Springcast Podcast analytics; what do the numbers say?

springcast podcast analytics
It's one of the most frequently asked questions since the launch of Springcast 2.0... What is a download? What is a unique download? What is the difference? In other words... What do the numbers say?

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In this article, I will explain the different statistics you can find in the Springcast platform.

Do you just want to know what a certain metric means? Then navigate to 'metrics' via the table of contents below.

Do you want to get a good understanding of how our analytics work? and how we get our data? Then read the whole article.

This article was published on 26 August 2021 and will be updated as changes are made to our analytics suite. 

Last edit 26-08-2021.

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Do you want to go directly to the explanation of the metrics? Then take a look at The metrics

Podcasts & analytics

Although the podcast itself has been around for over 20 years, podcast analytics is really still in its infancy. Until a few years ago, you could really only see how many downloads a podcast show or episode had.

In recent years, as people got more serious about their podcasting, analytics became more important and the podcast hosts offer more statistics. For example, you could see what time of day people were listening and on what days.

At Springcast, we think a little differently than the average podcast host. Whereas the average host has a background in hosting or podcasting, we come from a content marketing and communications background. That's led to our Analytics Suite being one of the most advanced in the industry.

What makes it particularly difficult is the lack of uniformity of the available data that we receive from parties such as Spotify and Apple. At the time of writing, Apple does not share any extensive data and we can only display downloads and, for example, the use of the Apple Podcasts App, whereas we receive extensive data from Spotify (as an official Spotify partner) via an API link (Nov. 2021).

And then there is the IAB standard, which has developed a standard for uniform reporting to advertisers. Unfortunately, this is not the most accurate standard at the time of writing, which is why we are deliberately not getting certified at the moment.

But anyway... we try to present all this as uniformly as possible in your podcast analytics suite

The metrics


Every time an audio file is called, we register a download. Even if it is the same person/device combination. For example, if someone listens again the next day, it is counted here again.

Unique listeners

Unique listeners can be seen as a person. Based on a number of characteristics, we can fairly accurately determine whether someone has listened before. So if someone listens to an episode for the second time, he is not counted here. *

Average listening time

If someone listens to your episode within the Springcast eco-system**, then we can see exactly where someone is listening up to. So the average listening time is an average of what we call the completion rate.


Did you add a call-to-action to your podcast? Then this metric reflects how often that link was clicked. We get this data from the listeners who listen via the Springcast ecosystem**.

Percentage listened to

This bar chart shows how many listeners have listened to a certain percentage. E.g. 10 people have listened 15% and 100 people have listened 90%. We get this data from the listeners who listen via the Springcast ecosystem**.

Listened to section

This is actually a more accurate representation of the listening percentage. Here you can see in the graph where people dropped out. We get this data from the listeners who listen via the Springcast ecosystem**.


In this graph, you can see where people pause. The pause points can give you insight into where people might make a note, look something up or something similar. We get this data from the listeners who are listening via the Springcast ecosystem**.


In this graph, you can see where people mute or unmute. These moments can give you insight into where people might temporarily drop out. We get this data from the listeners who are listening via the Springcast ecosystem.**

Fast forward and rewind

In this graph, you can see where people fast forward and rewind. These moments can give you insight into where people might find parts of the podcast interesting to listen to again or less interesting and skip them. We get this data from the listeners who listen via the Springcast ecosystem**.

* If several people within the same internet network are listening at the same time, they may be wrongly filtered out and counted as one unique listener. For podcasts that are listened to a lot internally, this is therefore not the most reliable metric.

** Springcast ecosystem: listeners who listen via the embedded player or via the podcast website.

How we get our data

The first thing you should know is that we distinguish between the following data sources:

  1. Native data sources
  2. Partner data sources
  3. External data sources

Native data sources are players that we have built ourselves, like the embedded player, the podcast website and for example our internal podcast apps. Here we have full access to all data (except for personal data of listeners, because we don't do that ;)).

Partner data sources are sources of external parties that we have a link with. These partners, which currently include SpotifyThey give us access to an extensive set of data. We just do not have access to all of it, so we have to make do with what is made available.

External data sources are sources that we identify. We see them fetching your content from our servers and serving it to listeners, but that's all the data we get. In fact, we only see which platform is retrieving your content, which device/app is being used and things like the time of day the request is made.

About our Spotify integration

Springcast is an official licensor of Spotify which means that we have an integration with Spotify. This means that we can get statistics from the platform through a link, but we also have a so called API Connection, so that changes are updated in real time at Spotify. A blog with more information about this link will follow shortly.

Reliability of data

It is good to know that there is nothing like 100% accurate data. We have several factors to weigh to determine whether someone is a unique listener, or someone who restarts an episode. 

One of these factors is, for example, the ip address. We do not log the IP address for reasons of privacy, but we do convert the IP address into an encrypted code. We use this code to determine whether a download made shortly after another download is from the same listener or from a new listener. 

This is only one of the 10 factors we take into account, but despite these 10 factors, it can happen that someone is wrongfully not taken into account or accidentally taken into account a second time.

We have the IAB standard for podcasts used as a starting point and extended further, because a number of new technologies have not been identified in this standard that would improve its accuracy. This is also one of the reasons why we are not yet IAB certified.

Our analytics roadmap

Our Analytics Suite is already one of the most comprehensive in the world, and we've only just started 😉 . 

We are busy working with various partners to further expand the data set of Partner Sources to provide more accuracy, but also continue to invest in native sources.

Because we believe that good, reliable analytics is one of the cornerstones on which the future of podcasting should be built. Because better understanding of how listeners interact with the content, the better content creators will be able to improve their content.

Spotify integration

We are currently working on the integration with Spotify, which will allow us to add a whole set of unique metrics to the Analytics Suite. Metrics that no other host in the world offers.

It may sound a bit pompous, but think of it as a combination of passion and ambition 😉 .

If you have any wishes regarding Podcast Analytics, please let us know. And... Happy podcasting!

Nico Oud

Nico Oud

An entrepreneur with a mission. A mission to help entrepreneurs reach their goals. As a business coach I share my 20+ years of experience and with Springcast I help entrepreneurs to spread their message through podcasts. I'm also an avid podcast listener and producer.

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