---
aliases: ["Podcast Analytics Review"]
Is A: Procedure
Belongs to: "[[responsibility-podcast]]"
Cadence: Monthly
Owner: "[[person-luca-rossi]]"
---
# Podcast Analytics Review

The monthly podcast analytics review turns download numbers into editorial decisions. By examining which episodes perform, where listeners drop off, and which topics sustain engagement, this procedure ensures the podcast evolves based on evidence rather than assumptions. The data collected here directly informs guest selection, topic planning, and format experiments, all of which drive [[measure-podcast-downloads]] growth over time.

## Steps

- [ ] Pull download data for all episodes published in the past month from the podcast hosting platform
- [ ] Record [[measure-podcast-downloads]] for each episode and the monthly aggregate — compare against the prior month and 3-month average
- [ ] Analyze listener retention curves for each episode: where do listeners drop off? Are there patterns tied to episode length, segment type, or topic?
- [ ] Rank episodes by performance and identify what the top-performing episodes have in common (guest profile, topic type, title format)
- [ ] Review listener geography and platform distribution for any notable shifts
- [ ] Check podcast review sites for new ratings and reviews — note themes in listener feedback
- [ ] Compare [[measure-podcast-episodes-per-month]] against the target cadence — were all planned episodes published?
- [ ] Identify 2-3 actionable insights (e.g., "episodes under 45 minutes retain 20% more listeners" or "solo episodes outperform interviews this quarter")
- [ ] Share findings with [[person-paco-furiani]] to inform editing and production decisions

## Notes

- Download numbers for new episodes stabilize after about 7 days. Do not draw conclusions from the first 24-48 hours — early downloads reflect audience habits, not content quality.
- Listener retention is the most underused metric in podcasting. A high-download episode with 40% retention at the midpoint is less healthy than a moderate-download episode with 75% retention.
- Compare performance across guest episodes vs. solo episodes. If one format consistently outperforms, adjust the mix accordingly rather than forcing a 50/50 split.
- External factors (being featured in a podcast directory, a guest sharing with their audience) can cause download spikes that are not repeatable. Separate one-time spikes from sustainable growth in your analysis.
- This review feeds into [[procedure-podcast-guest-outreach]] — let the data guide what kind of guests and topics to prioritize in the pipeline.
