Analytics
Analytics for podcast creators and audio content
Podcast analytics differ meaningfully from video analytics. You generally can't see exactly when a specific listener dropped off mid-episode the way you can with per-second video retention data. But there's still a genuinely useful set of things to track, even without that granular level of visibility into listener behavior.
What to actually track
| Metric | What it tells you |
|---|---|
| Download numbers, total and per episode | Whether specific episodes are meaningfully outperforming others |
| Release cadence (weekly vs. twice-weekly) | Which schedule actually sustains listener retention better over time |
| Episode length | Where your particular audience's realistic attention sweet spot actually sits |
| Guest episodes vs. solo episodes | Whether your specific audience prefers variety or a consistent solo voice |
| Topic-by-topic performance | Which subjects are genuinely worth revisiting or exploring further |
| First-time listener retention | Whether your first episode is effectively "selling" the value of your subsequent episodes |
Reading download numbers correctly
If a specific episode consistently gets meaningfully more downloads than your typical average, that's a genuine, real signal worth paying attention to — not simply random noise or coincidence. Compare topics and guest choices across your best-performing episodes specifically, looking for what they actually have in common, and use that pattern to inform future episode planning.
Why release strategy genuinely matters more than it might initially seem
Dropping two episodes a week versus one weekly episode can make a real, measurable difference in overall listener retention over time — but the right cadence for your specific audience isn't obvious in advance and really has to be tested directly, rather than assumed based on general industry norms or what other podcasts in your space happen to be doing.
The retention question that matters most
Do genuinely new, first-time listeners actually come back for a second episode after their first one? If they consistently don't, your very first episode isn't effectively selling the ongoing value of your subsequent episodes — regardless of how strong your content quality is further into your back catalog, which a first-time listener may simply never reach.
What podcast analytics ultimately need to serve
The actual goal was never podcast download numbers in isolation. It's whether podcast listeners convert into buyers, subscribers, or followers on your other channels — the podcast functioning as part of building an actual business, not existing as a self-contained vanity metric disconnected from everything else you're doing.
Tracking this without building a separate system
Most podcasts genuinely plateau because creators are guessing at what's actually working rather than tracking it directly and consistently. Track it deliberately and growth tends to follow — podcast growth moves slower than social media growth generally, but podcast listeners tend to be notably loyal once genuinely retained, which compounds meaningfully over time. mayy.ai can help track podcast performance alongside your other connected channels, so the full picture — not just isolated podcast download numbers — stays visible in one place.
See this for your own accounts
Ask mayy.ai about your own content in plain language — free to start, no credit card required.