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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AI video and avatars · PUBLIC RESEARCH BRIEF

SynthesiaWhich review step makes localized avatar video publishable?

Synthesia describes stock, customizable and personal avatars, including a live consent process for personal avatars, plus video translation with transcript, pronunciation and voice editing. These are vendor-described capabilities; they do not establish that translated training content is accurate or approved.

Updated 2026-10-15 · 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 Synthesia, which approval sequence best catches meaning errors in a translated training video without creating an unworkable review burden? Compare language, subject-matter and compliance review roles.

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When should a team choose a stock avatar, a customized character or a consent-verified personal avatar for internal learning? Test credibility and fit without assuming realism improves comprehension.

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Which visible provenance or disclosure cues would help employees understand who approved an avatar-led video and whether its script is authoritative?

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PROPOSED AUDIENCE

Who should weigh in?

Global learning, internal communications, localization, compliance and brand leaders at mid-market and enterprise organizations evaluating avatar-led video. Include subject-matter experts, language reviewers, accessibility owners and final publishers. Proposed audience only.

TWO TIME HORIZONS

Trial today. A habit tomorrow?

Near term · 0–90 days

Create synthetic training scripts with deliberate terminology and pronunciation challenges, then compare review sequences and avatar choices. Measure error detection, reviewer confidence, handoff clarity and time to approval rather than claiming learning outcomes.

Longer term · 3–12 months

Track approved pilots across revisions and languages to study governance consistency, correction rework, content reuse and comprehension in real learning contexts. Separate faster production from effective learning.

What would make the result actionable?

Require live consent where a personal likeness is used, language-owner transcript approval, pronunciation checks, subject-matter sign-off, accessibility review, version history and post-view comprehension testing. Validate business impact with real production and learning baselines.

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

About Synthesia

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