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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AI meeting workflows & deliverables · PUBLIC RESEARCH BRIEF

ZoomWhich meeting output is safe to let an AI teammate finish?

Zoom's current ZoomMate page describes finding decisions across conversations and apps, delegating tasks, custom meeting-summary formats, recurring workflows and post-meeting work such as follow-ups and record updates. This brief studies where teams want draft assistance, source verification and explicit approval before an output becomes an action.

Sources checked 2026-09-24 · 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.

After a Zoom customer meeting, would a source-linked draft of decisions and commitments or a polished follow-up email produce more accurate human approval and fewer unsupported promises? Keep the transcript constant and require the account owner to edit and approve any message.

Set up this study →

For a ZoomMate post-meeting workflow, which step should remain draft-only: task creation, CRM update or external follow-up? Compare participant choices with an operations-approved policy and test ambiguous conversations where the system should take no action.

Set up this study →

Would a custom Zoom meeting-summary template organized by business outcome or by speaker and chronology better preserve dissent, uncertainty and owner accountability? Use consented or synthetic meetings and score against the recording and facilitator record.

Set up this study →

PROPOSED AUDIENCE

Who should weigh in?

North American sales, project and customer-success teams evaluating or using Zoom Workplace and ZoomMate for recurring meetings and follow-up. Include meeting hosts, participants, absent stakeholders, operations owners and administrators responsible for connected apps. Recruit authorized adult employees. Proposed audience; no time saving or task-completion result is implied.

TWO TIME HORIZONS

Trial today. A habit tomorrow?

Near term · 0–90 days

Over 0–90 days, run controlled post-meeting exercises with synthetic or consented transcripts and sandboxed connected apps. Measure source fidelity, correct commitments, unsupported inferences, approval edits, safe no-action decisions and task or record accuracy. Do not send messages or update production systems during the study.

Longer term · 3–12 months

Over 3–12 months, follow approved teams using stable workflow rules. Examine corrections to summaries and CRM records, missed or duplicate follow-ups, workflow drift, connector permissions, meeting consent and whether human reviewers continue to challenge outputs. Productivity and revenue claims require observed business outcomes after errors and administration costs.

What would make the result actionable?

Use current plan and connector settings, participant consent, minimized transcripts, versioned workflow rules and an independently approved record of commitments. Keep meeting content private, restrict tool permissions and require human confirmation before any external message or production update. Simulated willingness is not proof that autonomous execution is safe or valuable.

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

Public sources

ZoomMate capabilities for meeting summaries, search, workflows and post-meeting tasks ↗Current product page; checked 2026-09-24