Podcast Episode Ideas: Find Them in Your Transcripts

Most advice on choosing podcast topics points outward: check keyword tools, browse Reddit, watch Google Trends. One well-known guide to data-driven content calendars from The Podcast Host (2022) lists search keywords, Facebook groups, Reddit, Twitter, Google Trends and Pinterest as its sources, and does not mention your own episodes at all.

That leaves out the best source. Your archive is full of unfinished threads: things you promised to come back to, tangents you cut short, and questions listeners sent that you answered in two sentences. Those are topics you already know something about, that your audience has already touched, and that you have already signaled interest in.

This post shows how to pull those threads out of your own transcripts, sort them, and turn the best ones into episode briefs. It assumes a folder of plain-text transcripts, one file per episode, holding only your own lines. If your transcripts still need cleaning, see our guide to podcast transcript formats.

The three kinds of idea hiding in your archive

A fourth kind lives outside your transcripts: emails, direct messages, and reviews. Add those to the same list. The method works for all of them.

Step 1: Pull the flagged moments

You need host-only transcripts, or full transcripts if you don't mind reading the guest's asides too. This script scans a folder for a list of flag phrases and prints each match with the surrounding text:

#!/usr/bin/env python3
"""Find passing mentions in host transcripts that could become episodes."""
import re
import sys
from pathlib import Path

FLAGS = [
    "long story", "another episode", "whole other episode", "we'll get into that",
    "i'll come back to", "we should do an episode", "someone asked", "a listener",
    "people ask me", "i get asked", "rabbit hole", "another time", "for a future episode",
]


def main(folder):
    pattern = re.compile("|".join(re.escape(f) for f in FLAGS), re.IGNORECASE)
    for path in sorted(Path(folder).glob("*.txt")):
        text = " ".join(path.read_text(errors="ignore").split())
        for hit in pattern.finditer(text):
            start = max(0, hit.start() - 100)
            print(f"{path.stem} [{hit.group(0).lower()}]\n    ...{text[start:hit.end() + 140]}...\n")


if __name__ == "__main__":
    if len(sys.argv) != 2:
        sys.exit("usage: find_ideas.py <folder-of-host-only-txt-files>")
    main(sys.argv[1])

Run python3 find_ideas.py transcripts > ideas.txt and read the file. Each hit shows the episode, the phrase that triggered it, and the sentences around it:

0012-course-pricing [someone asked]
    ...we ran out of time. Someone asked about pricing for a second course, and honestly I don't have a good answer yet...

Edit the FLAGS list to match how you actually talk. If you say "side note" or "we could do a whole show on that," add those. Your own verbal habits are the best filter, and the voice measuring script from our voice guide post shows which phrases you use most.

Step 2: Add the outside signals

Open a spreadsheet with these columns: source, date, the idea in one line, and a quote or link. Paste in the script's best hits, then add listener emails, reviews, and any questions from social media. Do not judge anything yet. The goal is one list.

Step 3: Group and count

Sort the list by subject. If "pricing for a second course" shows up in three episodes and two emails, that is a stronger lead than a topic mentioned once. The count is your rough measure of demand, so add a column for it.

Then check your topic map from the archive search post. Each idea lands in one of three places:

• The archive has nothing on it. This is a fresh topic.
• The archive touches it briefly. This is a thin topic that could take a full episode.
• The archive covers it well. Skip it, or write a sequel with a clear new angle.

Step 4: Score the leads

For each remaining idea, answer three questions, yes or no.

1. Do I have something specific to say, such as a story, a number, or a failure, and not just a general opinion?
2. Has at least one listener asked, directly or indirectly?
3. Is my archive thin or silent on it?

Three yeses go to the top. This is a rough filter, not a formula. Its purpose is to stop you from picking the idea that merely sounds exciting today.

Step 5: Write a one-paragraph brief

For the top idea, write a short brief before you record anything:

Working title:
The question a listener would type to find this:
What I already said (episodes and quotes):
What I have not said yet:
A story or number I can bring:
Who could speak to it (guest, if any):

The second line matters for discovery. Phrasing the topic as a real question keeps the episode title honest and helps it match what people search. The third line keeps you from repeating yourself, and the fourth is the reason the episode exists.

When the archive is the wrong source

Deferred promises can be deferred for a good reason. A tangent might be a tangent because it is only interesting to you. Read each hit in context before you commit. Also, an archive only reflects the audience you already have. If you want new listeners, look outward as well. The outside sources in The Podcast Host's guide are a good complement, not a replacement.

Checklist

• Transcript folder ready, host-only if possible
• find_ideas.py run, with flag phrases edited to match your speech
• Listener emails and reviews added to the same list
• Ideas grouped and counted
• Topic map checked for existing coverage
• Top three scored and one brief written