.97 1.00 1.00 1.00f 0 0 0 0 0 6 16 28 44 66 4

2 p 0.00 0.00 0.00 0.00 0.00 0.03 0.08 0.14 0.22 0.33 0.20 9.6 1.8cp 0.00 0.00 0.00 0.00 0.00 0.03 0.11 0.25 0.47 0.80 1.00f 0 0 0 0 10 10 14 32 84 34 16

3 p 0.00 0.00 0.00 0.00 0.05 0.05 0.07 0.16 0.42 0.17 0.08 8.9 1.5cp 0.00 0.00 0.00 0.00 0.05 0.10 0.17 0.33 0.75 0.92 1.00f 0 0 8 16 36 58 48 24 10 0 0

4 p 0.00 0.00 0.04 0.08 0.18 0.29 0.24 0.12 0.05 0.00 0.00 6.2 2.0cp 0.00 0.00 0.04 0.12 0.30 0.59 0.83 0.95 1.00 1.00 1.00

Statement

Sorting Categories

Centile Formula

i

P

pcLV

w

bc

Semantic Differential Scale

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

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


3. Three Uncorrelated Dimensions1) Potency

Strong - Weak Shallow - Deep Powerful - Powerless

2) Evaluation Good – Bad Sour – Sweet Informative – Uninformative Helpful – Unhelpful Useless – Useful

3) Activity: Dynamic – Static Orderly – Chaotic Aggressive – Non aggressive Dead – Alive Slow - Fast


4. 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


5. 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

Extremely

Somewhat

QuiteNeith

er

Somewhat

QuiteExtr

emely

Not Trustworthy ____:____:____:____:____:____:____ Trustworthy

Attractive ____:____:____:____:____:____:____ Unattractive

Not Expert ____:____:____:____:____:____:____ Expert

Knowledgeable ____:____:____:____:____:____:____Not Knowledgeable

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

Strongly

Disagree

AgreeStro

ngly Agree

Neither A

gree nor Disa

gree

Disagree

1.The celebrity endorser is trustworthy.

____ ____ ____ ____ ____

2.The celebrity endorser is attractive.

____ ____ ____ ____ ____

3.The celebrity endorser is an expert on the product.

____ ____ ____ ____ ____

4.The celebrity endorser is knowledgeable about the product.

____ ____ ____ ____ ____

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

-5 -4 -3 -2 -1 +1 +2 +3 +4 +5

1.The celebrity endorser is trustworthy.

2.The celebrity endorser is attractive.

3.The celebrity endorser is an expert on the product.

4.The celebrity endorser is knowledgeable about the product.

Basic Rating Scales (3)

1. Itemized Rating Scale:Most commonly used. Attitudes are measured by the

choice of positions on a continuum.

2. Graphics Rating Scale:Attitudes are expressed along a line or graphic

continuum running from one extreme to the next.

3. Comparative Rating Scale:Uses an explicit reference point for comparison.

• Rank order• Pairwise comparison

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.

Not ImportantSomewhat Important

Fairly Important

Exremely Important

1.Quality of sound reproduction

2.Physical size of CD Unit

3. Brand name 4. Durability of unit

Examples of the Rating Scales:Graphic Rating Scale

AttributeNot Important

Extremely Important

1. Quality of sound reproduction

2. Physical size of CD Unit

3. Brand name

4. Durability of unit

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

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

Quality of sound reproduction

Physical size of CD Unit

Brand name

Durability of unit

______

______

______

______

100%

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 ModelsAttribute Analysis of Valence and Salience Properties

Product AttributesComputer Memory, Software, Price, etc.Hotel ?Mouthwash ?Lipstick ?

BrandMemory Capacity

Graphics Capacity

Software Diversity Price

A 10 8 6 4B 8 9 8 3C 6 8 10 5D 4 3 7 8

1. Product Examples

2. Illustration: PC

3. Decision ModelsA. Ideal Brand Model

B. Constrained Brand Model

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

N

iijkikjk PWA

1

N

iikijkikjk CPWD

1

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

3.8 |5-7|.1 |10-7|.2 |10-3|.3 |6-4|.4D(d)

0.6 |5-5|.1 |10-10|.2 |10-8|.3 |6-6|.4D(c)

1.7 |5-3|.1 |10-8|.2 |10-9|.3 |6-8|.4D(b)

3.1 |5-4|.1 |10-6|.2 |10-8|.3 |6-10|.4D(a)

PART 5

Questionnaire: Anatomy

Dr. Doherty



Questionnaire: Anatomy

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

1. Obtain Relevant Information;

2. Direct the Questioning Process; and

3. Set the format for recording and evaluating data.

Eight Step Process

Step 1: Define Marketing Problem1) Write a paragraph

2) List data to be collected

3) Anticipate use of data

4) State objectives

5) Develop a Plan of Analysis

6) Client “Sign Off”

Eight Step Process

Step 2: Interviewing Process1) Personal

– Structured vs. Unstructured– Interviewer Administered vs. Self Administered

2) Telephone

3) Mail

4) Internet

Eight Step Process

Step 3: Evaluate Question Content

Four Rules:1) Will the Respondent understand the

question?

2) Will the Respondent have the information?

3) Will the Respondent provide information?

4) Will the Analyst understand the Respondent’s response?

Eight Step Process

Step 4: Q/A Format1) Open Ended

a. Free Responseb. Probingc. Projective (e.g. association, construction, sentence

completion)

2) Close Endeda. Dichotomousb. Multichotomousc. Scalesd. Rankinge. Check List

Eight Step Process

Step 5: Determine Wording of Question

Three Rules:1) Unambiguous

2) Simple and Familiar Words

3) Specific Words or Options

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

Eight Step Process

Step 6: Sequence of Questions1) Screening (if necessary)

2) Gain Confidence and Interest

3) Groups Like Topics Together

4) Funneling

5) Demographics at End

6) Thank You!

Eight Step Process

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

Step 8: Pretest - Revise - Formalize - Finalize1) Personal

2) Planned Method of Administration

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 MethodsF

orm

: •Standardized questions•Standardized responsese.g. fixed alternative questions

•Non standardized questions•Nonstandardized responses. e.g. depth interviews

•Simple Administration•Simple Analysis•Suitable for facts or clear-cut opinions due to forced alternatives

•Flexible•Difficult interpretation•Interviewer influenced•Better for exploratory research

•Standardized questions•Standardized responses

•Standardized stimuli•Non standard responsese.g. projective techniques

Simple administration•Simple analysis•Difficult interpretation•Least used method

•Difficult analysis•Subjective interpretation•Suited to exploratory research

UN

DIS

GU

ISE

DC

hara

cter

istic

s:F

orm

:C

hara

cter

istic

s:

DIS

GU

ISE

D

STRUCTURED UNSTRUCTURED

Comparison of mail, telephone, and personal interview surveys

BASIS OF COMPARISON MAIL SURVEYS TELEPHONE

SURVEYS

PERSONAL INTERVIEW SURVEYS

Cost per completed survey

Usually the least expensive, assuming adequate return rate

Moderately expensive, assuming reasonable completion rate

Most expensive because of interviewer’s time and travel expenses

Ability to probe and ask complex questions

Little, since self-administered format must be short and simple

Some, since interviewer can probe and elaborate on questions

Much, since interviewers can show visuals, probe, establish rapport

Opportunity for interviewer to bias results

None, since form is completed without interviewer

Some, because of voice inflection of interviewer

Significant, because of voice and facial expressions of interviewer

Anonymity given respondent

Complete, since no signature is needed

Some, because of telephone contact

Little, because of face-to-face contact

Comparison of Three Communications Media on Ten Factors

FACTOR MAIL PERSONAL TELEPHONEBias freedom (from interviewer) 1 3 2Control over collection 3 2 1Depth of questioning 3 1 2Economy 2 3 1Follow-up ability 3 2 1Hard-to-recall data obtainable 1 2 3Rapport with respondent 3 1 2Sampling completeness 3 1 2Speed of obtaining reponses 3 2 1Versatility to use variety of methods

2 1 3

MEDIUM

© 1987 by Prentice-Hall, Inc.A division of Simon & SchusterEnglewood Cliffs, NJ 07632

PART 6

STATISTICAL ANALYSIS

Sampling PlansNon Probability Probability

•Convenience•Judgment•Snowball•Quota

•Simple Random Sampling•Systematic Random Sampling•Stratified Random Sampling

–Proportionate–Disproportionate

•Cluster Random Sampling–One Stage–Two Stage

•Area–One Stage–Two Stage

From A, B, and C

Rewriting (1)

Also, from (1)

Solving for Sample Size

x

xZ

x

xt

ˆ

xZx xZx ̂

n

EZ xE

2

22

E

Zn

or

or

where Examples:

Let =100, Z=2, and E=10

n=(22 x 1002) 102 = 400

Let =100, Z=2, and E=5

n=(22 x 1002) 52 = 1600

(1)

(2)

(3)

Major Principles

A) )(xE

B)n

x

C) CLT

Determinants of Sample Size (3)

• Variance of Population

• Error Allowance

• Probability of Realizing Error Allowance

22

E

Zn

From A, B, and C: Binomial

Similar to (3), for Binomial

2

2 )1(

E

PPZn

A) )(PE

B)N

PPP

)1(

note: )1( PPx 22 )1( PPx

xP

n

PPZP

)1(

(4)

(5)

Example:

Let P =0.2, Z=2, and E=0.02

160002.0

)8.0(2.022

2

n

Suppose that P =0.3 from (5)

0229.3.

)0115(.23.1600

)7.0(3.023.

From A, B, and C: Binomial

Similar to (3), for Binomial

2

2 )1(

E

PPZn

A) )(PE

B)N

PPP

)1(

note: )1( PPx 22 )1( PPx

xP

n

PPZP

)1(

(4)

(5)

Example:

Let P =0.2, Z=2, and E=0.02

160002.0

)8.0(2.022

2

n

Suppose that Pfound =0.3 from (5)

0229.3.

)0115(.23.1600

)7.0(3.023.

Stratified Sampling1) Proportionate

22

2

iiWE

Zn

Where:

Allocation:

Note:

N

NW i

i

nN

Nn i

i

22

222

11

2

2

... kk

N

N

N

N

N

N

E

Zn

n

W iix

2

Stratified Sampling2) Disproportionate

22

2

iiWE

Zn

Allocation:

Note:

nN

Nn k

iii

iii

1

2

22

11

2

2

...

k

k

N

N

N

N

N

N

E

Zn

n

W iix

2

Stratified Sampling IllustrationN=1250E=8.0090% Confidence Level: Z=1.64

Industry

750 20 0.60 15000 0.50500/ 1250

30 0.4015,000/ 30,000

0.50

iN i iW iiN ii

ii

N

N

1N

2N

1) Proportionate

)360240(042025.

)900(4.)400(6.64

6896.2

)30(4.)20(6.8

)64.1( 222

2

n

10)25(4.

15)25(6.

215.25

2

1

n

n

n

Stratified Sampling IllustrationN=1250E=8.0090% Confidence Level: Z=1.64

Industry

750 20 0.60 15000 0.50500/ 1250

30 0.4015,000/ 30,000

0.50

iN i iW iiN ii

ii

N

N

1N

2N

2) Disproportionate

)576(042025.

121264

6896.2

)30(4.)20(6.8

)64.1(

2

2

2

2

n

121224

12)24()30(500)20(750

)20(750

24

12

1

nnn

n

n

PART 7

STATISTICAL DISTRIBUTIONS

Sales Performance of REPS under Three Different Sales Training Programs

80

758580

375425400Total

818984

718270

738881

687679

829086

IIIIII

x

x

SUMMARY (Anova: Single Factor)Groups Count Sum Average VarianceColumn 1 5 400 80 38.5Column 2 5 425 85 35Column 3 5 375 75 38.5

ANOVASource of Variation SS df MS F P-value F crit

Between Groups 250 2 125 3.348214 0.0699094 3.88529Within Groups 448 12 37.3333

Total 698 14

3.348 3.885

Accept H0 Reject H0

348214.33333.37

125

)315/(448

)13/(250

)/(

)1/(

KNSSE

KSSBF

698

)8081(...)8079()8086(

)(

222

2

N

ij xx

Step I: SST

Step II: SSB

250

])8075()8085()8080[(5

)(

222

1

2

K

jjj xxn

448154140154

154)7581()7571()7573()7568()7582(

140)8589()8582()8588()8576()8590(

154)8084()8070()8081()8079()8086(

)(

22222

22222

22222

2

N

jij xx

Step III: SSE

Note: SST = SSB + SSE

698 = 250 + 448

Step IV: Fcalc. Value

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

88.3 of Value Table

35.33.37

125

124482

2501

05122

j .i F

N-KSSEK-SSB

Chi-Square1. Definition

2. Applications

ler

ji ij

ijij

E

EO,

1,1

22 )(

rrkr2r1

22k2221

11k1211

P...PP

P...PP

P...PP

:H 0

rr

22

11

E0

E0

E0

:H 0

A. Contingency Table (r by le) B. Goodness of Fit Test

Chi-Square3. IllustrationProblem: 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)

33k3231

2232221

1131211

PPP

PPP

PPP

:H 0

Sample Test: Level of AGEUnderstanding 5-7 8-10 11-12 Total

I 55 37 15 107II 35 50 60 145III 10 13 25 48

TOTAL 100 100 100 300

Chi-Square4. Solution

160300/48PPP

483300/145PPP

357300/107PPP

3k3231

232221

131211

:0H

Level of AGEUnderstanding 5-7 8-10 11-12 Total

I 55 37 15 107(35.7) (35.7) (35.7)

II 35 50 60 145(48.3) (48.3) (48.3)

III 10 13 25 48(16) (16) (16)

TOTAL 100 100 100 300

1,000

Chi-Square

4. Solution (continued)

488.9

9.3616

)1625(...

7.35

)7.3537(

7.35

)7.3555(

24,05.

2

222

calc

022 reject , Since Hcriticalcalc

Dependent Samples: t-Test

nd

d

ˆ

H0: Consumers are Indifferent Between Alternatives, that is, 0D

d

Ddt

Test Statistic:

n

dd

1

)(ˆ

2

n

ddd

where:

n = number of sample (retail outlets)

Store TUMS I TUMS II d

1 130 111 19 1692 82 76 6 03 64 58 6 04 111 103 8 45 50 48 2 166 56 61 -5 121

TOTAL 493 457 36 310

2)( dd

Dependent Samples: t-Test

Illustration:

Dependent Samples: t-TestIllustration (continued)

66

36

n

dd

87.75

310

1

)(ˆ

2

n

ddd

21.345.2

87.7ˆ

nd

d

0:0 DH

015.205.: 5.0,1 nt

87.121.3

6ˆ

d

Ddt

0Htt criticalcalc reject cannot , Since

PART 1. INSERT COURSE OUTLINE MARKETING CASE REPORT FORMAT A.Executive Summary: Self-Contained...

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