How to Automate Podcast Brand Mention → PR Tracking + Outreach Email with n8n
Your brand just got mentioned on a podcast with 40,000 downloads — and you have no idea it happened. No screenshot, no thank-you note to the host, no link in your press page, no follow-up pitch to be
Your brand just got mentioned on a podcast with 40,000 downloads — and you have no idea it happened. No screenshot, no thank-you note to the host, no link in your press page, no follow-up pitch to be a guest. By the time someone forwards you the episode weeks later, the moment is cold. This is the invisible tax on brands that rely on word-of-mouth: earned media happens constantly, and almost none of it gets captured, tracked, or converted into a relationship. This article shows you how to build a fully automated podcast mention monitor in n8n that runs twice a day, logs every hit for PR reporting, and fires off a warm outreach email to the host — without you lifting a finger.
The Problem: Earned Media Evaporates in Real Time
Podcasts are a uniquely hard channel to monitor. Unlike a blog post or a tweet, a mention is buried inside an audio file — invisible to Google Alerts, invisible to most social listening tools, and impossible to skim. The signal only becomes text once the episode is transcribed, and most shows publish transcripts hours or days after release, if at all.
The result is a triple loss for founders and ops teams. First, attribution loss: you can't tell your board or investors how much earned media you're actually generating because you never counted it. Second, relationship loss: the single best moment to build a bond with a podcast host is within 48 hours of them mentioning you — that's when a "thank you, loved the episode" email lands as genuine, not transactional. Third, compounding loss: a host who mentioned you once is your warmest possible lead for a guest spot, a sponsorship, or a co-marketing deal, but only if you reach out while the mention is fresh.
Doing this manually means someone on your team listening to dozens of shows a week. Nobody does that, so the mentions pile up and quietly disappear.
The Solution: A Twice-Daily Mention-to-Outreach Pipeline
The workflow closes the entire loop automatically. On a schedule, it pulls fresh podcast episode data and transcripts, scans them for your brand name and known variations, and when it finds a match it does two things at once: it appends a structured row to your PR tracking sheet (episode, show, host, date, quote context, link) and it drafts and sends a personalized outreach email to the host. Everything is logged so you have an auditable record of earned media, and nothing depends on a human remembering to check.
The building blocks in n8n are deliberately simple: a Schedule Trigger to run twice a day, an HTTP Request node to query a podcast search/transcript API, a Code or Filter node to detect mentions and deduplicate, a Google Sheets (or Airtable/Notion) node for tracking, and a Gmail or SMTP node for outreach. Optionally, an AI Agent node writes the email body so each message references the actual context of the mention.
Step-by-Step Setup in n8n
1. Schedule Trigger. Add a Schedule Trigger node and set two cron expressions or use the interval mode set to run at, say, 08:00 and 18:00. Running twice a day keeps your outreach within the critical 48-hour window without hammering API rate limits or spamming hosts.
2. Fetch episodes and transcripts. Add an HTTP Request node pointing at a podcast data API (Listen Notes, Podscan, or a transcription service like Deepgram/AssemblyAI for shows you already track). Use a GET request with your API key in the Header Auth credential, and query by keyword — your brand name — plus a published_after timestamp so you only pull recent episodes. Set the response format to JSON. If you monitor a fixed list of shows, pass their feed IDs as a query parameter instead of an open keyword search.
3. Detect and normalize mentions. Add a Code node to loop over the returned items. Build a small array of brand variants — ["Acme", "AcmeHQ", "acme.com", "Acme AI"] — and test each transcript or description field with a case-insensitive regex. For every hit, output a clean object: { show, host, episodeTitle, publishedAt, matchContext, episodeUrl, hostEmail }. The matchContext should grab ~200 characters around the mention so both your sheet and your email have the actual quote.
4. Deduplicate. Before writing anything, guard against re-processing the same episode on the next run. Add a Google Sheets node in "lookup" mode (or an If node comparing against a stored list) keyed on episodeUrl. Route only new episodes downstream. This single step is what makes a twice-daily schedule safe — without it, every run re-emails hosts you already contacted.
5. Log to PR tracking. Add a Google Sheets node set to "Append Row." Map each field from your normalized object into columns: Date, Show, Host, Episode, Quote, Link, Outreach Status. Set Outreach Status to "queued" here; you'll update it after the email sends. This sheet becomes your earned-media report — sortable, shareable, and board-ready.
6. Draft the outreach email. Add an AI Agent or Basic LLM Chain node (Claude works well here) with a prompt that takes show, host, and matchContext and returns a short, warm, non-salesy email: thank them, quote the exact moment they mentioned you, and offer one specific piece of value (a guest appearance, exclusive data, an audience shoutout). Keep the system prompt strict — 90 words max, no marketing clichés, first-person from your founder.
7. Send and update status. Add a Gmail node (OAuth2 credential) set to "Send," mapping the host email to "To" and the AI output to the message body. On success, add a final Google Sheets "Update Row" node flipping Outreach Status to "sent" with a timestamp. Wire the whole chain so a failure at the email step doesn't corrupt your tracking log.
Benefits: What This Actually Buys You
Zero missed mentions. Every time your brand surfaces on a monitored show, it's captured within twelve hours — no human listening required. Over a quarter, this is the difference between "we think we get some podcast love" and a spreadsheet with 30 documented mentions.
Warm relationships at scale. The outreach email lands while the episode is still fresh in the host's mind. Hosts remember the brands that noticed and said thank you — this is how a single mention turns into a recurring sponsorship or a guest invite.
Board-ready PR reporting. Your tracking sheet is a live earned-media dashboard. When leadership asks "what's our organic reach?", you have quotes, dates, and download numbers instead of a shrug.
Founder time back. The entire pipeline runs on infrastructure you already have. No new hire, no agency retainer, no daily habit to maintain — just a workflow that quietly compounds relationships in the background.
Common Pitfalls (and How to Dodge Them)
Skipping deduplication. This is the number-one way to torch your reputation. If you forget the dedup step, the same host gets the same thank-you email twice a day forever. Always key on a stable unique ID like episodeUrl and store what you've already processed.
Over-broad brand matching. A brand named "Notion" or "Loop" will match thousands of false positives. Use word-boundary regex (\bacme\b), require a second signal for ambiguous names (your domain or a product term nearby), and route low-confidence matches to a "review" tab instead of auto-emailing.
Robotic outreach. Generic "We saw you mentioned us!" emails read like spam and burn goodwill. Feed the actual quote into the LLM, cap the length, and have your founder approve the tone once — then let it run. Consider an approval gate (a Wait node plus a Slack/Telegram button) for the first two weeks until you trust the copy.
API rate limits and cost. Transcript APIs charge per minute of audio. Filter to shows and keywords that matter, cache results, and don't re-transcribe episodes you've already scanned. The twice-daily cadence is intentional — it balances freshness against cost.
Silent failures. If your API key expires or the sheet auth breaks, the workflow can fail quietly and you'll assume "no mentions" when really it's broken. Add an Error Trigger workflow that pings you on any failed execution so a dead pipeline never masquerades as a quiet week.
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