Wynter Platform Help
Wynter (wynter.com) is an on-demand B2B message-testing and market-research platform. You upload a
homepage, landing page, ad, deck slide, cold email, or a paragraph of copy, pick a target audience from
Wynter's proprietary panel of 80,000+ LinkedIn-verified B2B professionals, and get back quantitative
scores (clarity, relevance, value/appeal, differentiation) plus verbatim qualitative quotes from each
respondent — organized by question, role, and segment — usually in under 48 hours.
Its niche vs the rest of the research/validation cluster:
- Real B2B panel, not synthetic. The whole pitch is real verified professionals in your ICP — the
opposite of synthetic-audience simulators (Artificial Societies, Ditto). Its edge over consumer usability
tools is hard-to-reach B2B targeting by seniority, industry, and company size.
- Message/positioning testing, not usability or idea validation. Wynter tells you whether your words
(positioning, value prop, copy, pricing narrative) land — not whether a built product is usable
(that's
/sales-lyssna / /sales-uxtweak) and not build-or-not (that's /sales-idea-validation).
- Self-serve, credit-metered. Pay-as-you-go per test (no annual commitment) or a subscription; billed
in credits (1 credit = 1 dollar). A solo/funded founder can run one test today without a sales call.
Two things to say almost every time:
- A message test measures resonance (stated preference), not demand. "This copy scored high / people said
they'd buy" is what lands with a reader, not a purchase. Keep the winning message and the quotes; take
the willingness-to-pay / conversion go/no-go to a real behavior test (smoke test, pre-sale) via
/sales-idea-validation.
- It's UI-only — no public API, webhooks, or MCP. Data-out is manual export (CSV/PDF) from the
dashboard. "Call the Wynter API / fire a webhook when a test finishes" is the wrong model — route a real
pipeline to
/sales-userintuition.
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 Wynter?
- A) Set up a test — pick a test type (message / preference / survey / cold-email / user-test /
pricing-page / brand-tracking) and write the questions
- B) Target an audience — build a B2B panel by seniority/industry/company size/region (or B2C, or bring
your own)
- C) Read results — quantitative scores + qualitative quotes, by role/segment
- D) Budget — credits, pay-as-you-go vs subscription, what a test costs
- E) Get data out — export/automation (there is no API/webhooks)
- F) Choose — Wynter vs synthetic simulators / usability tools / broader research
- Is the audience SaaS/software, or a different B2B vertical? This decides whether Wynter's panel builds
out cleanly (it skews SaaS) or you should tighten screeners / consider a peer.
Skip-ahead: if the user wants the validate-before-building method or a cross-tool comparison, 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 |
|---|
| The validate-before-building method, or comparing research/validation tools across the market | /sales-idea-validation {question} |
| A REST API / webhook / MCP-native research pipeline (Wynter has none — it's UI-only) | /sales-userintuition {question} |
| Running a real behavior demand test (smoke-test page, waitlist, pre-sale) after a message test | /sales-idea-validation or /sales-funnel {question} |
| Usability / prototype / IA testing on a built product or design (not message testing) | /sales-lyssna or /sales-uxtweak {question} |
| Consumer (not B2B) creative/message split-testing on a real panel — logos/ads/listings/covers/copy, with an API | /sales-pickfu {question} |
| Synthetic-audience message simulation (AI personas instead of a real panel) | /sales-societies or /sales-ditto {question} |
| Analyzing existing NPS/CSAT/VoC/survey data into themes (post-collection) | /sales-customer-feedback or /sales-trill {question} |
When routing, give the exact command: "This is a {domain} question — run: /sales-idea-validation {original question}"
Otherwise, answer Wynter-specific questions using Step 3.
Step 3 — Wynter reference
Read references/platform-guide.md for the full reference — the test-type / automation-surface table
(what's UI-only vs export), best-effort credit-based pricing and plan gates, the Test → Audience → Response
data model, how to write goal-based questions/screeners, audience targeting, and how to read scores vs quotes.
Read references/wynter-api-reference.md for the automation surface — it documents that there is no
public API/webhooks/MCP and inventories the real data-out options.
Answer using only the relevant section — don't dump the full reference.
Step 4 — Actionable guidance
- Say the caveat: a message test is resonance, not demand. Whatever the user asks, make explicit that a
high Wynter score (or panelists saying they'd buy) means the message lands with a real reader in the ICP
— a genuine, useful signal — but it is stated preference, not observed demand or a purchase. Point the
user to the verbatim quotes (objections, confusion, the words they use) as the real value rather than
trusting the top-line score, then take the willingness-to-pay / conversion go/no-go to a real behavior
test (smoke test, pre-sale) via
/sales-idea-validation.
- Treat automation as UI-only, and don't invent endpoints. When any API/webhook/export/integration comes
up, state that Wynter has no public REST API, webhooks, or MCP server — data-out is manual export
(CSV/PDF) from the dashboard, plus results by email. Don't design a REST/webhook pipeline or guess
endpoints; if a programmatic pipeline is a hard requirement, route to
/sales-userintuition. Present the
no-API finding as best-effort and point to wynter.com to confirm.
- Size a test by audience × seniority in credits, and call pricing best-effort. Billing is in credits
(1 credit = 1 dollar); a test's cost scales with audience size and seniority level, and pay-as-you-go
runs cost more than the same test on a subscription. Give a directional figure (a mid-size message test is
in the low hundreds of dollars) but present every number as best-effort and point to
wynter.com/pricing and the in-app cost calculator to confirm before running.
- Check the panel fits the vertical, and design questions to protect quality. State that Wynter's panel
skews SaaS/software — for other B2B verticals the audience may not build out fully (you may have to blend
segments), so tighten targeting or consider a peer. To counter low-effort or unqualified responses, write
goal-based, specific questions (not "do you like this?"), use screeners, and flag/request replacement
of clearly junk responses.
- Match the test type to the job. Recommend message testing for "does my copy/positioning land",
preference testing for A/B/C between value props or pages, buyer-intelligence surveys for ICP
pains/gains/JTBD, cold-email tests for outbound copy, and brand tracking for perception over time —
and reserve Wynter for B2B message/positioning, routing usability and build-or-not questions elsewhere.
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) — Wynter's pricing (credit amounts, per-test cost, subscription tiers),
panel size/composition, test-type lineup, and export options change; verify at wynter.com and
wynter.com/pricing.
- Resonance ≠ demand. A high score or "I'd buy this" is what lands with a reader, not a purchase. The
quotes (objections, confusion, real language) are the value — take the go/no-go to a real behavior test.
- No public API/webhooks/MCP — automation is manual export. Wynter confirms it has no API. Data-out is
CSV/PDF export + email; don't invent endpoints or design a webhook pipeline (that's a
/sales-userintuition
job). Best-effort — confirm at wynter.com.
- Priced in credits, not seats; PAYG costs more. 1 credit = 1 dollar; a test scales with audience size ×
seniority, and pay-as-you-go runs ~half-again the subscription rate. Subscriptions start high (four/five-
figure annual). Size the test in credits and confirm with the in-app calculator.
- Panel skews SaaS/software. Non-SaaS B2B verticals may not build out fully (you may blend disparate
segments). Verify the target audience exists at your needed size before committing credits.
- Respondent quality varies. Some panelists give shallow or off-target answers — a question/screener
design problem, not a dead panel. Write goal-based questions, add screeners/attention checks, and
flag/replace clearly junk responses.
- It's B2B message testing, not usability or idea validation. For testing a built product/prototype use
/sales-lyssna or /sales-uxtweak; for build-or-not use /sales-idea-validation; for a synthetic-audience
simulation use /sales-societies.
- Turnaround is hours, not minutes. Results land in roughly 12–48h — plan message iterations around that
cadence rather than expecting instant answers.
Related skills
/sales-idea-validation — The tool-agnostic validate-before-building method + the full research/validator tool landscape (use to decide build-or-not; a message-test "yes" is resonance, not demand). Install: npx skills add sales-skills/sales --skill sales-idea-validation -a claude-code/sales-pickfu — PickFu, the consumer-panel counterpart (fast, self-serve creative/message split-testing polls on a 15M+ consumer panel, with a real REST API/MCP/CLI). Pick PickFu for consumer creative/copy testing at speed; pick Wynter for hard-to-reach B2B positioning. Install: npx skills add sales-skills/sales --skill sales-pickfu -a claude-code/sales-societies — Artificial Societies, the synthetic-audience counterpart (simulate how a message lands with AI personas before spending on a real panel); pick Societies for fast/cheap pre-flight, Wynter for real verified B2B respondents. Install: npx skills add sales-skills/sales --skill sales-societies -a claude-code/sales-evelance — Evelance, the synthetic message/creative-tester (AI personas score copy/creative/product on 12 psychology metrics in minutes) — the fast, cheap synthetic pre-flight to triage messaging before validating with Wynter's real B2B panel. Install: npx skills add sales-skills/sales --skill sales-evelance -a claude-code/sales-lyssna — Self-serve usability/IA testing on a built artifact (five-second/first-click/preference, card sort, tree test) — the right tool when the question is "is my product usable", not "does my message land". Install: npx skills add sales-skills/sales --skill sales-lyssna -a claude-code/sales-userintuition — The REST-API/webhook/MCP research peer — the pick when you need a programmatic pipeline Wynter's UI-only surface can't offer. Install: npx skills add sales-skills/sales --skill sales-userintuition -a claude-code/sales-customer-feedback — Real-customer NPS/CSAT/VoC strategy across tools (use to analyze existing feedback; Wynter proactively tests new messages). Install: npx skills add sales-skills/sales --skill sales-customer-feedback -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: "My Wynter message test scored high — should I build/launch on that?"
User says: "I tested my new homepage headline on Wynter and it scored 4.3/5 on clarity and value, and a bunch of respondents said they'd sign up. Green light to build the product around it?"
Skill does: Credits the result as a real signal — actual verified B2B people in the ICP found the
message clear and appealing, far better than guessing or a synthetic score. Then draws the line: that's
resonance, not demand — a message landing with a reader is not a purchase. Directs the user to the
verbatim quotes (what confused them, what objections came up, the words they used) as the real payload,
and to take the willingness-to-pay / conversion go/no-go to a real behavior test (smoke-test page or
pre-sale) via /sales-idea-validation. Notes scores/pricing are best-effort.
Result: The founder keeps the winning message + quotes and runs a smoke test before committing.
Example 2: "How do I use the Wynter API to push test results into my dashboard automatically?" (developer/automation)
User says: "I want a webhook to fire when a Wynter test completes and POST the scores + quotes into our BigQuery / internal dashboard. What's the endpoint?"
Skill does: States plainly that Wynter has no public REST API, webhooks, or MCP server (Wynter itself
confirms it has no API) — so there is no endpoint or key to build against, and it does not invent one
(best-effort; confirm at wynter.com). Explains the only data-out is manual CSV/PDF export from the
dashboard plus emailed results. For an automated completion-to-warehouse pipeline, routes to
/sales-userintuition (API + webhooks + MCP).
Result: The user stops hunting for an API that doesn't exist and either exports manually or moves the pipeline to an API-native tool.
Example 3: "What will a Wynter test cost me, and will the panel cover my niche?"
User says: "I sell to hospital procurement leaders, not SaaS. What does a Wynter message test cost and can it reach that audience?"
Skill does: Explains billing is in credits (1 credit = 1 dollar), a test scales with audience size ×
seniority, and pay-as-you-go costs more than the same test on a subscription (a mid-size message test is
in the low hundreds of dollars — all best-effort, confirm at wynter.com/pricing and the in-app
calculator). Then flags the fit risk: Wynter's panel skews SaaS/software, so a niche vertical like hospital
procurement may not build out to the needed size (you may have to blend segments) — verify the audience exists
before spending credits, tighten screeners, and consider a peer if it's too thin.
Result: The user budgets credits correctly and checks panel coverage before committing.
Troubleshooting
"Where's the Wynter REST API / webhook to export test results?"
Symptom: You're looking for an API key and a webhook to fire when a test completes.
Cause: Wynter is UI-only — it has no public REST API, webhooks, or MCP server (Wynter confirms it has no API). Data-out is manual export.
Solution: Export scores/quotes as CSV/PDF from the dashboard (results also arrive by email). If a programmatic pipeline into a warehouse/CRM is a hard requirement, use an API-native tool — route to /sales-userintuition. Present the no-API finding as best-effort and confirm at wynter.com.
"My Wynter responses feel shallow or off-target — is the panel bad?"
Symptom: Some respondents give one-word or generic answers, or don't seem to fit your ICP.
Cause: Usually a question/screener-design problem, not a dead panel — vague prompts ("do you like this?") invite low-effort answers, and the panel skews SaaS/software so niche B2B targeting can pull marginal fits.
Solution: Write goal-based, specific questions, add screeners and attention checks, tighten audience filters (seniority/industry/company size), and flag/request replacement of clearly junk responses. For non-SaaS verticals, verify the audience builds out to size first — or consider a peer.
"How much will this test cost, and why is pay-as-you-go more expensive?"
Symptom: The credit total is higher than expected, or PAYG looks pricier than a subscription.
Cause: Wynter bills in credits (1 credit = 1 dollar); cost scales with audience size and seniority level, and pay-as-you-go runs cost more than the same test under a subscription (subscriptions start in the four/five-figure annual range).
Solution: Size the test by audience × seniority, use the in-app cost calculator before running, and if you'll run many tests, compare PAYG against a subscription. Treat all figures as best-effort — confirm current credit amounts and per-test cost at wynter.com/pricing.
