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Are you asking the right questions about synthetic data – Webinar recap

Yabble March 3, 2024

Synthetic data is a hot topic right now – and for good reason! It is one of the largest disruptions to the market research industry in history.

In our recent Q&A webinar ‘Are you asking the right questions about synthetic data?’, Kathryn Topp (Yabble Founder & CEO) and Doug Guion (Yabble Chief Growth Officer) provided valuable insights into the use of synthetic data in market research.

They highlighted the benefits and limitations of synthetic data, the importance of understanding its creation process, and the need for measures to address ethical concerns and biases. And they answered some of our most frequently asked questions when it comes to synthetic data – and outlined some key questions for you to use when vetting synthetic data providers.

Keep reading to see the summary of the session according to Yabble's Summarize tool...


Summary of ‘Are you asking the right questions about synthetic data?’ according to Yabble Summarize.


  • Synthetic data can be effectively utilized in various types of research, but understanding its limitations is crucial.
  • The creation of synthetic data involves complex AI models and algorithms, and understanding this process is important for evaluating its quality and reliability.
  • Existing data in organizations can be re-purposed and used in synthetic data models.
  • Ethical considerations, bias mitigation, and addressing recency bias are crucial in synthetic data creation.
  • Validation, accuracy, and testing are key aspects of synthetic data, and measures should be in place to validate its quality and reliability. 


  • Synthetic data has limitations and is not suitable for all types of research, which presents a challenge.
  • The dynamic nature of inputs in synthetic data models can be a challenge.
  • The industry is still grappling with understanding and accepting synthetic data, which presents a challenge. 


  • The limitations of synthetic data present an opportunity to develop more nuanced and adaptable models.
  • The challenge of understanding and accepting synthetic data in the industry presents an opportunity for more education and experience. 

To watch the full webinar visit the Yabble AI Academy and register to view our past webinars on-demand.