Synthetic sample promises to address well-worn challenges in B2B research: high CPIs and hard-to-reach audiences. But can it be trusted? If B2B research inherently relies on specialized, non-public knowledge that's hard to access, how do you train an AI model? 

Join Greenbook and NewtonX COO, Leon Mishkis, and Principal, Strategic Insights, Jason Talwar, for a conversation exploring the foundations of synthetic data and practical use cases for marketing and insights leaders.

We’ll explore new research from NewtonX that uncovers a successful approach to synthetic B2B research: Augmented Data. You’ll also gain practical insights into how AI via synthetic sample can help improve the effectiveness and efficiency of your B2B research projects. 

What you’ll learn:

• How it works: A step-by-step breakdown from framing your business question to AI modeling and achieving verified results.
• When to use it (and when to avoid): How to determine if Synthetic Sample and Augmented Data are the right fit for your business needs.
• How to supercharge your sample: Learn how to apply augmented sampling to improve data quality, reach niche audiences, and save time and cost.