Webinar | The Synthetic Data Promise Gap: What Research Leaders Need to Know
Synthetic data is gaining momentum in the insights industry, despite friction and polarizing perspectives on its utility. This has created a “promise gap”: the difference between marketing claims and what is actually delivered in practice. Without a consistent, transparent evaluation framework, researchers are left to their own devices to decide how trustworthy this new technology actually is.
That is why KS&R developed the ECHO Index, a rigorous evaluation framework designed to help organizations assess the quality, reliability, and trustworthiness of synthetic data with greater transparency and consistency. The ECHO Index benchmarks synthetic data against human response, helping quantify confidence in synthetic models.
In this webinar, Ben Cortese, PhD, Senior Vice President of KS&R’s Decision Sciences & Innovation team and Jen Longo, Senior Vice President of KS&R’s Telecom, Entertainment & Recreation Practice, will take a deeper look at the ECHO Index and share what KS&R is learning through ongoing research and model evaluation. The session will explore where synthetic data shows promise, where it falls short, and why governance matters.
What You’ll Learn:
- What the ECHO Index is and why KS&R developed it.
- How the framework helps evaluate synthetic data quality and reliability.
- Application of the ECHO Index to two data sets.
- Why consistent validation practices are needed as AI-enabled research methods evolve.
- How organizations can approach synthetic data with greater rigor, transparency, and confidence.
What to Expect:
Following KS&R’s announcement of the ECHO Index, this webinar will offer a closer look at the framework, the thinking behind it, and what it reveals about the current state of synthetic data in research.
Who Should Watch?
This webinar is designed for research, insights, analytics, marketing, and innovation leaders who are evaluating synthetic data or AI-enabled research methods. It will be especially relevant for anyone responsible for research quality, model validation, governance, or decision-making confidence.
