---
name: sales-askmore
description: "AskMore (askmore.ai) platform help — a self-serve AI-moderated interview tool that runs asynchronous text/chat interviews via a share link: the AI adapts to each answer, follows up, and digs deeper (the survey-to-interview bridge), works in any language with auto-translation, and returns shareable reports with full transcripts. Bring your own participants (no built-in panel); pay-as-you-go credits with free credits to start. Use when setting up AskMore interviews for user/customer/market research, sizing its credit pricing and free credits, running multilingual interviews, sharing a participation link to your own audience, getting data out when there is no public API, or choosing AskMore vs Chikka / Frank / User Intuition. Do NOT use for the validate-before-building method (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 AskMore]"
license: MIT
version: 1.0.0
tags: [sales, pre-launch, platform]
---

# AskMore Platform Help

AskMore (askmore.ai) runs **AI-moderated interviews on real people** — you set an objective, and its AI
interviewer runs **asynchronous, mostly text/chat interviews via a share link**: it adapts to each answer,
**follows up, and digs deeper** the way a human researcher would, then delivers **shareable reports**
(key findings + full transcripts). It markets itself as the middle ground **between a survey and an
interview** — "as easy as sending a survey link," but with an AI that probes instead of a static form. It
works in **any language** (auto-translates questions, answers, and the report), so a respondent can answer
in their language and you read the synthesis in yours.

Its niche in the real-human AI-moderated-interview cluster (User Intuition, Strella, Voicepanel, Frank,
Chikka, Listen Labs) is **three things**:
- **The survey↔interview bridge, text-first.** The lowest-friction, most survey-like format in the cluster
  — async, written answers, no scheduling, no call — vs the voice-first peers (Chikka, Frank, Voicepanel).
  It's the pick when you want interview *depth* at survey *reach and simplicity*.
- **Bring-your-own-participants, self-serve, pay-as-you-go.** **No built-in panel** — you share a link with
  your own audience/list (like Frank/Chikka). Billing is **credits** (free credits to start, then credit
  packs), so a solo maker can sign up and run interviews today — the opposite of sales-gated peers.
- **Any-language interviews + auto-translation** built in, so it fits international/multi-market research.

**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.** Distribution is a **share link**; data-out
  is **manual export** of transcripts/reports. "Call the AskMore 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 AskMore?**
   - A) **Run new interviews** — set an objective + questions, share the participation link, let the AI interview
   - B) **Recruit / reach participants** — AskMore has **no panel**; you bring your own audience (email list, in-app, community)
   - C) **Read / export results** — reports, key findings, full transcripts (there is no API/webhooks)
   - D) **Pricing / credits** — free credits, credit packs, what a credit buys
   - E) **Choose** — AskMore vs Chikka / Frank / User Intuition / Strella / Voicepanel
   - F) **Multilingual research** — interview in any language + auto-translation
2. **Is this discovery (strangers) or feedback from your own users/customers?** AskMore has no panel, so for
   strangers you must recruit them elsewhere first — that changes the plan.

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 (AskMore 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 **voice-first** AI interviewer, or turning interviews into testimonials/case studies | `/sales-chikka {question}` |

When routing, give the exact command: "This is a {domain} question — run: `/sales-idea-validation {original question}`"

Otherwise, answer AskMore-specific questions using Step 3.

## Step 3 — AskMore reference

**Read `references/platform-guide.md`** for the full reference — the module/automation-surface table
(what's UI-only vs export), best-effort credit pricing and free-credit limits, the
Project → Interview → Report data model, the share-link distribution workflow, the any-language/translation
workflow, and how the AI's adaptive follow-ups work. **Read `references/askmore-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
  AskMore 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 key findings** for objections and pricing language rather than trusting the
  top-line summary 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 AskMore has **no public REST API, webhooks, or MCP server** — distribution is a
  **share link** and data-out is **manual export** of transcripts/reports. 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** — confirm at askmore.ai.
- **Set expectations on recruiting: there is no panel.** AskMore does **not** supply respondents — you
  bring your own audience and share the link. It's the right tool when you *already have* people to talk to
  (your users, list, or community) and the **wrong tool for reaching strangers at scale**; for a panel,
  point to a panel-native peer via `/sales-idea-validation`.
- **Size it by credits, not seats, and call pricing best-effort.** Billing is **pay-as-you-go credits**
  (free credits to start, then credit packs) — a credit is roughly *per completed interview/response*.
  Present every figure as **best-effort** and point to **askmore.ai/pricing** to confirm the current
  credit rate, since the live site changes.
- **Lean into its real edge: survey-simplicity with interview depth, in any language.** Recommend it when
  the user wants **async, written, adaptive** interviews their audience can answer on their own time, in
  **their own language** — that's where AskMore beats both a static survey and a scheduling-heavy voice tool.

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 was bot-blocked at research, so credit pricing, free-credit
limits, the language list, whether a voice mode exists, and the exact export options all move; verify at
askmore.ai and askmore.ai/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 API was documented anywhere at research).
- **No built-in panel.** AskMore doesn't recruit respondents — you bring your own audience via a share link.
  For strangers at scale, recruit them elsewhere first (see `/sales-idea-validation`).
- **Credit pricing, not subscription seats.** Free credits get you started; past that you buy credit packs
  (roughly per interview/response). Historical aggregator figures (e.g. a small pack for a low double-digit
  price) are stale — confirm the current rate at askmore.ai/pricing.
- **It's text-first / async, not a live voice call.** Respondents answer in writing on their own time.
  If the user specifically needs *voice* depth or a testimonial pipeline, that's a `/sales-chikka` job.
- **"Any language" is a real strength, but check the report language.** Respondents can answer in their
  language and it auto-translates — confirm the synthesis/report language matches what your stakeholders read.
- **It collects, it doesn't synthesize what you already have.** AskMore runs *new* interviews; 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 **voice-first**, self-serve real-human peer (AI agent "Ava" runs multilingual *voice* interviews + a VoiceVerify testimonial/case-study pipeline); pick Chikka for voice depth and marketing assets, AskMore for async text simplicity. Install: `npx skills add sales-skills/sales --skill sales-chikka -a claude-code`
- `/sales-frank` — The other **bring-your-own-customers, self-serve, UI-only** peer (Prelaunch.com; voice + chat, voice-minute-metered); closest analog to AskMore's BYO-participant model — pick by modality and pricing shape. Install: `npx skills add sales-skills/sales --skill sales-frank -a claude-code`
- `/sales-researchgoat` — The **end-to-end, voice-first** self-serve peer (researchgoat.com) that bundles **AI research design + a screener + built-in participant recruitment + AI synthesis** around live voice interviews; pick ResearchGOAT for voice depth + a design/recruit stack, AskMore for async written survey-reach. Install: `npx skills add sales-skills/sales --skill sales-researchgoat -a claude-code`
- `/sales-userintuition` — The REST-API/webhook/MCP real-human interview peer — the pick when you need a programmatic pipeline AskMore'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; AskMore 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 AskMore interviews loved my idea — should I build it?"
**User says**: "I sent an AskMore interview link to 20 people on my list 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 key findings** 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 credit pricing/limits 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 AskMore transcripts into my CRM/warehouse via the API?" (developer/automation)
**User says**: "I want a webhook to fire when an AskMore interview finishes and push the transcript to BigQuery."
**Skill does**: States plainly that AskMore 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, confirm at askmore.ai). Explains distribution is a **share link** and the only
data-out is **manual export** of transcripts/reports. 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 AskMore cost and how do I reach people who aren't on my list?"
**User says**: "I want to interview target customers I don't already have contact with — what will AskMore cost me?"
**Skill does**: Explains AskMore is **pay-as-you-go credits** (free credits to start, then credit packs,
roughly per completed interview — all **best-effort**, confirm at askmore.ai/pricing), and flags the key
constraint: **AskMore has no built-in panel**, so it can't reach strangers — you share a link with an
audience you already have. To recruit unknown target customers, routes to `/sales-idea-validation` for the
panel-native tool map, then use AskMore (or a voice peer) to run the interviews.
**Result**: The user sizes credits correctly and recruits participants the right way instead of expecting AskMore to supply them.

## Troubleshooting

### "Where's the AskMore REST API / webhook to sync interviews?"
**Symptom**: You're looking for an API key and a webhook to fire on interview completion.
**Cause**: AskMore is **UI-only** — no public REST API, webhooks, or MCP server was documented anywhere at research. Distribution is a **share link**; data-out is **manual export**.
**Solution**: Export transcripts/reports 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 askmore.ai.

### "I don't have people to interview — does AskMore find respondents for me?"
**Symptom**: You expected AskMore to supply a panel of target customers.
**Cause**: AskMore has **no built-in panel** — it's bring-your-own-participants. You share the interview link with an audience you already have (list, in-app, community).
**Solution**: Recruit participants first (a panel marketplace or your own audience), then share the AskMore link. For the panel-native tool map, route to `/sales-idea-validation`.

### "How many interviews do my free credits get me, and what happens after?"
**Symptom**: You're unsure what a credit buys and when you'll have to pay.
**Cause**: AskMore is **pay-as-you-go credits** — free credits to start, then credit packs; a credit is roughly per completed interview/response. Exact rates change and the live site was bot-blocked at research.
**Solution**: Treat all credit figures as **best-effort** and confirm the current rate and free-credit allotment at askmore.ai/pricing before planning a study; size the study by number of completed interviews, not seats.