How to Validate and Operationalize Synthetic Data in B2B Research

Many organizations are experimenting with AI-driven research, yet only a small percentage have successfully operationalized it.

Join Greenbook and NewtonX for a session that will guide you through overcoming the trust gap in adopting synthetic data, ensuring it integrates smoothly into your research workflows without disrupting established methods. Discover real-world examples where leading organizations use synthetic data to improve research viability, accelerate the generation of insights, and lower costs.

You’ll learn to confidently introduce and operationalize synthetic data without compromising research quality, stakeholder trust, or decision-making integrity. By the end of the event, you’ll walk away with a clear, actionable roadmap to implement synthetic data in a validated, low-risk, and cost-effective way—making AI-driven methodologies a trusted part of your research strategy.

Key Insights:

• Gain internal buy-in: Use risk-free pilots and validation frameworks to convert skeptical stakeholders into advocates. 
• Ensure research integrity: Apply best practices for validation, bias detection, and quality control to prove synthetic data reliability. 
• Accelerate insights with confidence: Reduce fielding time without compromising statistical accuracy. 
• Maximize Research Budgets: Use synthetic sample augmentation to improve feasibility while cutting costs. 
• Integrate AI into research workflows: Learn how to blend synthetic data with traditional methodologies to drive better, faster insights.