Looking for the Podping.cloud project from Podcast Index? Please refer to their website for more information.
The podcast industry is continuing to grow at an impressive rate. But one thing that is frequently cited as holding it back is the difficulty with which accurate metrics can be obtained.
Several apps have implemented their own measurement systems, but each exist within their respective walled garden. None of these systems are interoperable and therefore lack offering a comparable or complete picture of podcast listening.
So, based on a previous exploratory idea, the team at Aiir have developed "Podcast Pingback", a method for reporting listening activity back to a podcast publisher.
The idea is intentionally simple. A podcast client can obtain a URL from inside an existing RSS XML feed that can receive simple "pingback" HTTP requests detailing key events; when the playback starts and when it pauses or stops. Beyond that there's additional optional meta that can be attached, such as if playback has been sped up or "enhanced" by the client and (subject to consent) some profile information on the listener.
Our work at Aiir is focussed around building innovative, easy to use products, to enable broadcasters to manage content whilst growing audience and revenue, all in one place. This means we know first-hand how making our clients audio more accountable is crucial for the future of podcasting. And if this is true for broadcasters exploring podcasting as a new revenue stream, it follows that it's even more important for those podcast innovators where it's one of their only revenue streams.
The grand ambition is simple; to get an open, interoperable analytics method embedded in as many clients and used by as many publishers as possible. It's a big one, and there's a huge elephant in the room, but we have some core beliefs that drive this ambition:
You might be thinking "great time to try and launch a snooping protocol to a suspicious public"? We take privacy concerns very seriously, but there's no getting around the fact that one of the desires for these analytics is to support the "evil" act of money making to support creators.
Spot and read advertising are unlikely to go away anytime soon and the arguably more controversial personalised or heavily targeted advertising is out of scope. The method revolves around an anonymous unique identifier derived by the client and the inclusion of a listener profile is optional and intended to be under a user consent agreement. The only way it can be obtained is by a client supplying it, which would raise a broader question of how the client obtained it before even passing it to the publisher. Finally, a "forget me" user flow was included to ensure a listener is always in control.
Check out the specification now. It relies on being adopted by publishers and software developers alike. If both points ring true and we see the adoption of a standard we can move the whole industry forward with a more complete view of the consumption of our content.
We're keen to receive feedback and engage the community in the future development of this spec. Please feel free to look at and fork our GitHub repository for the site and submit pull requests, or get in touch to discuss the specification further.
27th April 2018