What Qualtrics Just Revealed About the Future of Research | Signal & Noise Ep 17

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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