Podcast analytics are about as straightforward as tangled fishing line or knotted Christmas lights. Whether you’re looking at your podcast host’s download data, Spotify podcast analytics, Apple Podcasts analytics, or YouTube’s audience information, there is a lot to understand that the platforms don’t tell you (at least not up front).
Your understanding will be incomplete, however, without knowing how you should be approaching data. It’s a powerful tool and makes outcomes possible that wouldn’t be otherwise, but most people in business and in podcasts are using data incorrectly.
Here at Rooster High, I compile and analyze podcast data every month for our clients to tell the story of how the shows are performing as content marketing. As you’ll see, this isn’t a straightforward task; we gather download data from the podcast host, “Listener” and “Follower” data from Spotify for Creators and Apple Podcasts Connect, and viewer data from YouTube.
Every one of those platforms listed measures the data differently, which makes it much harder to find the real story behind it all.
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What are podcast analytics?
Podcast analytics are made up of data of various kinds. When someone’s phone wants to play one of your podcast episodes, their device asks your podcast host (the podcast software that holds your episodes, waiting to send them to listeners) for the sounds file. Various systems measure various things about that interaction, then report it to us in data.
Each time a computer asks your podcast host for the sound file, your podcast host calls that a download. That’s the basic metric of measuring a podcast. It’s important to note that just because your podcast got a download, it doesn’t mean someone listened to it.
Downloads are a measure of podcast delivery. They measure how many times audio or video files were requested by listeners’ devices and delivered by a hosting provider. But just because a file was requested and delivered does not mean it was actually played back.
– Dan Misener, co-founder of Bumper
What about Spotify Analytics, Apple Podcasts Analytics, and Podcasts on YouTube?
While the download is a metric directly attached to your podcast host, once those episodes go to Spotify and Apple and YouTube (well, kind of YouTube… we’ll talk about that later) those platforms can give us much more data about the listeners on their platform.
But they’re each reporting it differently. While Spotify’s analytics and Apple Podcasts’s analytics are somewhat similar, there are crucial differences that will lead you astray if you don’t know the exact differences. And then there’s YouTube, which can work in several different ways for your podcast. It is a completely different platform, and has a lot of powerful analytics, but it’s a completely seperate “data language” from the others.
Let’s use an example to illustrate where the complexities start to come in with podcast analytics.
The Podcast Downloads = Cupcakes Example
Let’s say that instead of a podcast, you have a cupcake store. Each cupcake, in this example, represents a download.
Let’s also say that you are absolutely mad for analytics, and you don’t just want to know if someone bought a cupcake; you want data on how many cupcakes were actually confirmed to be eaten.
In this instance, a podcast episode download is like the purchase of the cupcake. The cupcake (your episode) was delivered to the person who asked for it. However, just because someone buys a cupcake doesn’t mean they’ve eaten it. Maybe they had a sudden urge to go on a diet, and disposed of it. Perhaps they bought it to make you feel better about your cupcake store you opened over a full decade after the fad died, or it simply fell on the ground after they reached for something in their purse.
As the cupcake store owner, you need to track who buys cupcakes (easy) and who eats those cupcakes (not easy).
Tracking Podcast Downloads (As Cupcakes)
So, you ask a few friends to volunteer to track the cupcake-eating public, on top of getting regular reports from the Point of Sale in your store.
Your first source of data is that point-of-sale machine. It tells you how many cupcakes you sold. Excellent! But we are mad for data, remember? We now need to know about consumption, not just delivery.
These volunteer friends have a partial stake in getting the data right. They’re your friends, after all, but they’re not getting paid.
The Friends Tracking Cupcake Consumption
One friend, let’s call him Spotify (not one you’ll see on the baby name lists), has a thriving data firm exclusively for bakers of cakes. Cupcakes were related, so he has some solid experience tracking the cupcake-eaters, though your unsure of the numbers. He’s quite successful so it’s tough to ask him to put more effort in.
Another friend, Apple (not one you’ll see on the baby name lists outside of the Pepper Potts / Viva la Vida crossover fan club), is immensely wealthy and is only counting cupcakes because she’s your friend. When she delivers her report on cupcake consumption, she openly admits to double-counting many of the cupcakes.
Your friend YouTube is an altogether different señor beast. He actually buys the cupcakes wholesale, sells them in another part of town, and gives you more data on cupcake delivery and consumption than you could ever dream of.
How should I approach podcast analytics?
The cupcake example gives you a good picture of exactly how unstandardized podcast analytics are. Four sources of different, imperfect information are difficult to analyze. This can be helped by engaging in some analytics best practices.
Whenever you look at data, ask the question “What question should I be asking?” There is always a story of real human behavior behind podcast data. The numbers are simply an efficient and imperfect intermediary to give us a little glimpse into how people and machines are behaving, but they never tell the whole story.
The nature of a podcast download is a great example of this. If you didn’t know better, you would assume (and I could not blame you) that a podcast download means a lovely, intelligent person has listened to your episode and found it to be valuable. But when we do our research, we realize that a download isn’t a person at all – just a point at which one computer asked another computer for your episode.
You need to know what you’re working with. What is a download? In Spotify analytics, what is a Listener? What is a Follower? In Apple Podcast Analytics, what is a Listener? And what the heck is an Engaged Listener, and why are my Plays in Apple Podcasts Connects way higher than my Listeners? And that’s just the start.
Download Issues In Podcast Analytics
If you create a podcast for long enough, you’ll encounter download spikes that don’t seem to correllate with any other meaningful activity. In 2021, Apple finally fixed a bug that causes download spike (read at Podnews) and in April 2025 a Google News app error caused a similar issues for podcast analytics (read at Podnews).
Every download that is a result of those bugs isn’t an engaged listener, it’s a confusing by-product of tech malfunctions. And if you’re not subscribed to a reliable podcast new source like Podnews, and if you don’t have a reliable podcast analytics agency like Rooster High, you’re likely to remain confused.
Where are the Podcast Analytics Tools?
As of writing, there is no one publicly available tool that combines all four disparate data sources into one report to then interpret. Podcast agencies like Rooster High, StoryOn Media, and Bumper all have their versions for their clients, but every of these reporting systems is high-touch and as unstandardized as the data we’re analyzing.
It takes technical knowledge and data interpretation skills to make sense of all this. And it is possible – it’s just not easy.
The Next Steps for the Business Podcast
We write for business and non-profit podcasts here at Rooster High, since we use the medium of podcasts as content marketing for our clients (and are always asking the Relational Marketing question).
If you have a podcast for your business and the podcast analytics are a source of frustration, get in touch with me. Creating an understanding of what’s happening with your show, in the greater context of how your podcast is serving your business strategically, is a speciality of mine.
The Great Promise of Podcast Analytics
Podcast analytics are one part of telling the story of what is happening with your audience, your show, and your organization. Your show is the backbone of your marketing funnel, being an authentic place to derive a ton of content from or position your business in the industry. When the podcast analytics start to serve you as a part of the bigger picture, it will help accellerate that growth.