Synthetic Data, Done Right

Some audience questions never get answered. And it’s not because they don't matter - there just wasn't an easy way to ask them before. Synthetic data promises to close that gap: fast answers to niche audiences, time-sensitive questions, more markets than one study could cover.

But ask where the answer actually came from, and most tools go quiet. Many models learn from whatever's said across the open web - and the open web isn't a research sample. Almost anyone can generate a plausible-sounding response. Very few can show it's grounded in anything real. Before you trust an answer, it's worth knowing what's actually behind it.

Watch this webinar to find out what's actually worth checking before you trust one.

Virtual
October 15, 2026 12:00 PM

What is a simulated answer?

A simulated answer uses AI to model how real people might respond to something real, like an ad, a product or an idea. Think of it as putting a new question to an audience you already know. The AI generates responses for people based on what we know about people like them - their behaviours, attitudes and how they’ve answered questions before. So instead of starting from scratch, you can explore the questions that didn’t make it into the last study.

Say hello to your expert host

Jason Mander

Jason Mander

Chief Research Officer, GWI

What you’ll discover

Simulated vs. synthetic

What the difference actually is, and why it matters.

Where the data comes from

The real people and real research behind every answer.

Judging the data

Five golden rules for judging any synthetic data you see.

Why it matters for your team

What this could mean for the questions you've been putting off.

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