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. Confidence scores reflect internal AI response consistency, not statistical significance. Quantitative projections carry a ±15–20% margin of error. Treat findings as educated hypotheses to validate with real primary research, not as definitive measurements.

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Website experience design & optimization · PUBLIC RESEARCH BRIEF

WebflowWhich website change can marketing ship without losing control?

Webflow's current platform page describes visual development, a composable CMS, analytics, A/B testing, AI-powered personalization, localization, SEO controls and publishing permissions. This brief studies which website changes marketing can own directly and which still need explicit design, engineering or governance review.

Sources checked 2026-09-26 · Simulation results not yet generated

Test a question in Gather ↗Explore fictional demo →

CHANGE ONE THING. LEARN WHAT MATTERS.

Three questions for the GTM team.

For a new Webflow campaign page, would a marketer starting from a governed page-building pattern or handing a complete design to a developer produce a more accurate on-brand result with fewer approval loops? Use the same requirements and staging environment.

Set up this study →

When Webflow teams choose an optimization approach, would a transparent A/B test or AI-powered personalization earn more stakeholder trust for the first experiment? Compare hypothesis quality, audience logic, consent review and interpretation—not conversion results that have not occurred.

Set up this study →

For a localized Webflow page, would a full-page translated draft or a field-by-field workflow with source context help reviewers catch more brand, legal and cultural issues before publishing? Use synthetic copy and approved locale guidance.

Set up this study →

PROPOSED AUDIENCE

Who should weigh in?

North American B2B and B2C organizations evaluating or using Webflow for a marketing website. Include web marketers, designers, content editors, growth practitioners, developers, localization owners and brand or security approvers. Recruit authorized adult employees. Proposed audience; no conversion or speed outcome is implied.

TWO TIME HORIZONS

Trial today. A habit tomorrow?

Near term · 0–90 days

Over 0–90 days, run controlled page-building, optimization-planning and localization tasks in a staging site with fixed requirements and approval roles. Measure requirement coverage, brand deviations, reviewer corrections, accessibility checks, publishing errors and time spent in avoidable handoffs. Do not publish experiments or personalized experiences to live visitors.

Longer term · 3–12 months

Over 3–12 months, follow approved teams across repeated releases. Examine template drift, unauthorized changes, experiment quality, content freshness, localization maintenance, accessibility regressions and engineering demand. Speed or conversion claims require observed production outcomes and comparable baselines.

What would make the result actionable?

Use a versioned brief and design system, staging-only content, current permissions, approved analytics definitions and independent review for brand, accessibility and technical quality. Preserve consent and privacy requirements and require authorized publication. Simulated confidence is not evidence of conversion lift or production reliability.

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

Public sources

Webflow platform for visual development, CMS, optimization and governance ↗Current product page; checked 2026-09-26