Understanding podcast downloads

The term “download” can have different meanings depending on the context, but in podcasting, it refers to how often an episode is successfully delivered to a listener’s device. Importantly, as you'll see later in this article, not every play or stream is counted as a new download.

Downloads vs. Plays and Streams

Downloads measure the reach and popularity of your podcast but they differ from plays, streams, or listeners — metrics used by Spotify, Apple, or other platforms that control the client experience.

However, different actions and user behaviors can trigger a download but might not necessarily mean that a user has listened to it.

For instance:

• A listener may download an episode but not play it immediately (or at all).
• Someone might partially download an episode while streaming it online.
• Downloads can happen in the background when listeners subscribe to your podcast on platforms like Apple Podcasts.

How Does the IAB Define a Podcast Download?

That being said, the IAB Tech Lab (Interactive Advertising Bureau) sets clear guidelines for what qualifies as a download to ensure consistency across the industry.

According to the IAB:

• A download occurs when at least one minute of audio or a specified portion of the episode is delivered to a listener’s device.
• Duplicate requests (e.g., downloading the same file multiple times) and automated activity from bots or crawlers are filtered out.

How Downloads Are Counted

Aligning with the IAB standards, here's downloads are counted to 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.