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.

← All brands

Cross-functional work management · PUBLIC RESEARCH BRIEF

monday.comWhat gets a cross-functional launch out of the spreadsheet without rebuilding it badly?

monday.com presents work management for projects and tasks alongside dashboards, docs, forms, integrations and automations. Its current platform page also describes project-monitoring and status-reporting agents that surface risks, blockers and progress. This brief studies the smallest shared workflow that improves a real launch; it does not treat migration or automation activity as proof of better delivery.

Sources checked 2026-09-23 · 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 one cross-functional launch in monday.com, would a minimal shared board with milestones and owners or a role-specific template set lead to more accurate status and less duplicate tracking? Keep the same work scope and record shadow spreadsheets and missing dependencies.

Set up this study →

Would introducing monday.com automations after teams agree on ownership rules or introducing them during initial setup produce fewer broken or confusing handoffs? Test only reversible notifications or assignments and review every rule with affected users.

Set up this study →

For launch leadership, would a concise exception-based dashboard or a scheduled narrative status report better surface decisions that need attention without obscuring uncertainty? Compare whether readers identify the same blockers, owners and next decisions.

Set up this study →

PROPOSED AUDIENCE

Who should weigh in?

North American marketing, product, operations and PMO teams coordinating recurring launches or campaigns across at least three functions and considering monday.com as a shared system. Include project owners, contributors, approvers and executives who consume status, plus teams moving from spreadsheets or disconnected tools. Proposed audience; no time saving or delivery improvement is implied.

TWO TIME HORIZONS

Trial today. A habit tomorrow?

Near term · 0–90 days

Over 0–90 days, migrate one bounded launch with an explicit baseline and permission map. Measure update completeness, ownership accuracy, duplicated records, unresolved dependencies, notification burden and decision latency. Preserve an export and rollback path, and do not count board activity as delivery progress.

Longer term · 3–12 months

Over 3–12 months, follow repeated launches and workspace maintenance. Examine adoption by role, return of shadow systems, template drift, broken automations, permission changes, reporting trust and delivery outcomes relative to comparable work. Productivity or ROI claims require observed labor, delivery quality and subscription or administration cost.

What would make the result actionable?

Use authorized project artifacts, a current permission review, consented activity records and independent comparison with the source plan or launch outcome. Remove confidential customer and employee details from research materials, test automations in a safe workspace and require human approval before changing live assignments or communications. Simulated preference is not proof of productivity.

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

Public sources

monday.com work platform and work management capabilities ↗Current product page; checked 2026-09-23