In this episode of Signal and Noise, hosts Brian Lamar and Andrew DeCilles welcome Ellen Houston and Jordan Harper from Qualtrics Edge, marking the first time the podcast has featured guests from Qualtrics. The conversation dives into the future of AI, synthetic data, and the evolution of modern research inside one of the most influential insights platforms in the world.

Ellen, who leads the Edge Center of Excellence, outlines how her team focuses on the intersection of market research and artificial intelligence, particularly in developing synthetic respondents and next-generation research tools. Jordan, a senior principal thought leader, brings a scientific and strategic perspective shaped by his background in astrophysics, engineering, technology, and agency leadership. Together, they explain how Qualtrics Edge is working across product, engineering, delivery, and customer teams to establish a rigorous foundation for AI in research.

Throughout the episode, the conversation highlights the opportunities and challenges of AI, including research design, niche audience modeling, accuracy signals, and the role of synthetic respondents in uncovering deeper truths and exposing issues in survey construction. Both guests share examples of experiments, such as priming tests and concept evaluations, that reveal how synthetic respondents behave compared to humans and how these differences can expand the insight landscape.

Key Takeaways:

• Qualtrics Edge is focused on using AI to advance market research, especially through synthetic respondents.

• Synthetic respondents are meant to support human research, not replace it.

• The Qualtrics model is trained on decades of real survey data, giving it a unique advantage.

• Synthetic respondents help reveal issues in survey design and respondent behavior that humans may hide or overlook.

• Future developments include niche synthetic audiences and expanded AI tools across the entire research process.

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In this episode of Signal and Noise, hosts Brian Lamar and Andrew DeCilles sit down with Brandon Richard, Senior Vice President at The Link Group and a long-time AI enthusiast who has been leading multiple AI initiatives across qualitative and quantitative research. Together, they unpack what is actually happening in the research industry as companies race to understand and apply artificial intelligence.

The episode also explores the limits of AI-generated synthesis, the need for trust and human verification, the challenges of capturing nuance in qualitative work, and why the industry must avoid falling into the trap of faster and cheaper at the expense of true insight. Brandon highlights the importance of friction in the research process, explaining that many of the valuable ideas and breakthroughs come from the messy and human parts of research, not simply the final deliverable.

Key Takeaways:

• Where AI synthesis supports analysts and where it still falls short

• Practical examples of AI being used before and after qualitative work

• A balanced view of synthetic samples, digital twins, and personas

• Why accurate forecasting and real-time insight remain difficult for AI

• The risks of creating research that is fast and cheap but not meaningful

• Why friction in research often produces the best insights

• What the future of human plus AI collaboration should look like

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In this episode of Signal and Noise, hosts Brian Lamar and Andrew DeCilles talk with Lindsay Zaltman, Chief Executive Officer and Partner at Olson Zaltman, the firm known for creating the widely respected ZMET qualitative insight methodology. Together, they explore how deep psychological structures influence the way people think, feel, and make decisions, and why traditional research methods often miss these hidden drivers.

Lindsay explains how deep metaphors guide human behavior at a subconscious level and how they reveal the emotional stories people use to make sense of the world. He shares how Olson Zaltman uncovers these underlying meanings through imagery, personal narratives, and symbolic thinking. The discussion highlights how these insights help brands uncover motivations that consumers cannot easily verbalize and how they lead to more effective strategies, stronger creative ideas, and clearer paths for innovation.

Key Takeaways:

• Why traditional research struggles to reveal emotional truth

• How ZMET identifies the subconscious patterns that shape behavior

• The role of imagery and storytelling in uncovering hidden needs

• Examples of deep metaphors that changed brand strategy

• Why emotional meaning is the foundation of consumer decision making

• How deep metaphors support creative development and positioning

• The value of psychological depth in a fast-moving and automated world

• What it means to understand the stories behind customer choices

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