---
name: sales-notably
description: "Notably (notably.ai) platform help — an AI-forward qualitative research repository and synthesis tool: import interview transcripts, notes, survey open-ends, and audio/video, then auto-transcribe, AI-tag, cluster by theme and sentiment, and generate insight summaries on a split-screen data-driven canvas, stored in a searchable cross-project repository with template-driven analysis and shareable highlight clips. Use when synthesizing user interviews into themes, analyzing open-ended survey responses, building a searchable research repository, tags disappearing when switching sections, choosing between Notably and Dovetail/Condens/Marvin, or exporting insights when there is no API. Do NOT use for choosing a qualitative-analysis tool across the market (use /sales-customer-feedback) or recruiting and running studies end-to-end (use /sales-great-question)."
argument-hint: "[describe what you need help with in Notably]"
license: MIT
version: 1.0.0
tags: [sales, customer-cx, platform]
---

# Notably Platform Help

Notably (notably.ai) is an **AI-forward qualitative research repository + synthesis tool** — the analysis end of the research stack, a peer of **Dovetail, Condens, Marvin (HeyMarvin), and Aurelius**. You already *have* the data (interview transcripts, session notes, open-ended survey responses, audio/video, whitepapers); Notably ingests it, **auto-transcribes**, **AI-tags and clusters by theme/sentiment**, and **generates insight summaries** on a split-screen **data-driven canvas** that keeps the raw data next to the insight, then stores everything in a **searchable cross-project repository**. A **template** library (debrief → analysis → insights) guides each stage, and findings ship as **insights** (with AI imagery) and **highlight clips** you can share with free viewer seats.

**Two things to say almost every time:**
- **Notably ANALYZES data — it does not recruit, schedule, or generate it.** It has no participant panel and runs no studies. If the user needs to *find and talk to* users end-to-end (recruit → run → repository), that's the all-in-one research-ops job — route to `/sales-great-question`. Notably starts *after* you have transcripts/notes.
- **Notably has NO public API, webhooks, MCP server, or documented Zapier.** The only integrations are **Miro** and **FigJam** (import/sync from a whiteboard), plus imports from surveys/notes/audio/video; data-out is **manual export**. A "pipe insights into my CRM/warehouse" ask is a manual/scheduled export job, not an endpoint call — a documented REST/webhook pipeline belongs 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 Notably?**
   - A) **Import & transcribe** — bring in transcripts/notes/audio/video/survey open-ends
   - B) **Analyze** — AI tagging, theme/sentiment clustering, the data-driven canvas, templates
   - C) **Synthesize & share** — insight summaries, highlight clips, viewer sharing
   - D) **Repository** — cross-project search, organizing data across studies
   - E) **Get data out** — **manual export** (no API); Miro/FigJam sync
   - F) **Choose a plan** — Free (limited) vs Pro vs Team vs Enterprise
2. **Do you already have the raw research data, or do you still need to recruit/run the study?** The second is a research-ops question — flag it in Step 2 and route to `/sales-great-question`.

Skip-ahead: if the prompt already names the task or the question is specific, go to Step 3.

## Step 2 — Route or answer directly

| If the user's question is about… | Route to |
|---|---|
| Choosing a qualitative-analysis / research-repository tool **across the market**, or VoC/feedback strategy | `/sales-customer-feedback {question}` |
| **Recruiting + running** studies end-to-end (panel, scheduling, all methods) then storing them | `/sales-great-question {question}` |
| Validating whether to **build** an idea (the evidence ladder, AI scores, smoke tests) | `/sales-idea-validation {question}` |
| A documented **API / webhook-native** research pipeline (Notably has none) | `/sales-userintuition {question}` |
| Running **AI-moderated interviews** to *generate* the data first | `/sales-great-question` or `/sales-idea-validation` `{question}` |

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

Otherwise, answer Notably-specific questions using Step 3.

## Step 3 — Notably platform reference

**Read `references/platform-guide.md`** for the full reference — the module/automation-surface table (what's UI-only vs export-accessible), best-effort pricing and plan gates (Free vs Pro vs Team vs Enterprise, viewer seats), the Project → data → tag → theme → insight data model, the import sources and Miro/FigJam sync, and the no-API data-out playbook. Notably has **no REST API**, so there is no API-reference file.

Answer using only the relevant section — don't dump the full reference.

## Step 4 — Actionable guidance

- **In every response, verify AI output against the source verbatim.** Notably's AI tagging, theme clustering, and insight summaries are a **starting draft, not a finding** — tell the user to click into the **verbatims/quotes underneath each theme** and confirm the AI read the data correctly before presenting an insight. Say this even when the user only asked how to speed up synthesis: AI acceleration is the value, but an unverified AI theme can misrepresent what a participant actually said.
- **Draw the analysis-only boundary head-on whenever recruiting/data-collection comes up.** Notably does **not** recruit participants, schedule sessions, or run interviews — it **only analyzes data you already have**. If the user has no transcripts/notes yet, say so plainly and route the recruit-and-run job to `/sales-great-question` (all-in-one research-ops) or the interview-generation job to `/sales-idea-validation`. Notably is the wrong first pick when there's no data yet.
- **Flag it as export-only when any automation/API/pipeline comes up.** Notably has **no public REST API, webhooks, MCP server, or documented Zapier** (verify — it may change). The only data-out is **manual export**, and the only live integrations are **Miro** and **FigJam** (import/sync, not a data-out pipeline). "Sync insights to HubSpot/Snowflake on a schedule" is a manual/scripted export job, not REST — if a documented pipeline is required, route to `/sales-userintuition`.
- **Warn about the tags-disappearing bug and save often.** A recurring, reproducible complaint is that **tags/highlights can vanish when moving between sections** of the canvas. Tell the user to refresh to confirm whether a tag was truly lost vs a render glitch, apply tags in small batches, and re-check the tag/theme view after navigating — don't assume a single un-verified pass captured everything.
- **Present pricing as best-effort and match the plan to the job.** Best-effort tiers: **Free** (limited) → **Pro ~$21/user/mo** → **Team ~$200/user/mo** → **Enterprise** (custom); **viewer/observer seats are free** for sharing insights externally. Frame the choice around *how many researchers* need to tag/analyze (paid seats) vs *how many stakeholders* just need to read insights (free viewers) — point to notably.ai/pricing to confirm.
- **Match Notably to the moment in the workflow, and walk the synthesis steps.** Recommend it for the **synthesis** step — turning a pile of transcripts/notes/open-ends into themes, insights, and a searchable repository. When the user asks how to run that synthesis, spell out the workflow: **import/transcribe** the data into a **Project** → apply a **template** (debrief → analysis → insights) → let AI **tag and cluster by theme/sentiment** on the **canvas** → generate **insight summaries** and **highlight clips** to share via free viewer seats. Name its AI-forward edge over Dovetail/Condens (auto theme extraction + insight summaries) *and* its limit (analysis-only, thin automation); for a lighter/cheaper repository, note **Aurelius**; for the enterprise repository incumbent, **Dovetail**.

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, plan gates, the tags-disappearing bug, and the export-only surface; the live site was unreachable at research (SSL/bot-block) so specifics lean on third-party sources — verify at notably.ai.*

- **Analysis-only — no recruiting, scheduling, or data generation.** Notably starts *after* you have data. No participant panel, no studies. For recruit → run → repository, use `/sales-great-question`.
- **No REST API, no webhooks, no MCP, no Zapier.** The only integrations are **Miro** and **FigJam**; the only data-out is **manual export**. Don't design a live pipeline around it — route pipeline needs to `/sales-userintuition`.
- **AI insights are a draft, not a finding.** Auto-tags, theme clusters, and summaries can misread nuance — always confirm against the underlying verbatims before presenting an insight.
- **Tags/highlights can disappear when switching sections.** A reproducible bug — tag in small batches, refresh to confirm, and re-check the tag view after navigating.
- **Free tier is a real cap; Team is a steep jump.** Best-effort Free (limited) → Pro ~$21/user/mo → Team ~$200/user/mo → Enterprise (custom). Use free **viewer seats** for read-only stakeholders instead of paying for a full seat.

## Related skills

- `/sales-customer-feedback` — The tool-agnostic qualitative-analysis / VoC strategy and the full research-repository landscape (use this to *choose* an analysis tool, or for NPS/CSAT/survey strategy). Install: `npx skills add sales-skills/sales --skill sales-customer-feedback -a claude-code`
- `/sales-great-question` — The all-in-one **research-ops** peer that *recruits and runs* studies (panel + scheduling + every method) then stores them in a repository — the pick when you have no data yet. Install: `npx skills add sales-skills/sales --skill sales-great-question -a claude-code`
- `/sales-idea-validation` — The validate-before-building method + the full research/validator landscape; where a research-repository tool fits among validators, synthetic research, and interview tools. Install: `npx skills add sales-skills/sales --skill sales-idea-validation -a claude-code`
- `/sales-userintuition` — The API/webhook/MCP-native research peer — the pick when you need a documented programmatic pipeline Notably can't offer. Install: `npx skills add sales-skills/sales --skill sales-userintuition -a claude-code`
- `/sales-trill` — The **free, public-beta** synthesis peer — same analysis job (interview transcripts → AI insights + theme categorization → Notion-like report) but lightweight and free (no paid tiers); also no API. The budget alternative when Notably's price or feature depth isn't needed. Install: `npx skills add sales-skills/sales --skill sales-trill -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: "I ran 12 user interviews — how do I turn the transcripts into themes fast?"
**User says**: "I have a dozen interview recordings and messy notes. I want themes and a summary I can share, not to code every line by hand."
**Skill does**: Recommends importing the recordings (auto-transcription) and notes into a **Project**, running a **template** (debrief → analysis → insights), letting the AI **tag and cluster by theme/sentiment** on the **data-driven canvas**, then generating an **insight summary** + **highlight clips** to share via free **viewer seats**. Insists the user **click into the verbatims under each theme** to confirm the AI read them correctly before presenting, and warns to **tag in small batches / refresh** because tags can drop when switching sections.
**Result**: The user gets a verified, shareable set of themes and insights in a fraction of manual-coding time.

### Example 2: "Can I pull Notably insights into our warehouse / automate the export?" (developer/automation)
**User says**: "I want our research insights flowing into Snowflake automatically instead of clicking export every week."
**Skill does**: States plainly that Notably has **no public REST API, webhooks, or MCP server** — the only integrations are **Miro** and **FigJam** (import/sync, not a data-out pipeline), and the only data-out is **manual export**. Suggests a **scheduled manual/scripted export → ETL** as the workaround, notes there's **no programmatic pull** so it's batch, not a live sync, and — if a documented REST + webhooks pipeline is a hard requirement — routes to `/sales-userintuition`.
**Result**: The user builds a manual-export → ETL job instead of hunting for an API that doesn't exist.

### Example 3: "Should I use Notably or Great Question — and is Notably like Dovetail?"
**User says**: "I'm picking a research tool. We haven't recruited anyone yet. Is Notably basically Dovetail?"
**Skill does**: Clarifies that Notably is **analysis-only** (a Dovetail-style **repository + AI synthesis** tool that starts *after* you have data), and its edge over Dovetail/Condens is being the **most AI-forward** (auto theme extraction + insight summaries). Because the user **hasn't recruited yet**, flags that Notably is the wrong first pick and routes the **recruit → run → repository** job to `/sales-great-question`; for choosing among analysis tools across the market, routes to `/sales-customer-feedback`.
**Result**: The user picks the right tool for their stage — Great Question now, Notably (or Dovetail) once they have data.

## Troubleshooting

### "My tags/highlights disappeared when I switched sections."
**Symptom**: Tags or highlights applied on the canvas seem to vanish after navigating between views.
**Solution**: This is a reproducible Notably complaint. **Refresh the view** to confirm whether the tag was truly lost or just not re-rendered; apply tags in **small batches** rather than one long pass; and **re-check the tag/theme view** after navigating before assuming a study is fully coded. If tags are genuinely lost, re-apply and report it to Notably support — and keep your source transcripts as the ground truth.

### "The AI theme doesn't match what the participant actually said."
**Symptom**: An auto-generated theme or insight summary reads as off, generic, or overstated.
**Solution**: Treat AI output as a **draft, not a finding**. Open the **verbatims/quotes underneath the theme** on the split-screen canvas and confirm the AI clustered them correctly — re-tag or split the theme where it conflated distinct points. The value is acceleration; the accuracy check is yours. Feed cleaner, well-scoped source data (good transcripts, clear notes) for better clustering.

### "How do I get data in and out — and can I automate it?"
**Symptom**: The user wants imports set up and results flowing into other tools.
**Solution**: **In:** import transcripts/notes/**audio/video**/survey open-ends/whitepapers, and **sync from Miro or FigJam**. **Out:** **manual export** only — Notably has **no public REST API, webhooks, or MCP**, so there's no programmatic pull and no live sync. Script/schedule the manual export into your own ETL if you must, and route any documented-pipeline requirement to `/sales-userintuition`.