Real Research: The Market Research Podcast

AI is moving fast in market research, but faster isn't always smarter. In this episode Rashmi Sharma of Knowledge Excel, Dimitri Liakhovitski of NielsenIQ, and Ali Pierce of KS&R bring sharp thinking and practical examples to one big question: how do we use AI to go deeper into the data without letting quality quietly slip out the back door?
You'll learn how today's researchers are spotting fraud that looks surprisingly good, testing the limits of synthetic respondents, and building AI-assisted workflows for open-end coding that keep human judgment where it belongs. 
Watch the full webinar and download the speakers' slides here.

In this episode, Sawtooth CEO Bryan Orme explains three of the most widely used approaches in pricing research and, more importantly, when each one can help you make a better decision.
Bryan shares which tools lead to clearer pricing recommendations, a better read on demand, and more confidence in how buyers make choices in the real world. He also shares a reminder that strong sample quality and data cleaning may matter just as much as method choice.
It’s a thoughtful listen to sharpen judgment, strengthen pricing work, and match the research approach to the question in front of you.
Watch the full webinar and download Bryan's slides here.

This episode features Chris Chapman (Executive Director, Quant UX Association) and his take on LLM-generated “synthetic survey responses.” He lays out two paths to learn what people think: ask real people directly, or build a pipeline that generates “responses” using models, prompts, and “digital twins.”
Chris explains why he believes synthetic responses are never something you can certify in advance, why ideas like random sampling don’t map neatly to LLM outputs, and why surveys are better understood as motivated communication shaped by wording and context.
Watch the full webinar and download Chris's slides here.

This episode, originally a webinar, focuses on navigating one of the most challenging moments in research: when your findings contradict what stakeholders expect. Hosted by Justin Luster from Sawtooth Software, the episode features Story Haas, Product Research Leader at Owens Corning, who shares strategies for presenting unexpected data while maintaining stakeholder trust. Story walks through real examples where data seemed wrong. Examples include fraud rates declining when leadership expected increases, product usage that appeared impossible based on sales figures, and trends that contradicted expert assumptions. Whether you're presenting research findings or simply trying to communicate data effectively, this episode offers valuable guidance on building credibility when the numbers tell an unexpected story.

This episode, originally a webinar, focuses on 'Segment Finder,' a tool designed to identify needs-based segments in CBC (Choice-Based Conjoint) and MaxDiff data. Hosted by Brian Orme and Brian McEwen from Sawtooth Software, the episode covers the importance of market segmentation and the drawbacks of relying solely on mean values. It explains the historical and modern methods of segmentation, including the limitations of traditional rating scales and the advantages of MaxDiff and CBC analyzed through latent class multinomial logistic regression. Practical suggestions for conducting effective segmentation and cleaning data are also discussed. The episode includes a live demonstration of the Segment Finder tool in action, showcasing how it effortlessly segments respondents based on their latent preferences and aids in meaningful data analysis. 

Join Aaron Hill on the Real Research Podcast as he hosts Ben Cortese and Keaton Wilson from KS&R. Dive into their journey of leveraging Shiny, an R-based tool for delivering advanced data solutions to clients. Discover the challenges and successes they encountered in transitioning from Excel to Shiny for conjoint analysis and menu-based choice modeling. Learn about the practical applications, benefits, and future potential of integrating AI within these frameworks. Whether you are an experienced data scientist or new to market research, this episode offers valuable insights into scalable, efficient, and flexible data-driven decision-making. 

This episode features Megan Peitz, founder and CEO of Numerious, who delves into effective strategies for presenting conjoint analysis results. Megan shares her expertise on aligning stakeholder objectives, simplifying complex data, and using simulations to drive actionable insights. Through a detailed framework encompassing alignment, translation, simulation, visualization, and activation, Megan offers practical tips and real-world examples to elevate your conjoint analysis presentations. Don't miss this comprehensive guide to turning data into decisive action!
00:00 Introduction and Disclaimer
00:38 Welcome and Speaker Introduction
02:14 Understanding Conjoint Results
05:13 Framework for Presenting Conjoint Results
06:00 Pillar 1: Alignment
13:02 Pillar 2: Translation
19:23 Pillar 3: Simulation
28:09 Pillar 4: Visualization
30:30 Pillar 5: Activation
38:18 Typical Deck Outline and Conclusion
48:13 Closing Remarks

In this episode, originally recorded as a webinar, we are joined by Professor Tim Smith, founder and CEO of Wiglaf Pricing and adjunct professor of economics at DePaul University. Tim, who is the author of 'Pricing Done Right' and 'Pricing Strategy,' delves into the complexities of pricing and market research. He discusses the value-based pricing framework, different pricing strategies, and the significance of market pricing. Tim also reviews various market research methodologies such as Van Westendorp's Price Sensitivity Meter, Gabor-Granger, and Conjoint Analysis, highlighting their strengths and weaknesses. Throughout the webinar, he emphasizes the importance of having a solid hypothesis and understanding economic value to the customer for effective pricing research. Don't miss these valuable insights on how to set prices right and maximize value for shareholders. 00:00 Introduction
00:38 Meet Professor Tim Smith
01:16 Starting the Presentation
02:00 Value-Based Pricing Framework
03:07 Market Pricing and Strategy
06:54 Economic Value to Customer
16:16 Pricing Research Methodologies
27:13 Conjoint Analysis
32:41 Conclusion and Final Thoughts

In this episode we dive into making surveys more efficient with the use of Relevant Items MaxDiff. Guest speaker Chris Chapman, founder and president of the Quantitative User Experience Association, shares his extensive experience and insights. Chris discusses the motivation behind Relevant Items MaxDiff, its implementation, and how it addresses issues in data quality, respondent experience, and actionable results. Using examples from his work at Google and a live demonstration involving movie ratings, Chris illustrates how the method can improve survey accuracy and focus. Learn about different MaxDiff options, the importance of pretesting, and how Sawtooth Discover can facilitate this process. Ideal for researchers looking to enhance their survey methodologies. 00:00 Introduction
00:38 Guest Introduction: Chris Chapman
01:33 Overview of Relevant Items MaxDiff
06:41 Challenges with Standard MaxDiff
10:31 Implementing Relevant Items MaxDiff
20:16 Live Demonstration and Analysis
28:22 Discussion and Conclusion

In this insightful episode, Ray Poynter, founder of NewMR, explores using ChatGPT as a co-pilot for research data analysis. Ray covers study design, qualitative and quantitative analyses, data cleaning, driver analysis, and the use of ChatGPT for generating scripts and visualizations. Ray also highlights the benefits and limitations of ChatGPT, emphasizing its role as a starting point and second pair of eyes for research projects. Listen in to learn how AI can enhance your research and insights efforts.
00:00 Introduction and Disclaimer
00:39 Meet the Expert: Ray Poynter
01:54 Exploring ChatGPT Capabilities
03:28 Designing a B2B Market Research Study
08:55 Cleaning and Preparing Data with ChatGPT
17:32 Using ChatGPT for Quantitative Analysis
24:18 Driver Analysis for Hotel CX Tracking
31:02 Final Thoughts and Q&A