---
name: how-we-use-listen-notes-to-find-track-and-repurpose-every-podcast-appearance
description: "Use Listen Notes to find podcast leads. Check each match before it goes in your main list."
category: Content Factory — Process
stage: Process
definitive_article: https://blitzmetrics.com/how-we-use-listen-notes-to-find-track-and-repurpose-every-podcast-appearance/
status: complete
---

# How we use Listen Notes to find, track, and repurpose every podcast appearance

A search for your name can find old podcast visits. It can also find people who only mention you. This guide helps you tell the difference and save the useful results.

**The path:** Name query → Search matches → Episode proof → Merged inventory.

**Use this when:** The appearance inventory needs a reproducible Listen Notes discovery pass.

## Inputs
- Verified public name variants, known shows and identity context.
- The master inventory with lead/verified/mention/rejected/unresolved states.
- Listen Notes search access; exports and alerts may require existing paid access or separate purchase scope.
- Search date/filters and a named inventory owner.

## First-run prompt

> Search the supplied name variants on Listen Notes and record query/filter/date coverage. Capture accessible results or use the already-authorized export. Verify actual episode presence, merge duplicates and keep mentions separate. Treat scores and alerts as their actual measured states; do not buy access or invent delivered notifications.

## Steps
1. Prepare each quoted name variant and known show query. Record query, date and filters so another reviewer can repeat the pass.
2. Search Episodes and capture observed counts and accessible rows. Inspect Podcasts separately for hosted shows. A show match, episode match and verified appearance are different units.
3. Save title, show, date, Listen Notes URL, primary episode link and matching context. Export only when the actual feature/access and cost are in scope; otherwise capture the bounded results manually and state any uncollected remainder.
4. Use filters only when they fit the assignment and record them. Do not apply unique-podcast filtering if the goal is every episode, since that can hide multiple appearances on one show.
5. Open source show notes or episode evidence to verify identity and role. Listen Notes does not transcribe or search all audio; available transcript matches are a limited discovery source. A name in one is still only a mention until presence is established.
6. For priority verified rows, record any available Listen Score/percentile with its date as a show-level estimate. It does not prove guest presence, episode views, revenue or a comparable cross-platform rank.
7. Merge verified rows into the master inventory using episode identity and preserve all source links. Reconcile duplicates and review uncertain matches against Podchaser, YouTube or the host page.
8. If clipping is requested, use only a verified permitted source with actual start/end times and save the resulting state. Search completion does not require creating a clip or making a public playlist.
9. If monitoring is authorized and available, create or reuse the exact Listen Alert query, filters and email/RSS receiver. Verify the saved setting and first actual delivery; keep it “configured, first delivery pending” until observed. Return the updated inventory and remaining coverage gaps.

## Definition of done (QA checklist)

- [ ] Queries, filters, observed counts and captured rows are reproducible.
- [ ] Every confirmed row has primary role/identity evidence.
- [ ] Search/export/score counts are not substituted for verified appearances.
- [ ] Master merge and optional alert state are recorded without hidden purchase or delivery claims.

## Example(s)

**Fictional teaching example — no search was run.** A sample quoted-name query shows eight results. Review finds three genuine episodes, two mirrors of those episodes, two mention-only items and one unresolved identity.

The master list adds three appearances, not eight. A show-level Listen Score may help choose which source to inspect first, but stays separate from the verified-appearance count. If an alert is saved today but no email has arrived, its record says “configured; first delivery pending.”

## Handoff and Content Factory context

The inventory owner receives verified rows and unresolved leads for [the master appearance inventory](https://local-service-spotlight.github.io/task-library/?task=how-to-inventory-every-podcast-youve-been-on-and-why-its-one-of-the-highest-roi-things-you-can-do#task-how-to-inventory-every-podcast-youve-been-on-and-why-its-one-of-the-highest-roi-things-you-can-do). [Podchaser review](https://local-service-spotlight.github.io/task-library/?task=how-we-use-podchaser-to-amplify-authority-and-repurpose-podcast-content#task-how-we-use-podchaser-to-amplify-authority-and-repurpose-podcast-content) can use those leads while checking each credit independently.

Produce supplies the real source. **Process**, this stage of the [Content Factory](https://blitzmetrics.com/content-factory/), turns it into useful finished assets. Post saves or publishes them on the agreed channels. Promote tests and distributes suitable work within its own scope. The handoff above names this task’s actual next step; catalog neighbors alone are not prerequisites.

## When this runs

A bounded discovery pass, then optional authorized alerts or dated refreshes feeding the same inventory. Every new match still requires review.

## First-run setup and continuity

Open the supplied task file and its linked source. Verify the project’s real inputs, account, access and output folder before work. This Markdown file is a guide; it does not install an app, connect an account, supply a subscription or create a schedule. Carry out work already authorized; do not ask for the same approval again. Keep any unsupplied destination or new action outside that scope clearly pending.

Save source IDs, versions, decisions, checked outputs and next owner in the project tracker. Before a retry, check the saved state and other workers’ changes. A model name does not guarantee memory or a running timer. Repeated work needs an actual configured trigger and durable state; one-off work can be started by the prompt above.

Keep agent media muted with volume zero before playback. If mute cannot be verified, use captions, metadata or still frames. State the limit: silent visual checks do not prove spoken-word accuracy or audio quality. Do not start sound through the user’s speakers unless explicitly asked.

## Write up the real run

For every actual attempt, [write its meta article](https://blitzmetrics.com/meta-article-prompt/) with this recipe and revision, trigger, steps performed, output evidence, measured result, gaps and next owner. Failed, blocked and partial attempts also get a written record. A draft can satisfy writing; publishing it follows the existing job scope.

Keep one stable execution ID across retries and edits. A separately scoped child task may have its own ID linked to its parent. Writing the parent’s meta record is part of that run, not an endless new chain. The [recipe and meta-article guide](https://localservicespotlight.com/meta-articles/) explains this distinction. Teaching examples are not real executions and must not enter the run count.


<!-- factory-layer:start -->

## Factory chain (do not treat this as isolated)

- **Phase:** Process
- **Importance:** 4/5 `●●●●○` — frequency 4, revenue 3, gating 2 (runs every factory cycle or weekly)
- **Suggested previous station:** —
- **Suggested next station:** —
These stations are generated neighbors, not verified prerequisites or handoffs. Follow the task’s actual Inputs and Handoff sections.
- **Handoff:** Process-stage artifact examples include `transcript.md`, `gct.md`, `article.html` (or a staged draft), `clips/`, or `04-Promote-Creatives/`. These are examples, not requirements for every task. Follow this task's actual Inputs and Handoff sections for the required output, evidence, and next owner. Pass the files or records, not one vendor's memory.

## Model routing (same factory, any engine)

- **This task's lane:** `any` — Any capable chat model (Claude, ChatGPT, Grok, Gemini). SOP following, drafts, checklists.
- **Single-engine path:** Use the capable AI app you already have. Check its required tools and access before starting. Pass the actual result and proof to the next task.
- **Optional multi-engine:** A tested local model may draft; a stronger model may review facts and voice. Use supported tools for approved actions. Pick models from observed quality and cost; a model name does not prove it can run this task.
- **Never** store the working state in one vendor's memory. Files in the Content Library are the bridge.

<!-- factory-layer:end -->
## Definitive article & links

- Canonical article: https://blitzmetrics.com/how-we-use-listen-notes-to-find-track-and-repurpose-every-podcast-appearance/
- Exact task: [How we use Listen Notes to find, track, and repurpose every podcast appearance](https://local-service-spotlight.github.io/task-library/?task=how-we-use-listen-notes-to-find-track-and-repurpose-every-podcast-appearance#task-how-we-use-listen-notes-to-find-track-and-repurpose-every-podcast-appearance)
- Writing standard: [Article Guidelines](https://localservicespotlight.com/article-guidelines/)
- [Listen Notes export options](https://www.listennotes.help/article/108-podcast-datasets-quickstarts)
- [Listen Notes alerts and transcript limits](https://www.listennotes.help/article/106-how-to-track-podcast-mentions-with-listen-alerts-the-ultimate-podcast-social-listening-tool)
- [Listen Score definition](https://www.listennotes.com/listen-score/)

## Review and evidence still needed

The source contributor status is preserved. It is not certification of this draft or proof of account access, completed work or a live outcome. The worked example teaches the method and is explicitly fictional.
- Export/alert availability depends on actual access; uncaptured results and absent episode proof remain explicit.