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How to read the CSVs

A column-by-column guide to the data PodAnalyst exports. Every export button downloads a plain .csv file that opens in Excel, Google Sheets, or Numbers.

Overview

The Dashboard and Episodes pages each have an export button in their top toolbar. Click it and your browser downloads a file named <timestamp>-<podcastId>-<name>.csv. Accounts on the free plan see an upgrade prompt instead of a download.

The export reflects what you're currently viewing — you don't have to re-pick filters after clicking it. The downloaded file uses the reporting mode and date range selected on the page.

A blank cell means there's simply no data for that episode or period yet (for example, a very new episode). It's not an error.

Dashboard analytics export

dashboard-analytics.csv

One long, flat table of all four growth metrics across every platform. Every row is one metric, on one platform, for one period.

column what it means possible values
metric Which stat the row reports. seconds_consumed is total listening time in seconds. unique_listeners · seconds_consumed · plays · followers
platform Where the number came from. apple (Apple Podcasts Connect) · spotify (Spotify for Creators)
period The date (YYYY-MM-DD) the value was reported. Daily in the monthly and last-60-days views; one row per month in the All Time view. 2026-07-01, 2026-07-02, …
total The raw number for that metric, platform, and period. Any number, e.g. 412

How the reporting mode changes period

  • Monthly (default) — one row per day inside the selected month.
  • Past 60 days — daily rows for the last 60 days.
  • All Time — one row per month, using month-end snapshot totals.

Episodes export

episodes.csv

One row per episode, newest first. Capped at 50 episodes on the free plan and 200 on paid plans — exactly the list you see on the Episodes page.

Percentiles compare an episode to the baseline — the first ~100 episodes shown in your Episodes view. A percentile of 88 means the episode beat 88% of that baseline.

column what it means
titleEpisode title.
datePublish date, YYYY-MM-DD.
apple_episode_idApple's identifier for the episode. Useful for matching episodes across datasets.
starting_listenersListeners at the start of the episode.
starting_listeners_percentile0–100. How the starting listener count compares to the baseline — "better than N% of episodes".
percent_from_averageSigned % vs. the baseline average performance at the same age in days. Positive = above average, negative = below. This is the "% from Avg" column on the Episodes page.
day_measuredThe day since release (1-based, capped at 60) at which the comparison was measured.
episode_performanceThe episode's own performance value on that day.
avg_performanceThe baseline average performance on that same day.
retention_25 / 50 / 75 / 100Percentage of listeners (0–100) still listening at 25%, 50%, 75%, and 100% of the episode.
retention_…_percentile0–100. How that retention point compares to the baseline — "better than N% of episodes".

Coming next: reviews export

A reviews.csv export is on the way. When it lands it will include one row per review with: itunes_podcast_id, itunes_review_id, username, review_title, review_text, dt_reviewed, rating (1–5), and country_code.

Tips

  • Open the file in Google Sheets or Excel — it's a plain UTF-8 CSV, nothing special needed.
  • Use a pivot table on metric + platform to roll the dashboard export up into a single view.
  • Blank retention cells usually mean an episode is too new and the platform hasn't reported that point yet — check back later.
  • Percentiles are relative to your own show's history, not the whole internet.