Preference Measurement: Conjoint and Related Analyses

A practical overview of preference measurement techniques, with a focus on Max-Diff and discrete choice conjoint analysis, illustrating how these methods connect consumer choice data to real business decisions. Using applied case studies across consumer packaged goods and healthcare, the lecture demonstrates how Max-Diff efficiently prioritizes large sets of options, while conjoint analysis models realistic trade-offs among bundled attributes to uncover drivers of choice, brand equity, and willingness to pay. Covers study design, data collection, modeling, simulation, and optimization.

Conjoint Analysis: Everything You Ever Wanted to Know and More

A comprehensive overview of conjoint analysis covering foundational principles, practical implementation, and methodological developments. Explains how conjoint and related choice-based methods capture consumer trade-offs to reveal drivers of decision-making, estimate attribute importance, simulate market outcomes, and quantify brand equity. Addresses advanced topics such as prohibitions, pricing design, sample size requirements, and data quality concerns.

How to Determine Sample Size in Conjoint Studies

Provides practical guidance on calculating adequate sample sizes for conjoint analysis studies. Covers the tradeoffs between statistical power, number of attributes, number of choice tasks, and budget constraints—a common challenge for market researchers designing preference measurement research.

Apple vs Samsung: The $2 Billion Case

A business school case study examining how conjoint analysis was used as expert evidence in the landmark Apple vs. Samsung patent infringement trial. Demonstrates the application of preference measurement and damage estimation techniques in intellectual property litigation—one of the highest-profile uses of conjoint analysis in legal proceedings.

When Apple, Samsung and Conjoint Came Together

A practitioner-focused companion piece to the Columbia Business School case study, explaining how conjoint analysis techniques were applied in the Apple vs. Samsung trial and what market researchers can learn about the legal applications of preference measurement.

Product Configuration: A Research Technique for the Times

Introduces product configuration as a modern alternative to traditional conjoint analysis for product development research. Explores how interactive configuration tools allow respondents to build their ideal product, generating richer preference data while improving respondent engagement.

Conjoint Analysis: Course for Unisys Corporation

Unisys Corporation’s research department needed internal clients to understand conjoint analysis before requesting it. Rajan created and delivered a custom introductory course that was recorded and turned into a permanent course for Unisys University, training product and research teams on applying conjoint methods in B2B technology.

Deriving Value from Research: The Use of Conjoint Analysis for Product Development

Demonstrates how conjoint analysis can be leveraged beyond simple preference measurement to drive actionable product development decisions, including feature prioritization, product line optimization, and competitive positioning.

Residential Peak Corps Market Study: An Application of Choice-Based Conjoint Analysis Using Hierarchical Bayes Estimation

Presents a real-world application of choice-based conjoint analysis with hierarchical Bayes estimation in the energy sector, demonstrating how advanced statistical techniques improve preference measurement for residential energy programs.

Understanding Consumer Preferences: What Works, What Doesn’t?

A critical assessment of preference measurement techniques used in practice, evaluating which methods deliver actionable insights for product development and marketing strategy and which fall short.

What’s Their Willingness to Pay: A Framework for Pricing Research

Presents a practical decision framework for choosing among pricing research methodologies—including Van Westendorp price sensitivity analysis, Gabor-Granger direct pricing, and conjoint-based approaches—to help product and marketing teams determine consumers’ willingness to pay and optimize price points for new and existing products.

The Brand Insulation Effect

Examines how strong brand equity insulates companies from reputational damage during product crises, using the Toyota recall as a case study. Demonstrates that customers with high pre-crisis brand loyalty were significantly less likely to defect, quantifying the protective value of brand equity investment.

Toyota Steers Clear of Reputational Damage

An extended academic analysis of Toyota’s brand resilience during the 2010 recall crisis. Presents empirical evidence that brand equity, built through sustained customer satisfaction investments, acts as a buffer against negative publicity and competitive encroachment.

Does Media Coverage of Toyota Recalls Reflect Reality?

Published in Harvard Business Review, this analysis challenges the media narrative surrounding the Toyota recall crisis by comparing press coverage intensity to actual customer satisfaction and loyalty data, finding a significant gap between media portrayal and consumer behavior.

Using Research to Understand Brand Value

Explores research methodologies for measuring and understanding brand value from a practitioner perspective, covering quantitative approaches to brand equity assessment and their implications for marketing strategy.

How to Measure Brand Value

A practitioner tutorial on brand equity measurement methods, covering approaches from financial brand valuation to consumer-based brand equity research, with guidance on selecting the right methodology for different business objectives.

A Survey of Analysis Methods, Part I: Key Driver Analysis

A comprehensive practitioner guide to key driver analysis methods for identifying which factors most influence customer satisfaction and loyalty. Compares regression, correlation, derived importance, and structural equation modeling approaches.

Key Driver Analysis: How to Identify Drivers of Customer Satisfaction, Loyalty & Value

A full-day pre-conference workshop teaching practitioners how to design, execute, and interpret key driver analyses for customer satisfaction programs, covering the relationship between satisfaction, loyalty, and customer lifetime value.

Key Driver Analysis: A Critical Tool for Market Research

Bose Corporation required an in-depth educational seminar for its internal research team on key driver analysis given recent developments. This presentation covered everything from traditional regression modeling to neural network-based artificial intelligence modeling techniques.

Net Promoter Score: How Valuable Is It?

A critical academic assessment of the Net Promoter Score (NPS) methodology, examining the empirical evidence for and against NPS as a predictor of business growth and comparing it to alternative satisfaction and loyalty metrics.

An Alternative Method of Reporting Customer Satisfaction Scores

Proposes an improved framework for reporting customer satisfaction results, addressing limitations of simple top-box and mean score reporting with methods that highlight areas of competitive advantage and vulnerability.

Phone Reps Can Make, Break Overall CS

Examines the outsized impact of phone representative interactions on overall customer satisfaction, demonstrating that call center touchpoints disproportionately influence customer loyalty and willingness to recommend.

Customer Satisfaction Standards for Utility Call Centers

A results workshop establishing customer satisfaction benchmarks for energy utility call centers, based on multi-company research into what drives satisfaction in regulated utility customer service environments.

Temporal Variation of Expectations, Performance and Overall Satisfaction

An empirical study examining how customer expectations, perceived performance, and satisfaction judgments change over time—providing insights into the dynamic nature of satisfaction and implications for longitudinal tracking studies.

Use of Mail and Telephone Surveys in Customer Satisfaction Measurement

Compares mail and telephone survey modes in customer satisfaction research, with practical implications for survey design and mode-effect adjustments in satisfaction tracking programs.

How to Develop and Implement Successful Patient Satisfaction Measurements

A practitioner tutorial on designing and implementing patient satisfaction measurement programs, covering questionnaire design, sampling, benchmarking, and translating satisfaction data into operational improvements in healthcare settings.

Using Information Search to Study the Consequences of the Satisfaction Judgment

Applies information search theory to understand how customer satisfaction judgments influence subsequent consumer behavior, including information seeking, consideration set formation, and brand switching decisions.

Satisfaction, Preference, Search and Choice

An academic investigation of the relationships between satisfaction, preference formation, information search behavior, and product choice—contributing to theoretical understanding of how satisfaction feeds back into consumer decision-making.

Two-Dimensional Max-Diff

Introduces Two-Dimensional Max-Diff (2DMD)™, a proprietary TRC Insights methodology that extends traditional Max-Diff to simultaneously measure importance and performance on the same scale, addressing a longstanding challenge in market research.

How to Improve Your Segmentations with Max-Diff

Demonstrates how Max-Diff (best-worst scaling) improves market segmentation by providing more discriminating input variables than traditional rating scales, producing cleaner, more actionable segments.

Cluster Analysis Gets Complicated

A practitioner’s guide to the complexities and pitfalls of cluster analysis in market segmentation studies, addressing variable selection, number-of-clusters decisions, cluster validation, and interpretation challenges.

A Survey of Analysis Methods, Part II: Segmentation Analysis

A comprehensive practitioner guide comparing clustering algorithms, latent class models, and other segmentation methods, with decision criteria for selecting the right approach.

The Case for Synthetic Data

Makes the research and business case for incorporating synthetic data into market research workflows. Co-authored with Columbia Business School professor Oded Netzer, the article examines how AI-generated synthetic respondent data can supplement traditional survey research, addressing validity, cost-efficiency, and practical applications in conjoint analysis and concept testing.

Less Like Spock, More Like Darwin

Explores how market researchers should evolve their analytical mindset in the age of AI, arguing for an adaptive, experimental approach rather than a purely logic-driven one. Examines implications of AI and machine learning for hypothesis formation, study design, and results interpretation.

Scale Conversions

Addresses converting data between different rating scale formats when combining datasets or benchmarking across studies. Provides tested conversion formulas and discusses underlying statistical assumptions.

You May Get More Than You Pay For

Examines how smart incentive design in market research can improve both response rates and data quality, yielding richer product development insights beyond their primary purpose of boosting participation.

Asymmetry Analysis

Introduces asymmetry analysis for understanding nonlinear relationships in customer data—where the impact of improving an attribute differs from the impact of letting it decline. Provides practical applications for prioritizing investments.

Can Survey Research Survive CRM?

Examines whether operational CRM data could replace survey-based research, concluding that both approaches serve complementary and essential functions in a comprehensive insights program.

Interactive Voice Response (IVR): How Is It Different from Telephone Interviewing?

An early empirical comparison of IVR automated surveys versus traditional telephone interviewing, evaluating differences in response quality, response rates, and respondent experience during the transition to automated data collection.

Getting More Out of Survey Data: The Seinfeld and Clinton Examples

Uses accessible pop culture examples to illustrate advanced analytical techniques for extracting additional insights from survey data, demonstrating how creative analytical thinking can unlock hidden patterns.

Kramer: The Spin-Off?

A creative application of market research principles to entertainment marketing, using the Seinfeld franchise to illustrate brand extension viability and consumer demand estimation concepts.

Switching Behavior in Automobile Markets: A Consideration-Sets Model

A peer-reviewed study developing a consideration-sets model of brand switching behavior in the automobile market. Examines how consumers form consideration sets and make switching decisions, contributing to competitive dynamics and customer retention theory.

Columbia Graduate School of Business

A 15-year engagement as a recurring guest lecturer in Columbia’s MBA program. Courses evolved from general practitioner perspectives (2010–2012) to specialized conjoint analysis (2018–2020) to comprehensive preference measurement (2021–2025). Also co-authored case studies with Prof. Oded Netzer.

Yale School of Management

Served as Knowledge Partner to the Yale Center for Customer Insight, helping translate academic research into practical applications. Delivered recurring guest lectures on marketing research methodology for Yale MBA students.

Wharton School of Business, University of Pennsylvania

Multiple guest lecture engagements covering practical marketing research (2009), creativity in marketing research (2011), and the practitioner’s perspective on methodology (2009–2015). The creativity lecture explored emerging opportunities from new media, mobile research, social media monitoring, text analytics, prediction markets, and gamification.

MIT Sloan School of Management

Guest lectures on practical marketing research methodology for MIT Sloan MBA students, covering the application of advanced analytical techniques in real-world market research consulting.

NYU Stern School of Business

Guest lecture on the practitioner’s perspective of marketing research, bridging academic marketing science and applied market research consulting for NYU Stern MBA students.

Ross School of Business, University of Michigan

Guest lectures on marketing research for consumer behavior, covering regression, Max-Diff, and conjoint analysis, and illustrating how these tools translate consumer feedback into actionable insights for product design. Also highlighted emerging developments in digitally driven research approaches.

Rice University – Joint TRC & Jesse H. Jones School of Business Conferences

Rice University’s Jesse H. Jones School of Business and TRC Insights jointly organized conferences for three years serving the educational needs of Houston/Texas-area business executives. Presentations covered brand value, consumer preferences, Net Promoter Score, and maximizing research value. Rice’s primary collaborator was Professor Vikas Mittal.

Configuration: A New Approach to Product Development Research

Introduces product configuration as an innovative approach to product development research at TRC’s annual industry conference.

Return on Research: Linking Research to Firm Financial Outcomes

Presents a framework for demonstrating the financial ROI of market research investments, connecting research-driven decisions to measurable business outcomes.

TRC Tutorial Seminar Series (1998–2007)

A decade-long series of practitioner tutorials covering the core methodologies of modern market research. Topics included: Conjoint Analysis: Methods and Applications (2002–2004), New Product Development: Conjoint and Related Methods (2006–2007), Segmentation: Methods and Applications (2001–2003), Successful Segmentation: Tools and Strategies (2006–2007), Key Driver Analysis: Methods and Applications (2002–2004), and Market Research at the Millennium: De-Mystifying Advanced Analysis (1998–2001).

INFORMS Marketing Science Ambassadors Network

Selected as a member of the INFORMS Marketing Science Ambassadors Network, recognizing Rajan’s contributions to bridging academic marketing science and industry practice. INFORMS Marketing Science is one of the premier academic organizations in quantitative marketing research.