Today, podcast statistics are unable to reliably measure podcast subscribers. Below are frequently asked questions that answer why subscriber metrics cannot be reliably calculated.
Why can’t I use FeedBurner or feed subscriber metrics?
Feed tracking tools allow you to measure traffic from users who are subscribed to your podcast. It is important to note that feed tracking tools primarily track when the feed is accessed. It does not tell you when an episode has been downloaded. It is common for someone to be subscribed but not download episodes for various reasons. Because of this, feed subscriptions are not a reliable way to determine if someone is listening to your podcast.
Modern podcast applications and blog readers rely on cloud-based management of feeds. Because of this, feed subscription numbers from services such as FeedBurner are not accurate. Though the data provided is insightful, it is not reliable. You will most likely have more readers and subscribers than these services can report
Why can’t we use the IP address as a subscriber metric?
Today more than one-half of podcast consumption occurs on mobile devices that commonly use multiple networks throughout each day.
For example, tracking a users behavior we found a listener using not only their home’s WiFi, but a zoo’s WiFi, followed by a McDonald’s WiFi hot-spot all within a one week period. Other users’ consumption was evenly split between their WiFi at home and the 4G service through their cell phone provider. It is more common than not to see at least one IP address per user, and typical to see two or more IP addresses over time. Because of this we never use an IP address to determine subscribers as it will result in an inflated subscriber count.
What about repeat downloads / plays from the same IP address?
Unfortunately, such a metric would be an extremely conservative of the actual number of users subscribed to your podcast.
In the beginning years of podcasting from 2005-12, Blubrry Statistics included a “repeat unique downloads” total in the reporting. You could say that this total was a bare minimum number of users subscribed to your podcast, but saying that back then was a stretch. Today with the advent of modern mobile devices, such a metric cannot be relied upon.
It is common to see shared network IP addresses download the same podcast episode multiple times. Hot spots can be found in many places such as in airports, restaurants, sporting events, etc.. Many corporations, business and government agencies use shared networks for their employees. Because of such networks you cannot assume a unique user came from such an IP address.
More importantly, individual users more often than not will download/play podcasts from various networks based on where they are at the time. It is completely possible the same user starts listening to your podcast from one IP and ends from another.
Can I track listeners with cookies?
Only in web browsers. Web browser traffic amounts to 5-15 percent of a podaster’s audience. More importantly, web browser plays/downloads are not typically associated with someone being subscribed to your podcast, resulting in this metric being a conservative estimate at best. Remember, when someone subscribes to a podcast, that podcast is then consumed within an application, not in the web browser.
We recommend using Google Analytics to track users in web browsers.
Podcast applications do not use web browser controls in their apps, these controls typically manage cookies. Instead podcast apps use libraries to download or play podcast episodes. Because of this, applications cannot accept or send back cookies on each request.
As of November, 2017 and the latest Apple iOS podcast app, there is no way to reliably set cookies to track users. There are rumors this is possible but this is not true.
What about user or device unique IDs?
Just like cookies, user identifiable IDs or device specific information is currently not included in podcast play/download requests from podcast applications. Because this data is not provided by applications, it cannot be reported.
What about my own custom podcast or network app?
You can track user IDs, store cookies and log device identifiable information in your own applications today. Unfortunately most custom podcast apps do not have enough market share to be able to report on such subscribers in any meaningful way. Remember the top three clients make up 65-85 percent of all podcast downloads,which is dominated by the Apple podcast app.
Are there privacy concerns in applications that allow user or device tracking?