How to understand podcast stats
August 19, 2018 · Updated November 19, 2018 · By James Cridland · 6 minutes to read
Podcast statistics can be confusing and complex: but it’s always nice to look at the numbers to see how your podcast is doing.
Here are some details about how the different figures work, and how to read them.
How the Apple Podcast charts work
While Apple do not publish the way they compile the Apple Podcast charts, they are generally understood to be based on recent subscriptions.
An appearance on the Apple Podcast charts reflects a podcast’s ability to attract a larger number of new subscriptions to their podcast over recent days. It is not related to downloads.
You can appear very highly on the Apple Podcast charts by planning all activity around your podcast release on one specific day, and encouraging as many subscriptions on that one day as possible.
Other charts within Apple, like New & Noteworthy, are believed to be editorially driven: and again, unlikely to be driven by total downloads.
Like any other service, the Apple Podcasts charts can be manipulated, either by companies or by individuals.
Understanding Apple Podcast Analytics
You can see analytics for your podcasts by logging into Apple Podcasts Connect. It only tracks listens on the Apple Podcasts app (and iTunes), and only tracks recent versions of this app. Users can opt out of being tracked, too. Apple is responsible for about 60% of podcast downloads, so Apple Podcast Analytics perhaps only measures 50% of your downloads at best.
Because the numbers aren’t a total view of your podcast’s performance, Rob Walch from Libsyn recommends you ignore the numbers that you see in Apple Podcast Analytics; instead, he recommends you use it for the consumption graph that shows you how people are listening to your podcast; where they skip, and where they stop listening. You can also use it for trends - is the number generally increasing?
Apple Podcast Analytics only report a sample of your audience. They are an incredibly useful tool to help you understand how people are consuming your podcast. They do not give you the total numbers for your podcast, and will always be different to your podcast host.
Understanding your podcast host’s statistics
Your podcast host probably offers statistics about downloads. Be aware of the following:
- Spotify, Google Play Music, and in certain circumstances Amazon Alexa devices, cache your podcast (they take a copy and host it on their servers). Your podcast host may not see individual plays on these services. Make sure these numbers aren’t elsewhere on your podcast host’s dashboard, or hidden altogether.
- All podcast hosts measure downloads differently. Ones using the standard (they may describe themselves as “IAB v2 compliant”) are roughly comparable: but even these podcast hosts do not have identical measurement mechanisms. Ones that don’t use the standard, most notably Soundcloud, may appear to give you four or five times the amount of downloads. They’re not: they’re just counting them differently. When switching hosts, you won’t get the same numbers.
Understanding the difference between a play and a download
Most podcast apps download a podcast automatically; and don’t report back to your podcast host if it’s actually been played. However, the default for some podcast apps, notably Google Podcasts, Leela or Spotify, is only to download a podcast if you’ve pressed the play button. (This behaviour is typically known as “streaming,” though that’s a bit inaccurate).
A “play” normally means that there’s a human being listening. A “download” doesn’t always mean a podcast was ever listened-to. (32% of respondents to this UK survey say they listen to half their downloaded episodes or fewer).
Unfortunately, in most cases a podcast host can only measure total downloads - and is unable to know whether a downloaded podcast was played. Caution, therefore, when comparing different podcast apps.
Understanding Spotify analytics
Spotify does not measure downloads, but listens. Spotify supply two numbers. They say:
Starts measure any listener who clicked on a podcast episode. There is no minimum time limit to be counted as a start on Spotify. Starts align to a download used by other podcast listening platforms.
Streams measure any listener who listened to at least 60 seconds of your podcast. Streams align to the IAB (International Advertising Bureau) definition of a download, an industry-wide accepted metric.
Because Streams are a stronger representation of a person who listened to a meaningful section of your podcast, we recommend you use them to better understand your audience and their behavior.
Unlike other services, the Spotify for Podcasters portal gives you some data regarding the demographic breakdown of your listeners.
Understanding Podtrac analytics
Podtrac is a free service for podcasts. It measures downloads in a consistent way, whatever the podcast host.
You can use Podtrac to compare numbers for any podcast: but the numbers for individual shows aren’t made public.
Podcasters need to sign up with Podtrac (free) to measure a podcast. Many producers don’t; so the Podtrac numbers will always only show an incomplete picture of the podcasting landscape.
Caution: Podtrac actually measures a request for a download, and doesn’t know how much of the podcast is actually downloaded. There are technical ways to adversely affect the numbers.
You can discover if a podcast is using Podtrac by searching for it in Podnews, and then viewing its technical information.
Podtrac release some monthly data. See the latest from our daily newsletter archives.
Understanding third-party services like Podkite, Chartable and others
There are some products out there which might claim to show podcast analytics. However, unless they are directly built into your RSS feed or you’ve given them access to your hosting account, they do not know podcast download numbers.
These services mostly work by storing the Apple Podcast charts, and other similar services, and then making this historical information available in the form of a chart or table.
They are therefore a useful record of trending charts: but they do not offer a way of comparing a podcast.
You can get a taster of Chartable’s information for any podcast by searching for it in Podnews, and then viewing its technical information.
An example of why trending charts like the Apple Podcasts chart doesn’t measure a podcast’s popularity
Podcast 1 has spread by word of mouth. It has three new subscribers every day, and has existed for three years. It will never appear on the Apple Podcast chart, since that is worked out using recent subscriptions. It now has 3,000 subscribers (and almost as many downloads per episode).
Podcast 2 launched in a blaze of publicity three days ago. It got 200 new subscribers in one day, but has trickled away to very few new subscribers. It has a total of 230 subscribers. Because it did very well in its launch, it appeared at #20 in the charts.
While Podcast 1 has never appeared in the Apple Podcast Charts, it is over ten times larger than Podcast 2.
Podcast measurement vs radio measurement
You might hear some people compare podcast measurement with radio measurement. Here are the differences:
- Radio is measured by recruiting a sample of listeners, monitoring what they listen to (electronically or via a paper logbook), and then multiplying this number up to produce total audience figures. This is normally a statistically valid process (and station figures are relatively stable, which underlines this). However, sample sizes and the research process can cause unpredictable figures. Radio measurement isn’t, therefore, perfect.
- Podcasts do not use samples, and are typically measured by actual total downloads. However, total downloads aren’t the same as total plays. Podcast measurement isn’t, therefore, perfect.
- Radio research uses demographic information from the sample of listeners, so they’re able to claim certain stations do better with female listeners, or a 15-34 audience, or so on. This helps advertisers know where to advertise. Sample sizes may make this unreliable, though.
- Podcasts can use IP addresses and other data to give accurate geographical data; but they don’t have demographic research from their download figures, and have to undertake further research. That is often made up of super-fans of the podcast, a self-selecting group which is potentially unrepresentative of the total podcast listenership.
In short, therefore, all research is flawed. Be cautious about comparisons.
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