Synthetic Data: Pitfalls and Promises

Understand the technology, applications, and real-world uses of synthetic data in market research and insights

In this webinar we’ll focus on understanding “synthetic data” from a broad perspective at first, narrowing to the world of market research, particularly for synthetic data modelling and personas/”digital twins”.  We’ll look at current use cases, applications, and practical aspects of how available tools and procedures are working to deliver market research projects more effectively.  And our discussion will move beyond the conceptual to show actual real-world tests of synthetic vs. “real” data as well as agentic model operation providing guidelines and guardrails for employing this technology on your next project if you wish!

Learning outcomes:

• Industry discussions of synthetic data often mix technologies and uses which don’t exist in practice – you’ll understand how to recognize which type of synthetic data technology fits which application
• Synthetic data sceptics often make the mistake of thinking data is manufactured and not rooted in real consumer opinion – you’ll understand how the different types of synthetic data are very much developed through rigorous methodologies protecting the validity and reliability of the results
• Application and implementation of any new technology are of paramount interest – the tech may sound cool and generate buzz, but does it work? Does it actually solve for issues important to research and insights professionals? – you’ll see actual field tests and simulation models showing results, similarities, variances, where “real” data is compared to synthesized data.  This webinar is practical, not theoretical!
• However, for all its promise, some serious limitations and caveats need to be recognized for how to use synthetic data properly – you’ll see the “bad” along with the good, where synthetic data doesn’t work, why, and how to plan for those cases.

Who will benefit?  Synthetic data bridges all types of data collection – B2C, B2B, international.  If you’re responsible for data collection and its analysis for results and reporting, this topic will be of interest to you.  Synthetic data, like AI, will only grow and evolve and the understandings this course offers will give you a solid foundation for further knowledge and experience.

Learning method/delivery:  Online presentation and discussion, with real-world examples and case studies shown.  We’ll also engage in reviewing case studies and using breakouts for small-group review and discussion.

Trainer bio:  Scott's market research career includes more than 40 years as an insights practitioner, combined with part-time university-level teaching for more than 20 years, notably for UC Berkeley and Michigan State's Masters in Market research program in the U.S.  Much of his day-to-day work involves evaluating new technology and practices for data collection, testing promising methodological changes that potentially will deliver better data quality and results, especially for quantitative research projects.  Recent areas of focus for his investigations and real-world tests have been synthetic data modelling, voice and video data collection effectiveness, and multicultural trends in the U.S. affecting "representativeness".

Scott is a frequent speaker at conferences, webinars and industry association meetings.  His schedule takes him to more than a dozen locations worldwide annually, with organizations such as ESOMAR, IIEX, the Insights Association and the Market Research Society.  In addition, he has conducted subscribed webinars for ESOMAR and IIEX with record-setting attendance.