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.

← All brands

Application observability & debugging · PUBLIC RESEARCH BRIEF

SentryWhich issue context gets a team from alert to the right owner fastest?

Sentry currently documents issue details that can include stack traces, breadcrumbs, tags, related traces, replays, attachments and user feedback, plus searchable structured logs. Filters and recommended-event selection affect what a responder sees. This brief studies triage comprehension with fictional telemetry; it does not claim that a recommended event identifies root cause or that faster viewing means faster resolution.

Updated 2026-10-08 · 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 Sentry issue, would an evidence-ranked summary or a service-ownership cue better help an on-call responder route the problem without prematurely naming a root cause?

Set up this study →

When several events are grouped into one issue, would an explanation of why an event is recommended or a compact first-versus-latest event diff better help a developer choose what to inspect next?

Set up this study →

When logs, traces and replay context disagree, would a timeline that preserves each source or a conflict flag with suggested verification steps better prevent a team from trusting the most vivid artifact?

Set up this study →

PROPOSED AUDIENCE

Who should weigh in?

North American software engineering, site reliability, quality and product teams using or evaluating Sentry, including on-call responders, service owners, frontend and backend developers and engineering managers. Recruit participants with different familiarity with distributed systems and incident response. Proposed audience; no production error, log, replay, attachment or user identity is included.

TWO TIME HORIZONS

Trial today. A habit tomorrow?

Near term · 0–90 days

Over 0–90 days, test fictional Sentry issues with seeded errors, releases, traces, logs and replay fragments. Measure routing accuracy, evidence retrieval, premature root-cause claims, escalation quality and time to a correct next diagnostic step. Trigger no production alert.

Longer term · 3–12 months

Over 3–12 months, follow consenting teams in sandbox or de-identified projects across ownership changes, releases and recurring issue groups. Examine reopen rates, misrouting, evidence gaps and whether triage guidance remains useful as services evolve. Reliability gains require observed incident outcomes.

What would make the result actionable?

Use versioned Sentry documentation, synthetic telemetry with a hidden fault and ownership graph, controlled issue-grouping edge cases and task logs. Blind participants to the seeded cause, score both diagnosis and next-step quality, review data scrubbing and access controls, and keep every user artifact fictional.

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

About Sentry

Visit the company website ↗