--- name: sales-researchgoat description: "ResearchGOAT (researchgoat.com) platform help — a self-serve AI qualitative research tool that runs AI-moderated real-time voice interviews with real people in any language, then delivers AI-analyzed insights. Fuller-stack vs lightweight peers: an AI research-design assist (objective, pre-screening/screener survey, respondent selection) plus built-in participant recruitment, metered in interview-minutes with a free tier, cheaper than traditional qual. Use when setting up a ResearchGOAT study or writing its objective and screener, running multilingual AI voice interviews, sizing its free interview-minutes and plan gates, recruiting or screening respondents, getting data out when there is no public API, or choosing ResearchGOAT vs Chikka / AskMore / User Intuition. Do NOT use for the validate-before-building method or comparing research tools (use /sales-idea-validation), an API/webhook/MCP interview pipeline (use /sales-userintuition), or analyzing existing feedback into themes (use /sales-customer-feedback)." argument-hint: "[describe what you need help with in ResearchGOAT]" license: MIT version: 1.0.0 tags: [sales, pre-launch, platform] --- # ResearchGOAT Platform Help ResearchGOAT (researchgoat.com) is a **self-serve generative-AI qualitative research** tool that runs **AI-moderated, real-time voice interviews with real people** and returns **AI-analyzed insights**. You set a research objective; its AI helps **design the study** (shape the objective, draft a **pre-screening/screener survey**, and select respondents), an **AI interviewer** conducts live interviews **in any language** (laddering and following up like a human moderator), and it **synthesizes** the transcripts into findings — pitched at **up to ~90% lower cost** than traditional moderated qual. Its niche in the real-human AI-moderated-interview cluster (User Intuition, Strella, Voicepanel, Frank, Chikka, AskMore, Listen Labs) is being the **end-to-end, voice-first, self-serve** option: - **Fuller stack than the lightweight peers.** It bundles **AI research design + a screener + participant recruitment/selection + AI analysis** into one flow — closer to a design→recruit→interview→analyze suite than to a bring-your-own-participants share-link tool (Frank, AskMore, Chikka bring their own audience). - **Voice-first and multilingual.** Live AI voice interviews in any language — the depth of a spoken answer, not a written form (contrast text-first AskMore). - **Self-serve, minute-metered, with a free tier.** Billing is in **AI interview-minutes** (free tier includes a project and free minutes/month), so a solo maker can start today — the opposite of demo-gated Listen Labs / Voicepanel. **Two things to say almost every time:** - **It's real people, but a stated "I'd pay" is still not a purchase.** Real interviews beat synthetic signal (genuine reasoning, objections, language) — but the willingness-to-pay go/no-go belongs to a **real behavior test** (pre-sale, smoke test), not an interview transcript. Route that to `/sales-idea-validation`. - **It's UI-only — no public API, webhooks, or MCP surfaced.** Data-out is **manual export**. "Call the ResearchGOAT API / fire a webhook on completion" is the wrong mental model — for a real pipeline, route 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: 1. **What do you want from ResearchGOAT?** - A) **Design a study** — write the objective, let the AI draft a **pre-screening/screener survey**, set the interview questions - B) **Recruit / screen participants** — use built-in recruitment/respondent selection, or bring your own audience - C) **Run interviews** — live AI-moderated **voice** interviews, any language - D) **Read / export results** — AI-synthesized insights + transcripts (there is no API/webhooks) - E) **Pricing / minutes** — free interview-minutes, plan gates, what a minute buys - F) **Choose** — ResearchGOAT vs Chikka / AskMore / User Intuition / Listen Labs / Strella 2. **Is this discovery (strangers) or feedback from your own users/customers?** This decides whether you lean on ResearchGOAT's recruitment or bring your own list. 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}` | | A **REST API / webhook / MCP**-native interview pipeline (ResearchGOAT has none — it's UI-only) | `/sales-userintuition {question}` | | Running a **real behavior** demand test (smoke-test page, waitlist, pre-sale) after interviews | `/sales-idea-validation` or `/sales-funnel` `{question}` | | Analyzing **existing** NPS/CSAT/VoC/interview data into themes (post-collection, not new interviews) | `/sales-customer-feedback` or `/sales-trill` `{question}` | | **Synthetic-persona** interviews (AI personas instead of real people) | `/sales-syntheticusers` or `/sales-ditto` `{question}` | | A **text-first / async** AI interviewer, or turning interviews into testimonials/case studies | `/sales-askmore` or `/sales-chikka` `{question}` | When routing, give the exact command: "This is a {domain} question — run: `/sales-idea-validation {original question}`" Otherwise, answer ResearchGOAT-specific questions using Step 3. ## Step 3 — ResearchGOAT reference **Read `references/platform-guide.md`** for the full reference — the module/automation-surface table (what's UI-only vs export), best-effort minute-based pricing and free-tier limits, the Project → Screener → Interview → Insights data model, the AI-research-design + recruitment workflow, the multilingual voice-interview flow, and how the AI's adaptive follow-ups work. **Read `references/researchgoat-api-reference.md`** for the automation surface — it documents that there is **no public API/webhooks/MCP** and inventories the actual data-out options. Answer using only the relevant section — don't dump the full reference. ## Step 4 — Actionable guidance - **Say the caveat: a real interview is not a purchase.** Whatever the user asks, make explicit that ResearchGOAT interviews **real people** (a big step up from synthetic personas — genuine reasoning, objections, language), but a stated "I'd pay" in an interview is **not observed demand**. Point the user to the **transcripts and AI insights** for objections and pricing language rather than trusting the top-line synthesis as a verdict, then take the go/no-go from a **real behavior test** (pre-sale, smoke test) — route that to `/sales-idea-validation`. - **Treat automation as UI-only, and don't invent endpoints.** When any automation/export/integration comes up, state that ResearchGOAT has **no public REST API, webhooks, or MCP server** surfaced — data-out is **manual export** of transcripts/insights. 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** — the live site is a JS-rendered SPA; confirm at researchgoat.com. - **Size it by interview-minutes, not seats, and call pricing best-effort.** Billing is metered in **AI interview-minutes** (free tier includes a project + free minutes/month, e.g. a ~360-minute allotment seen at research). Present every figure as **best-effort** and point to **researchgoat.com/pricing** to confirm the current minute allotment and plan gates, since the SPA changes and paid tiers aren't cleanly published. - **Use its design + recruitment stack, but verify the recruitment source.** ResearchGOAT can **draft the screener and select/recruit respondents** — a real edge over bring-your-own-participants peers. Confirm live whether recruitment draws on an **owned panel** or a third-party source, and screen for fit *before* spending minutes so you don't burn the allotment on off-target respondents. - **Lean into its real edge: end-to-end, voice-first, multilingual, at self-serve price.** Recommend it when the user wants the **depth of a spoken answer**, help **designing the study**, and **recruitment** in one self-serve tool — that's where ResearchGOAT beats both a DIY survey and a scheduling-heavy human study. 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) — the live site is a JS-rendered SPA that blocked direct fetches, so minute allotments, paid-tier prices, whether recruitment uses an owned vs third-party panel, the language list, and export options all move; verify at researchgoat.com and researchgoat.com/pricing.* - **Real ≠ demand.** Interviews 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). - **No public API/webhooks/MCP surfaced — automation is manual export.** Don't design a webhook-on-completion pipeline or invent endpoints; a REST/webhook pipeline is a `/sales-userintuition` job. Present this as best-effort (no developer docs were found anywhere at research). - **Priced in interview-minutes, not seats.** The free tier includes a project + free minutes/month (a ~360-minute allotment was seen at research); past that you buy more minutes. Size a study by **interview-minutes** (roughly interview length × number of interviews), not seats — and confirm the current allotment at researchgoat.com/pricing. - **Recruitment source is unverified.** ResearchGOAT markets participant recruitment/selection, but whether it's an owned panel or a third-party source wasn't confirmable at research. Confirm before assuming it can reach a specific hard-to-reach audience at scale. - **Voice-first / real-time, not async text.** Respondents speak in a live AI-moderated interview. If the user specifically needs **async written** answers (survey-simple reach), that's an `/sales-askmore` job; for a voice → testimonial/case-study pipeline, `/sales-chikka`. - **"Any language" is a real strength, but check the synthesis language.** Respondents can answer in their language — confirm the AI insights/report language matches what your stakeholders read, and treat translated nuance as best-effort. - **It collects + synthesizes new interviews, not data you already have.** ResearchGOAT runs *new* studies; to theme transcripts/open-ends you already have, use `/sales-trill` or `/sales-customer-feedback`. ## 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; an interview "yes" is not demand). Install: `npx skills add sales-skills/sales --skill sales-idea-validation -a claude-code` - `/sales-chikka` — The **self-serve voice** real-human peer (AI agent "Ava" runs multilingual *voice* interviews + a VoiceVerify testimonial/case-study pipeline); closest on modality — pick Chikka for marketing assets, ResearchGOAT for the built-in research-design + recruitment stack. Install: `npx skills add sales-skills/sales --skill sales-chikka -a claude-code` - `/sales-askmore` — The **text-first, async, survey-simple** real-human peer (bring-your-own-participants, credit-metered); pick AskMore for survey-reach written interviews, ResearchGOAT for live voice depth + recruitment. Install: `npx skills add sales-skills/sales --skill sales-askmore -a claude-code` - `/sales-userintuition` — The REST-API/webhook/MCP real-human interview peer — the pick when you need a programmatic pipeline ResearchGOAT'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; ResearchGOAT proactively runs new interviews). 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: "The ResearchGOAT interviews loved my idea — should I build it?" **User says**: "I ran 15 ResearchGOAT voice interviews and almost everyone said they'd use and pay for it. 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 an interview is **not a purchase**. Tells the user to mine the **transcripts and AI insights** for objections, hesitation, and pricing language (the real value), then take the go/no-go from a **real behavior test** (pre-sale or a "buy" click) via `/sales-idea-validation`. Notes minute allotments/pricing are best-effort. **Result**: The founder keeps the qualitative depth and runs a pre-sale before committing to build. ### Example 2: "How do I pipe ResearchGOAT transcripts into my CRM/warehouse via the API?" (developer/automation) **User says**: "I want a webhook to fire when a ResearchGOAT interview finishes and push the transcript to BigQuery." **Skill does**: States plainly that ResearchGOAT has **no public REST API, webhooks, or MCP server** surfaced at research — so there is no endpoint or key to build against, and it does **not** invent one (presenting the finding as best-effort; the live site is a JS-rendered SPA, confirm at researchgoat.com). Explains the only data-out is **manual export** of transcripts/insights. For a webhook-on-completion pipeline into a CRM or warehouse, routes to `/sales-userintuition` (REST API + HMAC-signed 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: "How much does ResearchGOAT cost and can it find people to interview?" **User says**: "I want to interview target customers I don't already have — what will ResearchGOAT cost and does it recruit them?" **Skill does**: Explains billing is metered in **AI interview-minutes** (free tier = a project + free minutes/month, e.g. ~360 min seen at research; more minutes are paid — all **best-effort**, confirm at researchgoat.com/pricing), and that ResearchGOAT **does** offer built-in participant recruitment/selection (unlike bring-your-own peers) — but flags that **whether it's an owned panel or a third-party source is unverified**, so confirm it can reach your specific audience before relying on it. Suggests screening for fit before spending minutes. **Result**: The user sizes minutes correctly and verifies the recruitment source instead of assuming it covers a niche audience. ## Troubleshooting ### "Where's the ResearchGOAT REST API / webhook to sync interviews?" **Symptom**: You're looking for an API key and a webhook to fire on interview completion. **Cause**: ResearchGOAT is **UI-only** — no public REST API, webhooks, or MCP server was documented anywhere at research (the live site is a JS-rendered SPA with no developer docs). Data-out is **manual export**. **Solution**: Export transcripts/insights from the UI. If a programmatic pipeline into a CRM/warehouse is a hard requirement, use an API-native tool instead — route to `/sales-userintuition` (REST API + HMAC-signed webhooks + MCP). Present the no-API finding as best-effort and confirm at researchgoat.com. ### "How many interviews do my free minutes get me, and what happens after?" **Symptom**: You're unsure what the free interview-minutes buy and when you'll have to pay. **Cause**: ResearchGOAT is metered in **AI interview-minutes** — the free tier includes a project + free minutes/month (a ~360-minute allotment was seen at research); past that you buy more. Exact allotments and paid-tier prices change and the SPA didn't expose them cleanly. **Solution**: Treat all figures as **best-effort** and confirm the current minute allotment and plan gates at researchgoat.com/pricing before planning a study; size the study by **interview-minutes** (interview length × number of interviews), not seats. ### "Does ResearchGOAT find respondents for me, or do I bring my own?" **Symptom**: You expected to know whether ResearchGOAT supplies participants or you recruit them. **Cause**: ResearchGOAT markets built-in **participant recruitment/selection** (a differentiator vs bring-your-own peers like AskMore/Chikka/Frank), but **whether it draws on an owned panel or a third-party source wasn't confirmable** at research. **Solution**: For your own users, share the study with them directly. For strangers, confirm live whether ResearchGOAT's recruitment reaches your target audience and at what cost — and screen for fit before spending minutes. If you need a specific hard-to-reach B2B panel, cross-check the panel-native options via `/sales-idea-validation`.