Understanding podcast downloads

Modified on Wed, 4 Sep at 12:36 AM

The word “download” can mean so many different things depending on the context it is used.


When we talk about “downloads” in podcasting, it’s important to clarify what we mean. A download represents the number of times an episode is accessed or played by listeners. However, not every play counts as a new download.


Downloads vs. Plays and Streams


Downloads are a direct measure of your podcast’s reach and popularity, but they differ from plays, streams, or listeners. For example, someone might play your podcast and download it partially, or they might download an episode and listen to it later, possibly on multiple devices.


The IAB Tech Lab explains it like this:

Podcast downloading allows the audience to download full episodes of content that can be played at a later date and time. Listeners may subscribe to select programs, and platforms like Apple Podcasts continue to support full downloads to a personal library for listening offline at any time in the future. The convenience of this system makes downloaded podcasts a continued preference among listeners.


How Downloads Are Counted


The definition of a download is clear, what does mean on the user end not so much. Understanding how downloads are counted can help you get a clearer picture of your audience’s engagement:

  • One Download per Device: Each time someone starts listening to an episode on a device, it counts as one download. If they start and stop the same episode multiple times on the same device, it still counts as one download. This prevents inflated numbers from repeated plays.
  • Switching Devices: If a listener switches to a different device to continue listening, each device counts as a separate download. This helps track unique listeners accurately.
  • Filtering Out Incomplete or Duplicate Requests: Partial requests and duplicate entries are ignored to ensure only genuine downloads are counted, making the numbers more reliable.
  • Tracking IP Addresses: We exclude duplicate IP combinations to avoid counting multiple downloads from the same source, enhancing accuracy by effectively filtering out duplicates.


RSS.com Analytics


RSS.com provides industry-leading analytics to podcasters. Our analytics follow state-of-the-art industry guidelines to measure podcast metrics.


Here’s how our analytics service works:

  • Data Collection: When a listener downloads an episode via platforms like Spotify, Apple Podcasts, Google Podcasts, or Amazon Music, they leave a footprint in our system through a “log.” These logs include data such as the IP address (used to determine geolocation), device and operating system used, and specific files downloaded.
  • Automatic Processing: We have automatic processes in place to continuously process, analyze, and distribute data extracted from our logs. This data is provided to our users via the Analytics tab in the podcast Dashboard.
  • Metrics and Insights: Some metrics are straightforward calculations (e.g., total downloads), while others (e.g., Rolling Average Subscribers or RAS) are statistical inferences based on certain assumptions.


Key Metrics


The most important metric is the number of downloads. To ensure accuracy, we take a conservative approach by filtering our logs to exclude false positives, including methods to identify duplicates. This avoids inflated metrics and it is part of the technical guidelines for podcast measurement by the IAB Tech Lab.


Since we host your podcast episodes, we measure downloads across all podcasting platforms. For example, if you receive 50 downloads from Google Podcasts and 50 from Apple Podcasts, our analytics will show a total of 100 downloads.


Utilizing Analytics


This information allows you to assess the overall performance of your podcast, including your RAS and listener geolocation. For example, you can use your RAS to identify patterns that can help you maximize the reach of your show, such as peak downloads by weekdays and hours. Or create region-specific content targeting your most engaged cities.



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