Consumer Research – Course Summary (Fall 2025, Tilburg University)
Course Description
The course covers core ideas of consumer research at an advanced level, focusing on transferring
a theoretical model to a study design, with emphasis on measurement, sample selection,
causality, resulting analyses & reporting. The research methods of interest are
surveys & experiments, for which these factors are crucial. By learning about measurement &
causality, we also gain insights into issues that arise when using other (big data) approaches.
Survey research is an important source of information for business, government, and
academics. Surveys provide feedback from customers and can offer crucial insights when
developed and analyzed well; issues around good survey design—such as sample size
selection & good measurement practices—are essential for all other research designs.
Experiments are an important instrument of research in Marketing, especially Consumer
Behavior, as well as in Economics and Business Administration fields like Accounting, Finance,
and Organizational Behavior, and even in real-life policy testing. Their main advantage is their role
in establishing causality, a key challenge for anyone working with data. Therefore,
understanding the principles of experimental research is an important asset for future
managers in any discipline.
Table of Contents
Topic 1: Intro CR, Conceptualization, Sources of Error ......................................................... 3
Introduction to Consumer Research ................................................................................... 3
Sources of Error & Measurement Advice.............................................................................. 7
Readings Topic 1: ............................................................................................................. 12
Topic 2: Experiments .......................................................................................................... 24
Causality & More Confounds ............................................................................................ 32
(Deep Dive Video) Internet Advertising Causality............................................................ 39
Examples of Experiments in CR......................................................................................... 41
(Assignment A) A/B Testing in Organizations................................................................... 46
(Deep Dive Video) Mediation ............................................................................................. 50
Readings Topic 2: ............................................................................................................. 54
Topic 3: Power & Problems ................................................................................................. 60
(Deep Dive Video) False Discovery Rate & Power ............................................................... 68
Readings Topic 3: ............................................................................................................. 72
Topic 4: Ethics of CR ........................................................................................................... 78
Examples & Discussion .................................................................................................... 82
Readings Topic 4 .............................................................................................................. 89
,1.2 Course learning goals
After successful completion of this course, you are able to: Check
1 Be able to formulate a problem statement & hypotheses regarding relationships
between one or more independent and dependent variables.
2 Be able to realize how measured constructs relate to the actual constructs of
interest.
3 Know different research designs & understand their advantages as well as
disadvantages, especially in relation to causal inference.
4 Be able to reason where error enters any research design, and how good design of
research tries to minimize this impact.
5 Understand how to develop experimental manipulations for the independent
variable(s).
6 Understand how to measure constructs of interest.
7 Understand how to control for potentially confounding variables.
8 Understand how sample selection, differential attrition, and other factors
influencing the final sample size affect interpretation of data.
9 Know and be able to utilize different techniques of analysis (e.g., ANOVA, more
complex interactions).
10 Be able to analyze and interpret data in surveys & experiments.
,Topic 1: Intro CR, Conceptualization, Sources of Error
Introduction to Consumer Research
By the end of the course, students will be able to:
• Explain the logic of experiments in consumer research.
• Formulate research questions & hypotheses.
• Recognize and minimize bias & error.
• Apply statistical analysis appropriately.
• Interpret results & assess validity.
• Integrate ethical principles in research design.
Consumer research is not about collecting data — it’s about understanding people
scientifically & using evidence to improve decisions.
Historical Foundations
• Daniel Starch (1920): Early advertising research – ads must be seen, read, believed,
acted upon. Door-to-door recall polling pioneered ad-effectiveness testing.
• Margaret Mead & Kurt Lewin (1940s): Wartime experiment on encouraging organ-meat
consumption. Showed that participation & dialogue enhance behavioral change.
These milestones mark the shift from descriptive observation to controlled
experimentation in marketing.
Course content: three Phases of Consumer Research
Phase 1 – Research Question
• Define problem, research question, and hypotheses.
• Understand different methodological approaches.
• Focus on independent vs. dependent variables and ethical practice.
Phase 2 – Study Design
• Manipulate independent variables and control for confounds.
• Consider moderating and mediating variables.
• Discuss causality and alternative (non-experimental) approaches.
Phase 3 – Analysis & Interpretation (includes Assignment B; reporting)
• Analyze and interpret data; evaluate reliability and validity.
• Critically assess literature and business findings.
, Six Steps of the Research Process
1. Research objectives: develop objectives, research questions & hypotheses
2. Research Design: choose the method & design
3. Sampling: Choose the population & sample
4. Data collection: develop instrument, get data
5. Data Analyis: Analyze Data
6. Reporting: write up results & share them
Data in Consumer Research
Primary Data Secondary Data
Collected for the current study Collected for another purpose
Experiments, surveys, interviews, focus Eurostat, Nielsen, Google Trends, internal
groups company data
Pros: Tailored, causal insight Pros: Accessible, low cost
Cons: Costly, time-consuming Cons: Outdated, incomplete, non-causal
2ndary data Purpose & What It Measures Use in Consumer Research Key Limitations
Tools
Track household purchases over Focuses on behavior,
Analyze buying patterns, brand loyalty,
Scanner time, linked with demographics; not motivations; limited
response to price discounts or new
Panels shows effects of price, promotion, product coverage;
products.
or distribution changes. delayed data.
Shows relative—not
absolute—search
Google Tracks relative search interest for Identify market trends, seasonality, and
volume; may not reflect
Trends terms across time and regions. brand interest spikes after campaigns.
actual purchases;
sensitive to media hype.
Social May include irrelevant
Listening Monitors online mentions, Assess brand perception, detect emerging “noise”; automated
(Talkwalker, engagement, hashtags, and issues, compare competitor buzz, or track sentiment can
Hootsuite, sentiment on social media. campaign impact. misclassify tone; privacy
Salesforce) and ethics concerns.
Risk of over-targeting or
Targeted Ads Provides metrics on ad reach,
Evaluate ad performance (A/B tests), “creepy” ads; sensitive
Data engagement, clicks, and
personalize content, measure ROI, refine data handling
(Meta,Google, conversions; identifies audience
audience targeting. (GDPR/CCPA); ad
TikTok Ads) profiles.
fatigue or bias.
Data from CRM, loyalty programs, Often siloed, lacks
Internal Segment customers, predict churn, and
and web analytics; captures external benchmarks;
Company design personalized retention or pricing
purchase behavior and customer possible missing or
Data strategies.
lifetime value. inconsistent records.
Course Description
The course covers core ideas of consumer research at an advanced level, focusing on transferring
a theoretical model to a study design, with emphasis on measurement, sample selection,
causality, resulting analyses & reporting. The research methods of interest are
surveys & experiments, for which these factors are crucial. By learning about measurement &
causality, we also gain insights into issues that arise when using other (big data) approaches.
Survey research is an important source of information for business, government, and
academics. Surveys provide feedback from customers and can offer crucial insights when
developed and analyzed well; issues around good survey design—such as sample size
selection & good measurement practices—are essential for all other research designs.
Experiments are an important instrument of research in Marketing, especially Consumer
Behavior, as well as in Economics and Business Administration fields like Accounting, Finance,
and Organizational Behavior, and even in real-life policy testing. Their main advantage is their role
in establishing causality, a key challenge for anyone working with data. Therefore,
understanding the principles of experimental research is an important asset for future
managers in any discipline.
Table of Contents
Topic 1: Intro CR, Conceptualization, Sources of Error ......................................................... 3
Introduction to Consumer Research ................................................................................... 3
Sources of Error & Measurement Advice.............................................................................. 7
Readings Topic 1: ............................................................................................................. 12
Topic 2: Experiments .......................................................................................................... 24
Causality & More Confounds ............................................................................................ 32
(Deep Dive Video) Internet Advertising Causality............................................................ 39
Examples of Experiments in CR......................................................................................... 41
(Assignment A) A/B Testing in Organizations................................................................... 46
(Deep Dive Video) Mediation ............................................................................................. 50
Readings Topic 2: ............................................................................................................. 54
Topic 3: Power & Problems ................................................................................................. 60
(Deep Dive Video) False Discovery Rate & Power ............................................................... 68
Readings Topic 3: ............................................................................................................. 72
Topic 4: Ethics of CR ........................................................................................................... 78
Examples & Discussion .................................................................................................... 82
Readings Topic 4 .............................................................................................................. 89
,1.2 Course learning goals
After successful completion of this course, you are able to: Check
1 Be able to formulate a problem statement & hypotheses regarding relationships
between one or more independent and dependent variables.
2 Be able to realize how measured constructs relate to the actual constructs of
interest.
3 Know different research designs & understand their advantages as well as
disadvantages, especially in relation to causal inference.
4 Be able to reason where error enters any research design, and how good design of
research tries to minimize this impact.
5 Understand how to develop experimental manipulations for the independent
variable(s).
6 Understand how to measure constructs of interest.
7 Understand how to control for potentially confounding variables.
8 Understand how sample selection, differential attrition, and other factors
influencing the final sample size affect interpretation of data.
9 Know and be able to utilize different techniques of analysis (e.g., ANOVA, more
complex interactions).
10 Be able to analyze and interpret data in surveys & experiments.
,Topic 1: Intro CR, Conceptualization, Sources of Error
Introduction to Consumer Research
By the end of the course, students will be able to:
• Explain the logic of experiments in consumer research.
• Formulate research questions & hypotheses.
• Recognize and minimize bias & error.
• Apply statistical analysis appropriately.
• Interpret results & assess validity.
• Integrate ethical principles in research design.
Consumer research is not about collecting data — it’s about understanding people
scientifically & using evidence to improve decisions.
Historical Foundations
• Daniel Starch (1920): Early advertising research – ads must be seen, read, believed,
acted upon. Door-to-door recall polling pioneered ad-effectiveness testing.
• Margaret Mead & Kurt Lewin (1940s): Wartime experiment on encouraging organ-meat
consumption. Showed that participation & dialogue enhance behavioral change.
These milestones mark the shift from descriptive observation to controlled
experimentation in marketing.
Course content: three Phases of Consumer Research
Phase 1 – Research Question
• Define problem, research question, and hypotheses.
• Understand different methodological approaches.
• Focus on independent vs. dependent variables and ethical practice.
Phase 2 – Study Design
• Manipulate independent variables and control for confounds.
• Consider moderating and mediating variables.
• Discuss causality and alternative (non-experimental) approaches.
Phase 3 – Analysis & Interpretation (includes Assignment B; reporting)
• Analyze and interpret data; evaluate reliability and validity.
• Critically assess literature and business findings.
, Six Steps of the Research Process
1. Research objectives: develop objectives, research questions & hypotheses
2. Research Design: choose the method & design
3. Sampling: Choose the population & sample
4. Data collection: develop instrument, get data
5. Data Analyis: Analyze Data
6. Reporting: write up results & share them
Data in Consumer Research
Primary Data Secondary Data
Collected for the current study Collected for another purpose
Experiments, surveys, interviews, focus Eurostat, Nielsen, Google Trends, internal
groups company data
Pros: Tailored, causal insight Pros: Accessible, low cost
Cons: Costly, time-consuming Cons: Outdated, incomplete, non-causal
2ndary data Purpose & What It Measures Use in Consumer Research Key Limitations
Tools
Track household purchases over Focuses on behavior,
Analyze buying patterns, brand loyalty,
Scanner time, linked with demographics; not motivations; limited
response to price discounts or new
Panels shows effects of price, promotion, product coverage;
products.
or distribution changes. delayed data.
Shows relative—not
absolute—search
Google Tracks relative search interest for Identify market trends, seasonality, and
volume; may not reflect
Trends terms across time and regions. brand interest spikes after campaigns.
actual purchases;
sensitive to media hype.
Social May include irrelevant
Listening Monitors online mentions, Assess brand perception, detect emerging “noise”; automated
(Talkwalker, engagement, hashtags, and issues, compare competitor buzz, or track sentiment can
Hootsuite, sentiment on social media. campaign impact. misclassify tone; privacy
Salesforce) and ethics concerns.
Risk of over-targeting or
Targeted Ads Provides metrics on ad reach,
Evaluate ad performance (A/B tests), “creepy” ads; sensitive
Data engagement, clicks, and
personalize content, measure ROI, refine data handling
(Meta,Google, conversions; identifies audience
audience targeting. (GDPR/CCPA); ad
TikTok Ads) profiles.
fatigue or bias.
Data from CRM, loyalty programs, Often siloed, lacks
Internal Segment customers, predict churn, and
and web analytics; captures external benchmarks;
Company design personalized retention or pricing
purchase behavior and customer possible missing or
Data strategies.
lifetime value. inconsistent records.
