An immense library of market intelligence
As the world's most curious company, we've built a vast and constantly expanding body of knowledge about consumer behaviour, global markets and the research process.
We conduct many ongoing in-house research initiatives of broad interest to marketers.
These have a variety of objectives, including:
- Identifying emerging cultural trends
- Understanding changing consumer attitudes
- Adding to our quantitative knowledge of various market sectors
- Determining how research can be practically applied to initiate change
To help you find specific articles of interest, we've grouped them into common topics. A table of contents is also available.
Please send us your questions, comments and suggestions for new topics.
Alphabetical index
ABCDEFGHIJKLMNOPQRSTUVWXYZA
Analysis of Variance
14.
Analysis of Variance: One-factor Designs.
18.
Analysis of Ratios of Means.
24.
Interpretation of T-test Results.
Attributable Effect
50.
Statistical Analyses of Extreme Proportions.
57.
Estimation of the Effect of Attributes on Overall Liking.
B
Bayesian Inference
55.
Use of a Bayesian Orientation in Product Testing.
Bias
- Influence Of Brand Name In Product Test
16.
Using Letters to Identify Products or Brands.
- Product Order Presentation
16.
Using Letters to Identify Products or Brands.
- Question Order Presentation
1.
An Examination of Order Bias (On self-administered questionnaires).
9.
Pricing Research: Single vs. Multiple Presentations.
15.
Do You Want Overall Opinions or Diagnostic Information.
61.
Effects of Various Rating Scale Descriptors and Administration on Response Profiles With
Telephone Interview Data
.
- Respondent Fatigue
12.
Measuring Buying Intention: Product List vs. Single Product Questionnaire.
- Response Bias
4.
Number-type Data: Structured vs. Open-ends.
61.
Effects of Various Rating Scale Descriptors and Administration on Response Profiles With
Telephone Interview Data
.
- Sampling
36.
The Logic of Statistical Significance Tests.
Binary Data
- Compared to rating scales
53.
The Effect of the Number of Scale Points in Measuring Product Perceptions.
- Measures of Relationship
40.
Measures of Relationship for Binary Data.
Binomial Distribution
11.
Market Share Estimates and Their Standard Errors from Store Tests.
32.
Estimating Sample Sizes for Mailouts.
50.
Statistical Analyses of Extreme Proportions.
Bonferroni Inequality
20.
Examining Group Differences: Components of T-Plots.
30.
Testing Differences Among Several Means.
38.
Correctly Selecting the Best Product.
Bootstrapping
31.
Bootstrapping.
38.
Correctly Selecting the Best Product.
48.
An Alternative to the Mean.
Box and Whisker Plots
17.
Graphic Displays of Data: Box and Whisker Plots.
Brand Share, Estimation of
11.
Market Share Estimates and Their Standard Errors from Store Tests.
31.
Bootstrapping.
C
Cash Incentive
- Mail Survey Response
39.
Using a Cash Incentive to Heighten Mail Survey Response.
Carry-over Effect
13.
Repeat Measures Design and Analysis.
Censored Scales
4.
Number-type Data: Structured vs. Open-ends.
52.
Censored Scales.
Central Tendency
17.
Graphic Displays of Data: Box and Whisker Plots.
48.
An Alternative to the Mean.
Central Location Testing
51.
Factors Involved in Conducting Product Tests via Central Location Facilities.
Choice, Analysis of
26.
Analysis of Forced-Choice Data.
Cluster Analysis
25.
Function Plots of Multi-Dimensional Data.
29.
Displaying Group Differences Using Biplots.
35.
An Analysis of Multiple Brand Usage.
60.
An Analysis of Importance Ratings.
Clustering Concepts
42.
Clustering Concepts.
Component of t-Plot
20.
Examining Group Differences: Components of T-Plots.
Concept Testing
46.
Color Testing: Color vs. Black and White Product Photographs.
Concern Scales vs. Importance Ratings
44.
The Use of Concern Scales as an Alternative to Importance Ratings.
Conditional Probability
35.
An Analysis of Multiple Brand Usage.
57.
Estimation of the Effect of Attributes on Overall Liking.
Confidence Interval
11.
Market Share Estimates and Their Standard Errors from Store Tests.
18.
Analysis of Ratios of Means.
20.
Examining Group Differences: Components of T-Plots.
30.
Testing Differences Among Several Means.
31.
Bootstrapping.
34.
Confidence and Tolerance Intervals.
36.
The Logic of Statistical Significance Tests.
Confidence Level (See Type I error, significance level)
27.
Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels.
30.
Testing Differences Among Several Means.
36.
The Logic of Statistical Significance Tests.
37.
Sample Sizes for Analyses of Means and Proportions.
43.
Balancing Confidence and Power for Decision Making.
Conjoint Analysis
19.
Response Measures, Data Collection Methods, and Conjoint Analysis: A Two-attribute Case Study.
58.
Conjoint Analysis for Product Strategy Decisions.
Context Effects
6.
Brand Perceptions: Relative vs. Absolute Ratings.
9.
Pricing Research: Single vs. Multiple Presentations.
13.
Repeat Measures Design and Analysis.
41.
Some Methodological Issues in Product Testing.
Correct Selection Methodology
38.
Correctly Selecting the Best Product.
Correlation Point-Biserial
24.
Interpretation of T-test Results.
D
Data Collection Methods
1.
An Examination of Order Bias (On self-administered questionnaires).
8.
Using Multiple Question Grids.
51.
Factors Involved in Conducting Product Tests via Central Location Facilities.
61.
Effects of Various Rating Scale Descriptors and Administration on Response Profiles With
Telephone Interview Data
.
Designs
- Partially Balanced Incomplete Block
41.
Some Methodological Issues in Product Testing.
49.
Statistical Designs for Ordering and Rotating Products in Product Tests.
- Balanced Incomplete Block Design
49.
Statistical Designs for Ordering and Rotating Products in Product Tests.
- Incomplete Block
13.
Repeat Measures Design and Analysis.
29.
Displaying Group Differences Using Biplots.
41.
Some Methodological Issues in Product Testing.
- Monadic, Randomized Block, & Repeated Measures
13.
Repeat Measures Design and Analysis.
Diagnostic Information
15.
Do You Want Overall Opinions or Diagnostic Information.
Discriminant Analysis
25.
Function Plots of Multi-Dimensional Data.
29.
Displaying Group Differences Using Biplots.
Discrimination
- Tests, Design of & Measurement of
33.
Simultaneous Measurement of Discrimination and Preference.
Discriminator/Non-Discriminator Model, Double Pair Procedure, & Dual Train Procedure
33.
Simultaneous Measurement of Discrimination and Preference.
E
Effect Size
36.
The Logic of Statistical Significance Tests.
F
Forced-Choice Data
26.
Analysis of Forced-Choice Data.
38.
Correctly Selecting the Best Product.
Frequency
- Distribution
17.
Graphic Displays of Data: Box and Whisker Plots.
- Frequency Of Use
7.
Frequency Measurement: Past vs. Average Period.
Function Plot
25.
Function Plots of Multi-Dimensional Data.
G
Graphic Display of Data
17.
Graphic Displays of Data: Box and Whisker Plots.
20.
Examining Group Differences: Components of T-Plots.
25.
Function Plots of Multi-Dimensional Data.
29.
Displaying Group Differences Using Biplots.
53.
The Effect of the Number of Scale Points in Measuring Product Perceptions.
56.
Triangle Plots: Graphic Display of "Just Right" Scale Data.
H
Hypothesis Testing
36.
The Logic of Statistical Significance Tests.
54.
Test of Differences Between Correlated Proportions.
I
Importance, Measurement of
28.
Measuring the "Importance" of Attributes.
Importance Scales
44.
The Use of Concern Scales as an Alternative to Importance Ratings.
Internet
63.
An Examination of Online Sampling Techniques.
62.
Online Consumers: Beyond Fiction to Fact Distilling Reality from the Hype.
Interquartiel Range
17.
Graphic Displays of Data: Box and Whisker Plots.
Importance, analysis of
60.
An Analysis of Importance Ratings.
J
Jackknifing
11.
Market Share Estimates and Their Standard Errors from Store Tests.
31.
Bootstrapping.
"Just Right" Scales
56.
Triangle Plots: Graphic Display of "Just Right" Scale Data.
L
Letter Bias In Product Labeling
16.
Using Letters to Identify Products or Brands.
Listed Vs. Unlisted Telephone Numbers
10.
Dialing Selection Techniques: Random Digit vs. Directory.
M
Mail Panels
59.
Mail Panels vs. General Samples: How similar and how different.
Market Audits
11.
Market Share Estimates and Their Standard Errors from Store Tests.
21.
How to Improve Test Marketing.
22.
An Examination of Weekend Audits.
Means, For Censored Scales
4.
Number-type Data: Structured vs. Open-ends.
14.
Analysis of Variance: One-factor Designs.
17.
Graphic Displays of Data: Box and Whisker Plots.
18.
Analysis of Ratios of Means.
20.
Examining Group Differences: Components of T-Plots.
25.
Function Plots of Multi-Dimensional Data.
30.
Testing Differences Among Several Means.
37.
Sample Sizes for Analyses of Means and Proportions.
24.
Interpretation of T-test Results.
48.
An Alternative to the Mean.
Means, For Censored Scales
52.
Censored Scales.
Medians
4.
Number-type Data: Structured vs. Open-ends.
17.
Graphic Displays of Data: Box and Whisker Plots.
48.
An Alternative to the Mean.
Minimax Criterion
27.
Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels.
Multinomial Distribution
26.
Analysis of Forced-Choice Data.
Multiple Comparison Procedure
14.
Analysis of Variance: One-factor Designs.
20.
Examining Group Differences: Components of T-Plots.
26.
Analysis of Forced-Choice Data.
30.
Testing Differences Among Several Means.
36.
The Logic of Statistical Significance Tests.
Multiple Product Questionnaire
12.
Measuring Buying Intention: Product List vs. Single Product Questionnaire.
Multiple Question Answer Grid
8.
Using Multiple Question Grids.
Multiplicity
30.
Testing Differences Among Several Means.
Multivariate Analysis
20.
Examining Group Differences: Components of T-Plots.
25.
Function Plots of Multi-Dimensional Data.
29.
Displaying Group Differences Using Biplots.
N
No Answer, Analysis of Non-Response
12.
Measuring Buying Intention: Product List vs. Single Product Questionnaire.
- In Survey Data
8.
Using Multiple Question Grids.
23.
Measuring Buying Intention: How Valid is the Estimate?.
- To Rating Tasks
28.
Measuring the "Importance" of Attributes.
Null Hypothesis
36.
The Logic of Statistical Significance Tests.
O
Odds
40.
Measures of Relationship for Binary Data.
55.
Use of a Bayesian Orientation in Product Testing.
Order Rotation
1.
An Examination of Order Bias (On self-administered questionnaires).
61.
Effects of Various Rating Scale Descriptors and Administration on Response Profiles With
Telephone Interview Data
.
Outliers
17.
Graphic Displays of Data: Box and Whisker Plots.
P
Paired Comparison Procedure
- Attribute Evaluation
28.
Measuring the "Importance" of Attributes.
- Product Evaluation
19.
Response Measures, Data Collection Methods, and Conjoint Analysis: A Two-attribute Case Study.
26.
Analysis of Forced-Choice Data.
33.
Simultaneous Measurement of Discrimination and Preference.
38.
Correctly Selecting the Best Product.
Pattern Analysis
35.
An Analysis of Multiple Brand Usage.
Penalty Analysis
56.
Triangle Plots: Graphic Display of "Just Right" Scale Data.
Percentiles
17.
Graphic Displays of Data: Box and Whisker Plots.
Perceptual Maps
27.
Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels.
29.
Displaying Group Differences Using Biplots.
53.
The Effect of the Number of Scale Points in Measuring Product Perceptions.
Power (See Type II Error)
14.
Analysis of Variance: One-factor Designs.
27.
Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels.
36.
The Logic of Statistical Significance Tests.
37.
Sample Sizes for Analyses of Means and Proportions.
38.
Correctly Selecting the Best Product.
43.
Balancing Confidence and Power for Decision Making.
Preference
- Tests, Design Of
33.
Simultaneous Measurement of Discrimination and Preference.
41.
Some Methodological Issues in Product Testing.
- Influence By Attributes
15.
Do You Want Overall Opinions or Diagnostic Information.
- Measurement Of
35.
An Analysis of Multiple Brand Usage.
41.
Some Methodological Issues in Product Testing.
Price Perceptions
9.
Pricing Research: Single vs. Multiple Presentations.
Prior Information (see Bayesian inference)
55.
Use of a Bayesian Orientation in Product Testing.
Probability of Correct Selection
38.
Correctly Selecting the Best Product.
Probabilty Plot
17.
Graphic Displays of Data: Box and Whisker Plots.
Product Labels, Use of Letters
16.
Using Letters to Identify Products or Brands.
Product Tests, Analysis Of
55.
Use of a Bayesian Orientation in Product Testing.
Product Tests, Design Structure
16.
Using Letters to Identify Products or Brands.
33.
Simultaneous Measurement of Discrimination and Preference.
41.
Some Methodological Issues in Product Testing.
49.
Statistical Designs for Ordering and Rotating Products in Product Tests.
51.
Factors Involved in Conducting Product Tests via Central Location Facilities.
- Treatment Structure & Monadic For Ordering and Rotating Products
41.
Some Methodological Issues in Product Testing.
- Balanced Incomplete Block, Partially Balanced Incomplete Block, Factorial Design, Fractional Factorial Design, Latin Squares, Youden Squares, & Cross Over Design
41.
Some Methodological Issues in Product Testing.
49.
Statistical Designs for Ordering and Rotating Products in Product Tests.
Product Tests, Measurement of
- Absolute Measurement
- Relative or Comparative Measurement
- Direct vs. Indirect Measurement
43.
Balancing Confidence and Power for Decision Making.
Product Tests, Methods
51.
Factors Involved in Conducting Product Tests via Central Location Facilities.
Proportions, Analysis of
26.
Analysis of Forced-Choice Data.
37.
Sample Sizes for Analyses of Means and Proportions.
50.
Statistical Analyses of Extreme Proportions.
53.
The Effect of the Number of Scale Points in Measuring Product Perceptions.
54.
Test of Differences Between Correlated Proportions.
Purchase Incidence, Measurement of
5.
Measuring Purchase Incidence Rates.
Purchase Intent
- Influenced By Multiple Product List
12.
Measuring Buying Intention: Product List vs. Single Product Questionnaire.
- Influenced By Price Presentation
9.
Pricing Research: Single vs. Multiple Presentations.
- Measurement Of
9.
Pricing Research: Single vs. Multiple Presentations.
12.
Measuring Buying Intention: Product List vs. Single Product Questionnaire.
23.
Measuring Buying Intention: How Valid is the Estimate?.
- Purchase Cycle
52.
Censored Scales.
- Validation Of Measures
23.
Measuring Buying Intention: How Valid is the Estimate?.
Q
Questionnaire Design
1.
An Examination of Order Bias (On self-administered questionnaires).
4.
Number-type Data: Structured vs. Open-ends.
5.
Measuring Purchase Incidence Rates.
7.
Frequency Measurement: Past vs. Average Period.
8.
Using Multiple Question Grids.
9.
Pricing Research: Single vs. Multiple Presentations.
15.
Do You Want Overall Opinions or Diagnostic Information.
53.
The Effect of the Number of Scale Points in Measuring Product Perceptions.
61.
Effects of Various Rating Scale Descriptors and Administration on Response Profiles With
Telephone Interview Data
.
R
Rank Order Data
19.
Response Measures, Data Collection Methods, and Conjoint Analysis: A Two-attribute Case Study.
44.
The Use of Concern Scales as an Alternative to Importance Ratings.
Rating Scales
- Analysis Of
2.
Measuring Purchase Intent.
- Censored
52.
Censored Scales.
- Comparison Of
2.
Measuring Purchase Intent.
3.
Variations in Semantic Differential Scales.
28.
Measuring the "Importance" of Attributes.
53.
The Effect of the Number of Scale Points in Measuring Product Perceptions.
61.
Effects of Various Rating Scale Descriptors and Administration on Response Profiles With
Telephone Interview Data
.
- Concern Scales
44.
The Use of Concern Scales as an Alternative to Importance Ratings.
- Effect Of Context On
6.
Brand Perceptions: Relative vs. Absolute Ratings.
- Importance Scales
44.
The Use of Concern Scales as an Alternative to Importance Ratings.
- "Just Right"
56.
Triangle Plots: Graphic Display of "Just Right" Scale Data.
- Labeling Of Scale Points
28.
Measuring the "Importance" of Attributes.
- Semantics Of
2.
Measuring Purchase Intent.
3.
Variations in Semantic Differential Scales.
61.
Effects of Various Rating Scale Descriptors and Administration on Response Profiles With
Telephone Interview Data
.
- Structure Of
2.
Measuring Purchase Intent.
3.
Variations in Semantic Differential Scales.
4.
Number-type Data: Structured vs. Open-ends.
28.
Measuring the "Importance" of Attributes.
- Transformation Of
2.
Measuring Purchase Intent.
- Variability Of Responses
37.
Sample Sizes for Analyses of Means and Proportions.
Ratio Data
- Analysis Of
18.
Analysis of Ratios of Means.
- Measurement Of
4.
Number-type Data: Structured vs. Open-ends.
Recall Respondent
7.
Frequency Measurement: Past vs. Average Period.
Repeat Pair Procedure
33.
Simultaneous Measurement of Discrimination and Preference.
Relative Effect
57.
Estimation of the Effect of Attributes on Overall Liking.
Response Patterns
3.
Variations in Semantic Differential Scales.
S
Sample Size Estimation
14.
Analysis of Variance: One-factor Designs.
32.
Estimating Sample Sizes for Mailouts.
36.
The Logic of Statistical Significance Tests.
37.
Sample Sizes for Analyses of Means and Proportions.
38.
Correctly Selecting the Best Product.
45.
Sample Size Tables For Significance Tests.
- Effective Sample Size
- Finite Population Correction Factor (FPC)
47.
The Effect of Population Size on Precision and Sample Size.
Sample Size Tables
45.
Sample Size Tables For Significance Tests.
Sampling Error
37.
Sample Sizes for Analyses of Means and Proportions.
Sampling With Replacement (Resampling)
31.
Bootstrapping.
Sampling
- Internet
63.
An Examination of Online Sampling Techniques.
- Quota & Stratification
35.
An Analysis of Multiple Brand Usage.
- Mail Panels vs. General Samples
59.
Mail Panels vs. General Samples: How similar and how different.
Segmentation
35.
An Analysis of Multiple Brand Usage.
64.
Is this Art of Science?.
Significance Level (See Type I Error, Confidence Level)
30.
Testing Differences Among Several Means.
36.
The Logic of Statistical Significance Tests.
37.
Sample Sizes for Analyses of Means and Proportions.
Similarity Coefficients
35.
An Analysis of Multiple Brand Usage.
Skewness
17.
Graphic Displays of Data: Box and Whisker Plots.
Standard Error
37.
Sample Sizes for Analyses of Means and Proportions.
Statistical Decision Rules
27.
Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels.
Statistical Significance Tests
11.
Market Share Estimates and Their Standard Errors from Store Tests.
13.
Repeat Measures Design and Analysis.
14.
Analysis of Variance: One-factor Designs.
18.
Analysis of Ratios of Means.
20.
Examining Group Differences: Components of T-Plots.
24.
Interpretation of T-test Results.
26.
Analysis of Forced-Choice Data.
27.
Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels.
32.
Estimating Sample Sizes for Mailouts.
34.
Confidence and Tolerance Intervals.
36.
The Logic of Statistical Significance Tests.
37.
Sample Sizes for Analyses of Means and Proportions.
38.
Correctly Selecting the Best Product.
54.
Test of Differences Between Correlated Proportions.
Structured Vs. Unstructured Questions
4.
Number-type Data: Structured vs. Open-ends.
7.
Frequency Measurement: Past vs. Average Period.
Subjective Prior Probabilities
27.
Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels.
T
Taste Test
51.
Factors Involved in Conducting Product Tests via Central Location Facilities.
T-Test
18.
Analysis of Ratios of Means.
20.
Examining Group Differences: Components of T-Plots.
24.
Interpretation of T-test Results.
Telephone Sampling
- Raised Integer Dialing, Random Digit Dialing (RDD), & Systematic Digit Dialing
10.
Dialing Selection Techniques: Random Digit vs. Directory.
Test Marketing
21.
How to Improve Test Marketing.
22.
An Examination of Weekend Audits.
Tolerance Interval
34.
Confidence and Tolerance Intervals.
Triad Procedure & Triangle Discrimination Procedure
33.
Simultaneous Measurement of Discrimination and Preference.
Triangle Plots
56.
Triangle Plots: Graphic Display of "Just Right" Scale Data.
TYPE I ERROR (See Significance Level, Confidence Level)
27.
Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels.
30.
Testing Differences Among Several Means.
36.
The Logic of Statistical Significance Tests.
37.
Sample Sizes for Analyses of Means and Proportions.
38.
Correctly Selecting the Best Product.
43.
Balancing Confidence and Power for Decision Making.
55.
Use of a Bayesian Orientation in Product Testing.
Type II Error(See Power)
27.
Minimizing Losses (or Maximizing Gains) and Choosing Confidence Levels.
36.
The Logic of Statistical Significance Tests.
37.
Sample Sizes for Analyses of Means and Proportions.
38.
Correctly Selecting the Best Product.
43.
Balancing Confidence and Power for Decision Making.
55.
Use of a Bayesian Orientation in Product Testing.
U
Unit of Analysis
11.
Market Share Estimates and Their Standard Errors from Store Tests.
V
Variablility
17.
Graphic Displays of Data: Box and Whisker Plots.
Variance, Estimation of
37.
Sample Sizes for Analyses of Means and Proportions.
Variance, With Censored Scales
52.
Censored Scales.
Versioning, Effect on Ratings
6.
Brand Perceptions: Relative vs. Absolute Ratings.
W
Weekend Audits
22.
An Examination of Weekend Audits.