Podcast Transcription plus Data Entry

I have a series of technical, industry-specific podcast episodes that need to be turned into clean, word-for-word transcripts and then summarized into a simple data sheet for quick reference. Accuracy with jargon is critical because each episode is packed with domain terminology that my team will later quote in white-papers and slide decks.

Here is how the workflow should run from my side:

• You receive the raw audio file and a short show-note outline.
• You create a verbatim transcript, lightly edited for readability (ums, ahs, false starts removed).
• You capture speaker names and insert a time-stamp every five minutes to make navigation easier.
• Key data points—guest name, episode title, main topics, quoted statistics—are copied into a spreadsheet row so I can search them later.

I normally work with Word for the transcript itself and Excel for the data sheet, but if you prefer a different tool chain (e.g., Google Docs/Sheets or transcription software such as Otter.ai or Descript), that’s fine as long as the final files land in .docx and .xlsx formats. Turnaround on a single episode should be no more than 48 hours once you confirm receipt of the audio.

Deliverables will be accepted when:
1. The transcript is at least 98 % accurate based on a random three-minute spot check.
2. All requested metadata fields in the spreadsheet are filled in and spell-checked.
3. Technical terms match the usage found in the episode audio.

If this workflow fits your skill set, let me know and I’ll send over a test episode so we can kick things off.