---
name: sales-frank
description: "Frank (hifrank.ai) platform help — an AI-moderated customer-research tool (by Prelaunch.com) that interviews your REAL customers, not synthetic personas: an AI voice/chat interviewer that adapts follow-ups and turns conversations into transcripts, themes, sentiment, quotes, and video reels across 30+ languages. Bring-your-own-customers only — no third-party panel; you share an interview link by email, chat, or in-product journey, with optional incentives. Self-serve, voice-minute-metered plans; UI-only — no public API, webhooks, Zapier, or MCP (API is Enterprise-only). Use when setting up a Frank study or discussion guide, running churn / discovery / concept-testing interviews with your own users, picking a plan by voice-minute allowance, or getting data out with no API. Do NOT use for comparing research tools or the validate-before-build method (use /sales-idea-validation), an API/webhook/MCP-native pipeline (use /sales-userintuition), or reaching strangers on a recruited panel (use /sales-respondent)."
argument-hint: "[describe what you need help with in Frank]"
license: MIT
version: 1.0.0
tags: [sales, idea-validation, platform]
---

# Frank Platform Help

Frank (hifrank.ai, built by **Prelaunch.com**) is an **AI-moderated customer researcher** that interviews
your **real customers** — an AI **voice** (and **chat**) interviewer that adapts its follow-ups, runs many
conversations in parallel 24/7, and turns them overnight into **transcripts, themes, sentiment, key quotes,
and video reels** across **30+ languages**. *"Talk to hundreds of real customers while you sleep."*

Its defining trait in the AI-moderated-interview cluster is **bring-your-own-customers (BYOC) only — it has
no third-party participant panel**. You reach the people who already use (or are considering) your product
by **sharing an interview link** — in an email, a chat, or as a step in the user's journey inside your
product — with an **optional incentive** (an Amazon gift card, a discount, or nothing). That makes it the
pick when you already have customers/prospects to talk to (churn, discovery, concept/feature testing,
engagement), and the *wrong* pick when you need to reach strangers you don't already have.

**Two things to say almost every time:**
- **It's real humans, but a stated "I'd pay" is still not a purchase.** A real interview beats a synthetic
  "yes" (genuine reasoning, objections, language) — but the willingness-to-pay go/no-go belongs to a
  **real behavior test** (pre-sale, smoke test), not a transcript. Route that to `/sales-idea-validation`.
- **Frank is UI-only for self-serve users.** There is **no public API, no webhooks, no Zapier, no MCP** — an
  "API integration" is listed only on the **Enterprise** tier and is undocumented. Any "pipe transcripts
  into my CRM/warehouse" ask is **manual export**, not an integration. If the user needs an API-native
  interview pipeline, the right tool is `/sales-userintuition`, not Frank.

## 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 Frank?**
   - A) **Set up a study** — write the objective/discussion guide, pick voice vs chat, set incentive
   - B) **Distribute** — get the interview link in front of your own customers (email, chat, in-product)
   - C) **Read results** — themes, sentiment, quotes, video reels — or decide whether to trust them
   - D) **Get data out** — export transcripts/reels for a deck, CRM, or warehouse (no API — manual)
   - E) **Choose a plan** — Free vs Starter vs Growth vs Business by voice-minute allowance
   - F) **Compare** — Frank vs User Intuition / Strella / Listen Labs / Voicepanel for your use case
2. **Do you already have customers/prospects to interview?** Frank has **no panel** — if you need to reach
   strangers, it's the wrong tool (route to a panel-based peer or a recruit marketplace in Step 2).

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}` |
| An **API / webhook / MCP-native** interview pipeline (Frank has none for self-serve) | `/sales-userintuition {question}` |
| **Reaching strangers** on a recruited panel (Frank is BYOC-only, no panel) | `/sales-respondent` or `/sales-idea-validation` `{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/review feedback (post-launch, not new interviews) | `/sales-customer-feedback {question}` |
| A **synthetic-persona** peer (AI personas instead of real people) | `/sales-syntheticusers` or `/sales-ditto` `{question}` |

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

Otherwise, answer Frank-specific questions using Step 3.

## Step 3 — Frank platform reference

**Read `references/platform-guide.md`** for the full reference — the module/automation-surface table
(what's exportable vs UI-only), best-effort pricing and the voice-minute/credit model, the
Study → Interview → Participant → Insight data model, BYOC distribution, and the no-API data-out playbook.
Frank has **no public API** for self-serve users, so there is no API-reference file.

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 Frank
  interviews **real humans** (a big step up from synthetic personas — genuine reasoning, objections,
  language), but a stated "I'd pay" in an interview is **not observed demand**. Keep the *why/objections/
  language* and take the go/no-go from a **real behavior test** (smoke-test click, pre-sale) — route that
  to `/sales-idea-validation`. When they interpret results, point them to the **verbatim quotes and video
  reels under each theme** (the objections, hesitation, and pricing language) — not just the top-line
  sentiment/theme summary, which is an index, not the finding.
- **Lead with BYOC: Frank has no panel.** When the user asks who Frank interviews, state that it is
  **bring-your-own-customers only** — you distribute a **share link** to your own customers/prospects
  (email, chat, or an in-product journey step), so it fits churn/discovery/concept-testing with an audience
  you *already have*. If they need to reach **strangers**, say so plainly and route to a panel-based peer
  (`/sales-userintuition`, `/sales-listenlabs`) or a recruit marketplace (`/sales-respondent`).
- **Flag it as UI-only when any automation/export comes up.** Frank has **no public API, webhooks, Zapier,
  or MCP** for self-serve plans (an "API integration" appears only on the **Enterprise** tier and is
  undocumented — verify against current docs). "Sync transcripts to HubSpot/Snowflake" is a **manual**
  export/copy job. If the user needs a programmatic pipeline, tell them so and route to `/sales-userintuition`.
- **Recommend a plan by voice-minute allowance, not seats.** Frank meters **voice minutes** (roughly
  ~15 min/interview; ~10 credits ≈ 1 voice minute or ~10 chat messages), so size the plan by how many
  interviews/month they'll run, and note **chat conversations are cheaper than voice**. Present every
  price as **best-effort** and point to **hifrank.ai/pricing** to confirm.
- **Keep the discussion guide tight; let the Research Agent draft it.** Setup is fast (share your site +
  goal, the AI drafts an outline in ~2 min). Give it a **sharp objective + a few core questions** and let
  the adaptive moderator probe — a thin brief caps depth, but an over-long guide fatigues participants.
- **Set the incentive to the ask.** The incentive is **optional** (Amazon gift card, purchase discount, or
  none) — use a reward for cold/low-motivation audiences and skip it for engaged customers; it's a
  response-rate lever, not a quality guarantee.

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) — Frank is new (launched ~2026-04) and its modality mix, pricing, and
(absent) API surface move fast; verify at hifrank.ai.*

- **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 panel — BYOC only.** Frank does **not** recruit strangers; you must already have customers/prospects
  and distribute a share link. For strangers, use a panel-based peer or a recruit marketplace.
- **No API, no webhooks, no Zapier, no MCP (self-serve).** Frank is UI-only; "API integration" is an
  **Enterprise**-only, undocumented line item. The only data-out is manual export (transcripts, reels).
  Don't design a live integration around it — route pipeline needs to `/sales-userintuition`.
- **Voice is the live modality; video + WhatsApp are newer/coming.** Marketing lists voice, video, and
  WhatsApp, but voice (and chat) are what's shipped — treat video/WhatsApp as best-effort until confirmed.
- **Plans meter voice minutes, and interviews have a max length.** Free caps interview length short; paid
  tiers raise it. Model cost by minutes, not by interview count, and confirm the current caps on site.
- **Pricing is published but moves.** Monthly vs annual differ a lot (annual is far cheaper per month) —
  treat any figure as best-effort and confirm at hifrank.ai/pricing.
- **It's built by Prelaunch.com.** Frank is a distinct product from Prelaunch's concept-testing/pre-order
  platform — don't conflate their feature sets or pricing.

## Related skills

- `/sales-idea-validation` — The tool-agnostic validate-before-building method + the full research/persona/validator tool landscape (use this to actually 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-userintuition` — The API/webhook/MCP-native real-human interview peer — the pick when you need a programmatic pipeline Frank can't offer for self-serve (deepest developer surface in this cluster; also has a big panel Frank lacks). Install: `npx skills add sales-skills/sales --skill sales-userintuition -a claude-code`
- `/sales-strella` — The other **UI-only** real-human AI-moderated interview peer (deterministic scripted flows, 3M+ panel via User Interviews); pick Strella when you want a panel or scripted repeatability, Frank when you're interviewing your own customers self-serve. Install: `npx skills add sales-skills/sales --skill sales-strella -a claude-code`
- `/sales-listenlabs` — The enterprise/consultative real-human peer with a 30M+ panel, REST API v2 + OAuth MCP; pick it when you need a panel of strangers or an API pipeline. Install: `npx skills add sales-skills/sales --skill sales-listenlabs -a claude-code`
- `/sales-chikka` — The closest analog — another **self-serve, UI-only** AI voice-interview tool with a free tier; its twist is a **voice → marketing-asset** pipeline (VoiceVerify testimonials/case studies). Pick by pricing model and whether you want testimonials out of the same interview. Install: `npx skills add sales-skills/sales --skill sales-chikka -a claude-code`
- `/sales-respondent` — Participant-recruitment marketplace — recruits, screens, and pays strangers from a 4M+ B2B/professional panel; the pick when Frank's BYOC model can't reach the audience you need. Install: `npx skills add sales-skills/sales --skill sales-respondent -a claude-code`
- `/sales-customer-feedback` — Real-customer NPS/CSAT/VoC strategy across tools (use to analyze *existing* feedback; Frank proactively runs new interviews with your own customers). Install: `npx skills add sales-skills/sales --skill sales-customer-feedback -a claude-code`
- `/sales-funnel` — Build the smoke-test / fake-door landing page that turns an interview 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: "The interviews said they'd pay — should I build it?"
**User says**: "I ran 30 Frank interviews with my waitlist and most said they'd pay. Green light?"
**Skill does**: Credits the signal as **real** (actual humans, genuine reasoning — far better than a
synthetic tool), then draws the line: a stated "I'd pay" is **not a purchase**. Tells the user to open the
**verbatims and video reels** and mine objections, hesitation, and pricing language, then take the go/no-go
from a **real behavior test** (a pre-sale or a "buy" click) via `/sales-idea-validation`. Flags pricing as
best-effort and points to hifrank.ai/pricing.
**Result**: The founder keeps the qualitative depth and runs a pre-sale before committing to the build.

### Example 2: "How do I get Frank transcripts into HubSpot automatically?" (developer/automation)
**User says**: "I want every completed Frank interview transcript to land on the HubSpot contact."
**Skill does**: States plainly that **Frank is UI-only for self-serve — no public API, webhooks, Zapier, or
MCP** (an "API integration" is an Enterprise-only, undocumented line item), so there's no automated path;
the only data-out is a **manual export** of transcripts/reels. If a live pipeline is a hard requirement,
routes to `/sales-userintuition` (REST API + HMAC webhooks + MCP) as the API-native alternative, noting the
trade-off (Frank's edge is fast, cheap self-serve interviews with your own customers).
**Result**: The user stops hunting for an API that doesn't exist and either exports manually or switches
tools for the pipeline.

### Example 3: "Which plan do I need, and how do I reach people to interview?"
**User says**: "I want ~25 customer interviews a month. Which Frank plan, and where do the participants come from?"
**Skill does**: Explains Frank is **BYOC — no panel**: you share an **interview link** with your own
customers/prospects (email, chat, or in-product journey), with an optional incentive. Sizes the plan by
**voice-minute allowance** (~15 min/interview → ~25 interviews needs a mid tier's minute pool; chat is
cheaper than voice), flags monthly-vs-annual pricing as best-effort → hifrank.ai/pricing, and notes that if
they need to reach **strangers** they don't already have, Frank can't — route to `/sales-respondent` or a
panel-based peer.
**Result**: The user picks a plan by minutes and understands they must supply their own audience.

## Troubleshooting

### "Who does Frank interview — where's the panel?"
**Symptom**: The user expects Frank to recruit participants like a panel tool.
**Cause**: Frank is **bring-your-own-customers only** — it has **no third-party panel**. It interviews the
people you already have a way to reach.
**Solution**: Distribute the **interview link** to your own customers/prospects (email, chat, or an
in-product journey step), with an optional incentive (Amazon gift card / discount / none). If you need to
reach **strangers**, Frank is the wrong tool — recruit via `/sales-respondent` or use a panel-based peer
(`/sales-userintuition`, `/sales-listenlabs`).

### "How do I automate exports / connect Frank to my stack?"
**Symptom**: You want transcripts, reels, or insights flowing into a CRM, warehouse, or Slack.
**Cause**: Frank has **no public API, webhooks, Zapier, or MCP** for self-serve plans — it's UI-only (an
"API integration" appears only on the Enterprise tier and is undocumented; verify against current docs).
**Solution**: Use the built-in **manual export** (transcripts / video reels / summaries) for decks and
ad-hoc handoff. If an automated, programmatic pipeline is a requirement, use an API-native interview tool
instead — route to `/sales-userintuition` (REST API + HMAC-signed webhooks + MCP server).

### "Which plan, and why did I run out of interviews so fast?"
**Symptom**: The user is unsure which tier to buy, or hit a limit sooner than expected.
**Cause**: Frank meters **voice minutes** (roughly ~15 min/interview; ~10 credits ≈ 1 voice minute or
~10 chat messages) and caps interview length by tier — so cost tracks minutes, not interview count, and a
few long voice interviews burn a small plan.
**Solution**: Size the plan by **monthly voice-minute allowance** for your expected interview count, prefer
**chat** where voice depth isn't needed (it's cheaper), and watch the per-tier **max interview length**.
Treat every figure as best-effort and confirm at hifrank.ai/pricing.