The Corruption of Podcast Subscriber Data

If you’re a podcaster, advertiser, or curious listener, you may want to know how many subscribers a podcast has. It sounds like a simple question with an easy answer. To the frustration of many, podcast data is full of ignorance, white lies, deception, and intentional manipulation.

In the “big data” era, this should be easy to figure out, but 3rd party objective data is not available—and it hasn’t been for years. This means we are all at the mercy of the podcaster’s honesty. (For now) Knowing how listers are tracked is vital. Let’s dig in.

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Why can’t you tell how many subscribers a podcast has?

To be clear, most podcasters do have access to data like downloads and location; three problems corrupt this data, however.

  • A “download” might not actually be a listen
  • Location data might not be accurate due to VPNs and ISPs.
  • The downloads might be fake.

It’s not an easy task to unpack how many subscribers a podcast has, or even if anyone listened at all. To provide a more clear picture, it helps to understand the mechanics of podcasting.

How are podcasts sent to Apple, Google and Spotify, etc?

Like websites, podcasts are stored on a podcast host server. Popular servers include Libsyn, PodBean or Megaphone. The server generates an RSS feed, and the podcaster submits the feed to platforms like Spotify, Apple Podcasts, Google Podcasts, iHeartRadio, Stitcher, Amazon Podcasts, and Pandora. When one of those platforms “requests” the file, the host server logs it as a listen. It’s as simple as that.

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When a listener “subscribes” they are simply telling their platform of choice, like Spotify, to download new episodes when available. For this reason, podcasters may have no idea how many actual subscribers they have. Podcasters can view some information about their subscribers using various dashboards provided by the listening platforms, (more on that later) but even that data has problems.

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Ok… how do podcasters know their subscriber number?

If the podcaster is honest, a podcaster knows their subscriber number by calculating the average number of downloads per episode. Not all listeners are subscribed because many people listen to a podcast for a single guest. However, calculating the average download per episode is the best way for podcasters to determine subscriber count. Podcast creators can also combine their numbers from various listening platforms’ dashboards as well.

Sadly, many podcasters claim their subscriber number is the total number of downloads over the duration of the podcast. Using this metric, if a podcaster produces 30,000 episodes and only their mom listens, they will claim they have 30,000 “listeners.” Because I’ve helped numerous podcasters, I’ve witnessed how many “listeners” various podcasters claim to have. An alarming amount of them misrepresent their subscriber numbers.

Some podcasters go beyond fudging the numbers, choosing to manipulate the numbers directly. In these cases, if an advertiser is given access to their data it still may not be an accurate measure of how many subscribers a podcast has.

How to manipulate podcast listener numbers.

Manipulating podcasting numbers is surprisingly easy both from the server-side and through the actual listening platforms, like Apple and iHeart. From a server perspective, there are easy ways to download a track over and over again.

Seeing a massive spike in listens on my own website years ago, I assumed a few guests had incredible networks or my podcast was mentioned in a large publication. Later I found out the real reason: As my dev team was testing my podcaster player API on my website, each “test” was logged as a listen.

A podcast creator can easily set a “minimum listen” number for every episode by entering a few lines of code on their website. It’s for this reason, analyzing how many subscribers a podcast has, even if an advertiser or partner has access to the data, might not be accurate.

At times exploiting simple page-load errors can also boost numbers. Using an embedded player function on iHeart Radio, I was able to boost a show’s listen count by 200 listens in one minute. No coding. No dev team. After hitting play on an embedded podcast player, accidentally refreshing the page at the same time, I watched the “play” button refresh rapidly. I checked the backend to see if this action resulted in listens and it did. (iHeart was made aware of this issue.)

Can You Buy Podcast Listens?

Podcast listener data can even be faked via the platforms themselves, like Apple Podcasts. It’s big business! Some brands hire foreign entities, many from Bangladesh, to inflate their numbers by mass-subscribing.

In the same way “influencers” gain artificial engagement on Clubhouse, LinkedIn, Twitter, and Facebook, they manipulate podcast listens. Click-farms exist overseas for the sole purpose of inflating numbers. Pay one of these farms, and your numbers go through the roof.

I got a real look into this world when a person, who will go unnamed, contacted me on LinkedIn with an offer to “dramatically increase my listening numbers” offering to easily get my show in the Apple Podcast top 50 list. Obviously, no one can guarantee this, so I started asking questions, eventually recording a call with him where he claimed I could get 20,000 listeners for $300. And he had evidence.

He confirmed, with screenshots and private messages, which podcasts he’s helped inflate in the past. As of writing this, some of his customers are sitting in the iTunes top 50. In the words of Buddy the Elf, they sit on a throne of lies!

This manipulation makes it difficult to know how many subscribers a podcast has.

Are podcast analytics tools accurate?

iTunes connect screen shot showing icons for: apps, artists, books, media, and podcasts connect.
iTunes Connect Portal

Platform providers like Apple and Google are making big strides to determine how many subscribers a podcast has, but they’re not ideal.

Apple specifically introduced a “Podcast Analytics” platform a while ago within its iTunes Connect platform, but it’s rough.

view of Apple's podcast analytics logo
Apple Podcast Analytics Are In Beta

In theory, the tool shows how many devices have listened, the duration, total time listened, and average time consumption per show.

Obviously, as stated above Apple is still struggling with fake overseas click-farms as well, so the data’s accuracy is in question.

Google’s new tool Google Podcast Manager seems to show signs of life as well. It doesn’t provide much more data than iTunes Connect, but it’s a good start. The platform provides plays, plays in the first 30 days, average time played, and a breakdown of device type like phone, tablet, smart speaker, etc. But it’s limited as well.

The Future of Podcast Rankings

Websites like Podtrac and Chartable claim to rank podcasts. Users can submit their data to Chartable, which is a good start, but they can’t determine what is a valid listen from a click-farm listen. If a user doesn’t submit their data to Chartable, they just scan the “top” sections, such as Apple’s top 50 and user-submitted data. As previously mentioned, these numbers are easy to manipulate as well. Hopefully, companies like Nielson will roll out products in the future.

The best advice for advertisers is to pay based on results and engagement, not based on audience size.

In the future, I hope podcasting data to be complete and unhackable, giving us a crystal clear view on how many subscribers a podcast has. But, that’s up to the platforms. As they look to monetize podcasts on their own platforms I have a hunch they aren’t going to be quick to provide this data. I hope I’m wrong.

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