What is synthetic research?

Synthetic research uses AI-powered personas that simulate how real buyers, customers, or market segments would respond to your research questions. It produces directional signal — insights to sharpen your hypotheses — before you invest in real primary fieldwork. Gather Synthetic runs AI-moderated interviews across any audience archetype in minutes, not weeks.

How is synthetic research different from real research?

Synthetic research generates directional signal using AI personas, while real primary research collects data from actual people. Synthetic pre-research is faster (minutes vs. weeks), cheaper, and ideal for hypothesis generation and stakeholder alignment. It is not statistically valid and should be used to focus and prioritize real fieldwork, not replace it. Gather offers both synthetic pre-research and real AI-moderated interviews with actual respondents.

What types of research can Gather Synthetic run?

Gather Synthetic supports 14 study types: Brand Perception, Product Feedback, Concept Testing, Competitive Intelligence, CX/NPS Deep Dive, Messaging & Claims Testing, Win/Loss Analysis, Market Segmentation, Pricing Research, Ad & Creative Testing, Customer Journey Mapping, Feature Prioritization, Churn & Retention Analysis, and Audience Discovery.

How much does synthetic research cost?

The first 5 synthetic interviews are free. After that, B2C audience interviews cost $0.50 each and B2B audience interviews cost $5.00 each. There is no subscription required.

How accurate is synthetic research?

Synthetic research is directional, not statistically accurate. Predictive accuracy and a statistical interval are only shown when established for the specific result. Treat findings as educated hypotheses to validate with real primary research, not as definitive measurements.

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Market research platform governance · PUBLIC RESEARCH BRIEF

ForstaHow much survey automation can a complex study safely reuse?

Forsta presents Research HX as a market-research suite spanning data collection, panel management, multiple methods, analytics and reporting. Its Decipher product supports complex logic, quotas, reusable templates, automated checks and AI-assisted workflows. Reuse can improve consistency, but it can also preserve assumptions that no longer fit a new audience or decision.

Updated 2026-10-29 · Simulation results not yet generated

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CHANGE ONE THING. LEARN WHAT MATTERS.

Three questions for the GTM team.

For Forsta, which changes in audience, market, objective or questionnaire logic should force a reusable survey template through full review instead of a fast relaunch?

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When an automated quality check passes but routing or quota logic creates an analytically biased sample, what review evidence should stop fieldwork?

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How should a team compare results across waves after changing question wording, localization or sample supply without presenting a broken trend as real movement?

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PROPOSED AUDIENCE

Who should weigh in?

North American market-research agencies, corporate insights teams and research-operations leaders evaluating Forsta. Include survey programmers, sample managers, analysts, quality reviewers and stakeholders responsible for recurring studies. Proposed audience only; no Forsta tenant, survey, panel, dashboard or private response data is included.

TWO TIME HORIZONS

Trial today. A habit tomorrow?

Near term · 0–90 days

Over 0–90 days, generate synthetic recurring-study specifications with seeded routing errors, quota interactions, translation changes and template drift. Compare review protocols, issue detection and launch decisions under fast-reuse and full-review workflows.

Longer term · 3–12 months

Over 3–12 months, introduce new markets, methods, panel sources and reporting owners. Study version control, trend breaks, defect recurrence and whether reusable assets remain understandable to teams that did not create them.

What would make the result actionable?

Keep machine-readable versions of questionnaires, routing, quotas, translations and sample specifications. Test logic with known synthetic cases, document every material change and validate cross-wave conclusions only after assessing measurement and sample equivalence.

A Gather simulation returns hypothetical customer reactions. Quantifying revenue, traffic or retention needs actual business inputs and validation against observed behavior.

About Forsta

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