Great Question (greatquestion.co) platform help — an all-in-one UX research platform: recruit real participants (6M+ B2B/B2C panel or your own customers in a built-in Research CRM), run moderated and AI-moderated (beta) interviews, unmoderated Figma prototype tests, surveys, card sorting, tree testing and focus groups, then analyze in a repository (AI synthesis, highlight reels). Unusually complete automation: a V1.0 REST API (Bearer; studies, candidates, sessions), HMAC-signed webhooks, AND a native MCP server (112+ actions, Enterprise). Use when setting up a Great Question study or recruit, syncing research into a CRM or warehouse, building a Great Question API or webhook pipeline, wiring its MCP server into Claude Code, or reading its per-seat self-serve vs Enterprise pricing. Do NOT use for the validate-before-building method or comparing research tools broadly (use /sales-idea-validation), or analyzing existing NPS/CSAT/VoC feedback (use /sales-customer-feedback).
Great Question (greatquestion.co) platform help — an all-in-one UX research platform: recruit real participants (6M+ B2B/B2C panel or your own customers in a built-in Research CRM), run moderated and AI-moderated (beta) interviews, unmoderated Figma prototype tests, surveys, card sorting, tree testing and focus groups, then analyze in a repository (AI synthesis, highlight reels). Unusually complete automation: a V1.0 REST API (Bearer; studies, candidates, sessions), HMAC-signed webhooks, AND a native MCP server (112+ actions, Enterprise). Use when setting up a Great Question study or recruit, syncing research into a CRM or warehouse, building a Great Question API or webhook pipeline, wiring its MCP server into Claude Code, or reading its per-seat self-serve vs Enterprise pricing. Do NOT use for the validate-before-building method or comparing research tools broadly (use /sales-idea-validation), or analyzing existing NPS/CSAT/VoC feedback (use /sales-customer-feedback).
argument-hint
[describe what you need help with in Great Question]
license
MIT
version
1.0.2
github
https://github.com/GreatQuestion
tags
["sales","pre-launch","platform"]
Great Question Platform Help
Great Question (greatquestion.co) is an all-in-one UX research platform — "the UX research platform
for every team building and improving products." It bundles three jobs teams usually buy separately:
recruit (a 6M+ B2B/B2C paneland your own customers via a built-in Research CRM —
segmentation, eligibility rules, scheduling, automated incentives via Tremendous), run studies
(moderated + AI-moderated [beta] interviews, unmoderated Figma prototype testing, surveys, focus
groups, card sorting, tree testing, online tasks, observer rooms, blind studies), and analyze & store
(a centralized research repository, AI synthesis, highlight reels).
Its place in the landscape is the research-ops / real-participant class — closest to User Interviews
(recruitment) + Dovetail (repository) combined, run on real people. It is not a synthetic-persona
tool (Synthetic Users, Ditto) and not a pure AI-moderated-interview tool (User Intuition, Strella,
Voicepanel) — moderation is primarily human/scheduled, with AI moderation in beta.
Two things to say almost every time:
Real research, but a stated "I'd pay" is still not a purchase. Interviews and unmoderated tasks surface
genuine reasoning/objections/language (strong signal) — but the WTP go/no-go belongs to a real behavior test (pre-sale, smoke test), not a transcript → /sales-idea-validation.
The automation surface is unusually complete — pick the right one. Great Question has a REST API, HMAC-signed webhooks,
and a native MCP server all at once (MCP for agent ops, REST for a pipeline, webhooks for event sync) — but note the gates: API tokens need Team/Enterprise, and MCP is Enterprise/early-access.
Step 1 — Gather context
If references/learnings.md exists, read it first for accumulated platform knowledge.
Ask only what you can't infer:
What do you want from Great Question?
A) Set up a study — pick a method (moderated/AI-moderated interview, unmoderated Figma test,
survey, card sort, tree test, focus group), objective, screener, incentive
B) Recruit — the 6M+ panel (screening/eligibility) vs your own customers (Research CRM import)
C) Analyze — repository, AI synthesis, highlight reels, sessions
D) Automate / integrate — REST API pipeline, webhooks, the MCP server, or Zapier/Make
E) Choose / price — self-serve ($129/seat, 5-seat cap) vs Enterprise, or GQ vs another tool
Is this discovery (strangers on the panel) or feedback from your own users? That decides panel
vs Research-CRM and how honest the signal is.
Skip-ahead: if the user wants to compare research tools across the market or the
validate-before-building method, that's a /sales-idea-validation question — route in Step 2.
Step 2 — Route or answer directly
If the user's question is about…
Route to
Comparing research/idea/synthetic tools across the market, or the validate-before-building method
/sales-idea-validation {question}
Running a real behavior demand test (smoke-test page, waitlist, pre-sale) after research
/sales-idea-validation or /sales-funnel{question}
Analyzing existing NPS/CSAT/VoC feedback (post-launch surveys, not new studies)
/sales-customer-feedback {question}
A synthetic-persona approach (AI personas instead of real people)
/sales-syntheticusers or /sales-ditto{question}
A pure AI-moderated real-human interview tool with a self-serve API/webhooks
/sales-userintuition {question}
When routing, give the exact command: "This is a {domain} question — run: /sales-idea-validation {original question}"
Otherwise, answer Great Question-specific questions using Step 3.
Step 3 — Great Question reference
Read references/platform-guide.md for the full reference — the module/automation-surface table
(API vs webhook vs MCP vs UI-only), best-effort pricing/plan gates, the Study → Candidate → Participant →
Session data model, recruiting (panel vs Research CRM), and quick-start recipes (REST sync, CRM upsert,
webhook verification, MCP). Read references/great-question-api-reference.md for the verbatim API
surface (Bearer auth + non-standard header, endpoints, JSON models, webhook HMAC, MCP). Answer using only
the relevant section — don't dump the full reference.
Step 4 — Actionable guidance
Say the caveat: real research is not a purchase. Whatever the user asks, make explicit that Great
Question studies real people (a step up from synthetic personas — genuine reasoning, objections,
language), but a stated "I'd pay" in an interview/survey is not observed demand. Keep the
why/objections/language; take the go/no-go from a real behavior test (smoke-test click, pre-sale)
→ /sales-idea-validation.
Match the automation surface to the job, and name the gates. Great Question has all three: REST
API (data pipeline into a CRM/warehouse), HMAC-signed webhooks (event-driven sync), and a
native MCP server (agent-driven study/candidate ops from Claude/Cursor). Recommend by job — but
always state the plan gates: API tokens require Team/Enterprise (admin-generated at Account >
API tokens; access enabled by support), and MCP is Enterprise/early-access. No self-serve API key.
For webhooks, warn it's concierge + no retries. Endpoints are set up by contacting support (no
self-serve UI) and there's no documented retry policy — verify the HMAC signature
(X-Signature-SHA256: t=<ts>,v1=<sig>, sign ts + "." + body, timing-safe compare) and add a
reconcile poll (GET /v1/studies/{id}/participants) to catch missed participation.completed events.
Note the non-standard auth header and beta status. The documented header is literally
Authorization: "BEARER: <token>" (with BEARER: and quotes) and the API is V1.0 / beta, under
active development — tell the user to confirm the exact header spelling and base host in their
Account > API tokens screen, and to code defensively against changes.
Watch the 5-seat self-serve cap. Self-Serve is $129/seat/mo, capped at 5 seats (unlimited free
observer seats). Focus groups, card sort/tree test, Salesforce/Snowflake/Qualtrics/Databricks
connectors, SSO/SCIM, HIPAA, and MCP are Enterprise-only (quote-only). If the user needs any of
those or a 6th seat, they're on the Enterprise path — flag it early; present all pricing as best-effort
(confirm at greatquestion.co/pricing).
Panel vs Research CRM: match to the question. The 6M+ panel reaches strangers for
discovery/concept tests; your own customers (CSV import, POST /v1/candidates upsert by email, or
Salesforce/Snowflake connectors) are the honest audience for churn/win-loss feedback — check
consented_at/unsubscribed before contacting; use POST /v1/studies/{id}/candidates (≤5,000, poll
status_url) for a study-scoped batch. Before wiring MCP, enable "Hide PII via MCP" and connect
with a role scoped to what the agent should do (MCP mirrors your in-app permissions).
If you discover a gotcha or tip not in references/learnings.md, append it there with today's date.
Gotchas
Best-effort from research (2026-07) — pricing ($129/seat self-serve, 5-seat cap; Enterprise quote-only),
panel size ("6M+"), the V1.0-beta API surface, and MCP early-access status all move; verify at
greatquestion.co/pricing and developer.greatquestion.co.
Real ≠ demand. Studies reveal the why better than any synthetic tool, but a stated intent to pay
is not a purchase — the go/no-go still belongs to a real behavior test (pre-sale, smoke test).
API tokens are plan-gated (Team/Enterprise) and access must be enabled. Not available on the
$129 self-serve plan by default — admins generate tokens at Account > API tokens, and support must
enable API access for the workspace. Don't assume an instant key.
The auth header is non-standard. Documented as Authorization: "BEARER: <token>" (with the colon
and quotes) — verify exact spelling in-app; the API is V1.0/beta, so code defensively.
Webhooks are concierge-registered with no documented retries. Email support to set up an endpoint;
verify the HMAC signature and poll to reconcile missed participation.completed events.
MCP is Enterprise / early-access.https://greatquestion.co/api/mcp/v1 (OAuth, 112+ actions) is
not instant self-serve — request access. Enable "Hide PII via MCP" and connect with a scoped role.
The 5-seat self-serve cap + Enterprise-only methods are the real constraints. A growing team (6th
seat), focus groups, card sorting, tree testing, warehouse/CRM connectors, SSO, HIPAA, or MCP all
push you to Enterprise (quote-only) — don't design a self-serve card-sort study.
G2 reviewers flag occasional bugs, slow performance, and "limited survey features." Set
expectations for complex surveys; the platform's strength is consolidation, not depth in every module.
Related skills
/sales-idea-validation — The tool-agnostic validate-before-building method + the full research/persona/validator tool landscape (use this to decide build-or-not; a research "yes" is not demand). Install: npx skills add sales-skills/sales --skill sales-idea-validation -a claude-code
/sales-customer-feedback — Analyze existing NPS/CSAT/VoC feedback across tools (Great Question runs new studies and stores them in its repository; this is the post-launch feedback-strategy peer). Install: npx skills add sales-skills/sales --skill sales-customer-feedback -a claude-code
/sales-notably — Notably (notably.ai) — the analysis-only research repository peer: it synthesizes qualitative data you already have (transcripts/notes/open-ends) into AI-clustered themes + insights, where Great Question recruits and runs the studies that produce that data. The pick for the synthesis step once you have data — but it has no panel/recruiting and no API/webhooks/MCP (Miro/FigJam sync + manual export only). Install: npx skills add sales-skills/sales --skill sales-notably -a claude-code
/sales-userintuition — Pure real-human AI-moderated interviews with a self-serve REST API + webhooks + MCP — the pick when you want deep automated interviews, not an all-in-one recruit+repository suite. Install: npx skills add sales-skills/sales --skill sales-userintuition -a claude-code
/sales-respondent — Respondent (respondent.io) — the recruit-only peer (the direct twin of User Interviews): recruit + screen + schedule + pay real participants from a 4M+ B2B/professional panel via a Partner REST API, then run the study in your own tool. The pick when you only need recruiting (not Great Question's run + repository). Install: npx skills add sales-skills/sales --skill sales-respondent -a claude-code
/sales-lookback — Lookback (lookback.com) — the self-serve, run-the-live-session peer: live/moderated video interviews + usability tests with observer rooms and best-in-class mobile screen+gesture recording (recruits via User Interviews, no own panel). The pick when you want to run the live session yourself rather than Great Question's all-in-one recruit+repository suite — but it's UI-first (no self-serve API). Install: npx skills add sales-skills/sales --skill sales-lookback -a claude-code
/sales-participant-kit — Participant Kit (participantkit.com, formerly Consent Kit) — the consent + participant-ops peer: informed consent forms/NDAs with e-signatures + audit trail, a participant CRM + opt-in panels, retention/deletion reminders, and UK/EU data residency — the compliance/ops layer around studies, where Great Question runs and stores them. The pick when the job is consent/GDPR governance, not recruit-and-run — but its API is Enterprise + request-only (no webhooks/MCP). Install: npx skills add sales-skills/sales --skill sales-participant-kit -a claude-code
/sales-syntheticusers — Synthetic-research studies (AI personas, not real people) for a fast, cheap directional pre-test before spending on real recruits. Install: npx skills add sales-skills/sales --skill sales-syntheticusers -a claude-code
/sales-funnel — Build the smoke-test / fake-door landing page that turns a research hypothesis into a real demand test. Install: npx skills add sales-skills/sales --skill sales-funnel -a claude-code
/sales-do — Not sure which skill to use? The router matches any sales objective to the right skill. Install: npx skills add sales-skills/sales --skill sales-do -a claude-code
Examples
Example 1: "How do I sync completed Great Question research into my warehouse?" (developer/automation)
User says: "I want completed interviews and participant data flowing into Snowflake automatically."
Skill does: Lays out the three surfaces and picks by job — a REST pipeline (GET /v1/studies?status=closed → GET /v1/studies/{id}/participants, paginated 100/page, Bearer auth) for a
scheduled pull, plus participation.completed webhooks (HMAC-verified) for near-real-time sync,
with a poll to reconcile since retries are undocumented. Flags that API tokens require a
Team/Enterprise plan and API access must be enabled by support, and that the header is the
non-standard Authorization: "BEARER: <token>". Notes native Snowflake/Salesforce connectors are
Enterprise-gated as a no-code alternative.
Result: The user builds a webhook + reconcile-poll pipeline and knows the plan gate up front.
Example 2: "The interviews loved my concept — should I build it?"
User says: "I ran 15 Great Question interviews and a survey; people said they'd pay. Green light?"
Skill does: Credits the signal as real (actual people, genuine reasoning — far better than a
synthetic tool), then draws the line: a stated "I'd pay" in a study is not a purchase. Tells the
user to mine the repository highlight reels and transcripts for objections, hesitation, and pricing
language, then take the go/no-go from a real behavior test (pre-sale or "buy" click) via
/sales-idea-validation.
Result: The founder keeps the qualitative depth and runs a pre-sale before committing to build.
Example 3: "Is the $129 plan enough for my team, and can I run a card sort?"
User says: "We're 6 people and want card sorting and Salesforce sync on the self-serve plan."
Skill does: Flags two Enterprise gates on Self-Serve: it's capped at 5 seats (a 6th person
pushes you to Enterprise), and card sorting, tree testing, and the Salesforce/Snowflake connectors
are Enterprise-only. Explains Self-Serve is $129/seat/mo (unlimited free observer seats, 100
participants / 100 hr storage) and Enterprise is quote-only, all best-effort — confirm at
greatquestion.co/pricing.
Result: The team plans the Enterprise conversation instead of hitting the wall mid-setup.
Troubleshooting
"Where's my Great Question API key? I'm on the self-serve plan"
Symptom: You can't find an API token screen or your calls 401.
Cause: API tokens require a Team or Enterprise plan, are admin-generated (Account > API
tokens), and API access must be enabled for the workspace by Great Question support.
Solution: Confirm you're on Team/Enterprise, have an admin generate the token, and email
support@greatquestion.co to enable API access. Use the documented header exactly:
Authorization: "BEARER: <token>" (verify the spelling in-app; the API is V1.0/beta).
"My webhook never fired / I missed a completion event"
Symptom: participation.completed didn't arrive, or arrived and you can't verify it.
Cause: Webhook endpoints are registered by contacting support (no self-serve UI), and there's
no documented retry policy.
Solution: Ask support to register your endpoint; verify each request's X-Signature-SHA256
(t=<ts>,v1=<sig> — sign ts + "." + rawBody with HMAC-SHA256, timing-safe compare); and add a
reconcile poll (GET /v1/studies/{id}/participants) to catch anything the webhook missed.
"My agent can't run a card sort / can't see a study over MCP"
Symptom: The MCP connection works but a method or study is unavailable.
Cause: MCP mirrors your in-app role and plan — card sorting/tree testing/focus groups are
Enterprise-only, and if a study is hidden from your UI role it's hidden from MCP. MCP itself is
Enterprise/early-access.
Solution: Confirm MCP access is enabled (request it), connect with a role scoped to the studies you
need, and enable "Hide PII via MCP" to redact candidate PII before it reaches the agent. For
Enterprise-only methods, use the UI on an Enterprise plan.
