Synthetic data used in market research

Move from research projects to insight assets

Synthetic data, when combined with research communities, enables a different model. Instead of one-off projects, you begin to build a continuous layer of insight that evolves over time. This is where grounded synthetic insights become valuable: they are built from the research context, audience data, and behavioral patterns your team already understands.

Every interaction contributes

Every survey, every response, and every interaction contributes to a growing dataset that can be reused, explored, and extended.

A living source of knowledge

Your community becomes a living source of knowledge, and synthetic data allows you to activate that knowledge on demand.

Insight that evolves over time

Build a continuous layer of insight that evolves over time and grows more valuable with every study you run.

How synthetic data works in real research workflows

Select your data

Choose the respondents and datasets from your existing communities that you want to model.

Define your objective

Set your research goal and generate questions, just as you would in a qualitative study.

Simulate interviews

The platform simulates interviews with matched profiles, producing responses that reflect your audience.

Get your report

Responses are synthesized into a report with themes, patterns, and early insights to guide next steps.

More than one way to activate synthetic insights

QuestionPro synthetic data is not limited to one workflow. Teams can generate grounded synthetic insights from Communities, existing survey data, and interactive AI-driven conversations, depending on the type of research they need to run.

Synthetic survey responses

Generate AI-simulated survey responses using existing audience profiles and survey data. Test questionnaires, explore early trends, and validate ideas before launching a live study.

Converse AI

Have dynamic conversations with synthetic personas, ask follow-up questions, and explore insights interactively instead of relying on static one-time outputs.

Synthetic IDIs

Generate interview-style qualitative insights, summaries, and quotes instantly using existing community and survey data, without launching a new study.

What if you could ask your community anything, anytime?

Even with an active community, you cannot continuously go back to respondents every time a new idea comes up. Synthetic data changes this dynamic by allowing you to simulate responses from profiles that reflect your actual audience.

That is why QuestionPro focuses on grounded synthetic insights: outputs connected to real audience data, behavioral context, and research workflows, instead of generic AI responses disconnected from the people you are trying to understand.

Get started

Why not all synthetic data is the same

	QuestionPro	Generic AI
Real audience data
Behavioral context
You control the data
No AI training on your data
Segment-level modeling
Research-native workflow

This is not "made-up AI data"

A common concern around synthetic data is whether the insights are reliable or simply generated by a generic AI model. While modern language models can produce plausible responses, they often lack the context needed for meaningful research.

Without grounding in real data, outputs can become generic and disconnected from actual audience behavior.

Get started

Your data stays yours

Zero external AI training

QuestionPro does not use customer data to train external AI models. Your insights are generated entirely within your own environment.

Transparency and privacy

This ensures transparency, protects privacy, and allows you to benefit from synthetic data without losing ownership or control.

You control what is used

You control what data is used, which segments are modeled, and how the system is applied, ensuring outputs remain relevant and aligned with your research objectives.

Frequently asked questions

Synthetic data in research is artificially generated data that reflects patterns from real respondent data. It helps researchers explore ideas, simulate responses, and prepare stronger studies before launching full qualitative or quantitative research.

Synthetic data models analyze existing respondent profiles, survey history, and behavioral patterns to generate simulated answers. In QuestionPro, synthetic insights can be grounded in Communities, helping teams explore questions using audience context they already own.

Synthetic data can be useful for directional insight, early exploration, and research planning. It should not replace validated research when final measurement, compliance, or statistical confidence is required.

No. Synthetic data works best as a complement to real research. It helps teams decide what to test, which questions to ask, and where to focus before engaging real participants.

QuestionPro synthetic data is designed to work with real respondent context from Communities and research data. This helps reduce generic outputs and keeps synthetic insights closer to the audience being studied.

No. QuestionPro does not use customer data to train external AI models, customers own their data, and synthetic workflows are designed to keep control within their research environment.

Synthetic data for research

Turn your community into an always-on engine for grounded synthetic insights