Why Feed Hits and Monthly Downloads are Meaningless Podcast Stats – TAP330
Feed hits and monthly downloads are two podcast stats the may confuse or mislead podcasters. Here's why you should never rely on these meaningless numbers. Why feed hits are a meaningless stat Every time a podcast app check for new episodes, it's checking for updated information from your RSS feed. That counts as a feed hit each time. Tools like FeedBurner, FeedBlitz, and some startup podcast hosting companies may offer stats on how many times your feed is loaded. But such a stat doesn't tell you the true size of your audience, for the following six reasons. 1. There is no measurement standard Unlike the industry standard we have for measuring podcast downloads, there is no association setting a standard or guideline for measuring feed hits. For example, should only full downloads of the feed be counted, or should head requests (probably checking the “Last-Modified” date) be counted, too? 2. Apps refresh feeds throughout the day Whereas a podcast episode is usually downloaded only once, a podcast RSS feed will be loaded multiple times. Some apps refresh the feed every hour. Some apps refresh even more frequently than that! This then requires more filtering to reduce the excessive duplication by IP address. 3. There's no way to track a single device across multiple IP addresses Speaking of IP addresses, most mobile devices will probably have at least three different IP addresses in an average day: one for home, one for work, and one for mobile. But there could be even more if your mobile device automatically connects to additional wifi networks (such as a store, a coffee shop, a friends house, etc.). And if you leave a particular region, it's likely your mobile data provider will give your device a new IP address as the location changes. For media downloads, this kind of IP address behavior can be accounted for with some different filtering and crossreferencing. Even at the simplest level of measurement, podcast apps will download an episode only once unless the user forces it to redownload. But since mobile devices refresh the feeds throughout the day and their IP addresses change as their location changes, a single device could show up as multiple devices based on RSS feed hits. 4. Feed traffic varies every day Podcast RSS feeds are only checked based on app settings and user interaction. This usually results in lower activity on the weekends. Measuring RSS feed hits would make it seem like your audience unsubscribes on the weekends. Many website statistics tools, such as Google Analytics, will track a user across multiple visits, so it's easy to see how many unique visits you had across time (such as a week or month). But FeedBurner and other RSS tools don't offer such tracking, and thus report only a daily number or an average across days (but not tied to actual users). 5. Feed stats exclude non-RSS plays Trying to measure “subscribers” raises the question, what really is a “subscriber”? While it may seem reasonable to say anyone who has pressed “Subscribe” on your podcast is a subscriber, that excludes many loyal audience members. Some people will faithfully visit your website and press play on your latest episodes. Some people will watch or listen on social networks. Some people will add your podcast to their app without actually subscribing to it. Some people use apps or services that subscribe to your feed only once for thousands of users (such as Stitcher, iHeartRadio, or Google Play Music). People on those platforms could still be loyal consumers of your podcast, but they're not individually subscribed to your own RSS feed. Thus, anything that tracks you audience through RSS hits or downloads will not count any of these other loyal fans. 6. iOS 11 refreshes feeds repeatedly (possible bug) Lastly, Apple Podcasts in iOS 11 introduced some strange new behavior regarding podcast RSS feeds. This is resulting in a significant increase is feed hits since iOS 11. A significant increase in feed hits started with the release of iOS 11 on September 19, 2017. (Weekend dips removed for clarity.) While there are different theories to explain this, we do not yet know whether this is an intentional design by Apple or a bug in the app. But we can compare these daily feed hits to daily downloads and see this increase is not an actual increase in audience. Why downloads per month/week/day is a meaningless stat You'll often see podcasters speak highly of their downloads per week, per month, or per day. While some numbers can be fun to celebrate (my own Noodle Mix Network reached 15 million total downloads in Fall 2017), these “downloads per time” (DPT) don't really mean much; they don't tell you any truth about the size of the audience! Here's why. 1. It's not enough information Downloads per time tell us nothing about the podcast's actual reach. It doesn't tell us how many episodes were published, how many episodes were already available, how many people downloaded episodes, or how many episodes people downloaded. Downloads per time would include downloads for new episodes released during that time and all old episodes also downloaded during the same time. For example, if I say I delivered 10,000 downloads in a month, that may sound impressive until you learn that I published 10 episodes that month and I have 1,000 episodes in my back catalog. But even with that information, you still can't calculate the audience size, because these numbers don't tell you how many people downloaded your episodes. It seems most podcasters like to share this meaningless number because it's an impressive number or they don't understand the lack of information. 2. It will always be changing You may think downloads per time will grow with your podcast, but that's not the case. Downloads per day, for example, will always be highest the day you release your latest episode unless you publish late in the day. Weekends will be low for some shows and high for others. Downloads per week or per month will also change based on how many episodes you published or skipped during that time. Trying to account for these constant changes could drive you crazy! 3. It's easy to inflate without growing the audience Here's a little secret. Want to double your downloads per month? Simply publish twice as many episodes! Or, go from publishing weekly to publishing daily and septuple your downloads per month! While these things will increase your downloads per time, the inflated stat does not reflect an increase in actual people consuming your podcast. In other words, you can increase your downloads without ever growing your audience (episode 260). 4. It's misleading to advertisers Absolutely don't use your misleading downloads per time stat to entice a sponsor! They may expect their ad to receive that same reach, but because of these reasons I just shared with you, your actual reach could be a much, much smaller portion of that impressive number. This is because most advertising will be put into only specific episodes. There are some dynamic ad-insertion technologies that can put an ad into every episode in your entire catalog, but setting that up can be complicated, especially if you didn't prepare for it with all of those episodes. Plus, dynamic ad-insertion can feel even more disruptive to your audience. How should you measure your audience? The industry standard we've had for years is downloads per episode (DPE), typically 30 days after release. But raw download logs are still not accurate. That's why Association of Downloadable Media (ADM) many years ago and Interactive Advertising Bureau (IAB) more recently have created podcast measurement guidelines. These account for things like partial downloads, bots, public IP addresses, user-agent filtering, repeat downloads, and much more. Blubrry, Libsyn, Podtrac, and soon Spreaker, contributed data to and are in compliance with these agreed-upon industry standards. That's why you hear these companies recommended by professionals—we know we can trust these companies to uphold the standard and conform where necessary all in the interest of accurate measurement, not impressive data. Thank you for the podcast reviews! 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