I wrote this article earlier this year, and with the original site transformed into something completely different, I thought I’d put it here for us to enjoy for years to come.
Podcasting has the same problem as television, radio, and that legendary tree falling in the forest. There’s no accurate way to measure the number of listeners.
That’s not to say there aren’t metrics. There’s are plenty of things to count – each with it’s own issues. Counting pageviews excludes listeners that only pay attention to the RSS feed. Counting hits to the RSS feed also includes directories and aggregators. Counting downloads of a specific mp3 file then shaking out duplicate requests from the same IP address and failed attempts just might provide the most accurate number of downloads – for that specific podcast.
Despite the effect this number has on your monthly bandwidth bill, it still says nothing about the number of people actually listening.
Emails, weblog comments, audio comments, trackbacks, a mention in another podcast are all great methods for measuring the hardcore fans – the people deeply affected by a podcast to act – post-listen. Arguably, these are the only listeners worth caring about. These are the listeners more apt to spread the word about you – to yet to be fans.
Personally, I’m a big – perhaps not hardcore – fan to a number of podcasts and I don’t regularly invest that level of communication. Partially because not every podcast compels me to comment and partially because it’s not always easy or convenient. Eric Larson, from the Ericast mentions the comment line phone number. I’ve called and left a message more than once. Other times, not a all. Does that mean I wasn’t there to hear it?
As a listener and podcaster, I don’t think so. Neither does AttentionTrust.org.
Why does the number of listeners matter?
Traditionally, this is what advertisers mean by ‘reach’ – the number of people exposed to a specific message. Even in the comparatively mature fields of television and radio, counting the audience any more specifically than a millions is a shot in the dark. In the internet world, browsers knows where they’ve been (browser history) and the sites visited have a similar record (server logs). AttentionTrust.org believes if more than those 2 parties aren’t involved today, they will be shortly. Though this attention data is valuable to advertisers, competitors, researchers, in addition to the the site owner and the visitor, the visitor needs to have control over how it’s shared and what level of identifiable. All in a well-formed, easy-to-share XML document.
So, advertisers care. Not everyone cares about advertisers.
A podcaster’s audience is made up of 2 groups of listeners – those driven to invest the effort of crafting and send a response, and those not. Any given listener alternates between action and apathy continually. Within the apathetic group, some will never signal their existence, others just need a method of communication with a lower barrier. This is where someone like the AttentionTrust comes in – providing tools to reduce the barriers of involvement.
Flip on the AttentionTrust AttentionRecorder and your browser clickstream history can be sent to RootVaults service and the default ACME Attention Service, or stored locally (redundant to your browser history). As of this writing, the AttentionRecorder captures HTTP traffic from the Firefox browser. In the audio realm, Last.FM’s iTunes plugin will send everything you play up to their database, where you can share it with others and find new and similar things. Like the Podcasts.Yahoo.com directory, the iTunes podcast directory, PodcastAlley, and so many others, there’s someone missing from the equation. The podcaster themselves. Each one of those services offers ratings and commenting – each distinct, redundant, and independent from the podcaster’s own site that may very well have both. As Dave Winer said about more than one RSS-like format, “two is more than twice as bad.” Each additional service shoe-horning themselves between saving listener responses increases the burden on the podcaster and the confusion for the listener.
The First Crack Podcast already has commenting & trackbacks – standard in the WordPress system and a 5-star rating system (using Owen Winklers Votio plugin
So, let’s build a little something to reduce the level of investment required to connect listeners and podcasters. Something that reuses existing information.
First off, like your web browser, iTunes (what i use for my podcast listening – though not for receiving) records what’s played and when. That’s how it populates the ‘Recently Played’ and ‘My Top Rated’ playlists. On the Mac OS X side – all the information iTunes stores is accessible through Applescript.
To access all the information about the podcasts you’ve recently listened to, open up your Script Editor and enter in:
tell application "iTunes"
repeat with theTrack in (get every track of playlist "Recently Played")
if (genre of theTrack) is "podcast" then
set theAlbum to (album of theTrack)
set theArtist to (artist of theTrack)
set theTitle to (name of theTrack)
set theRating to (rating of theTrack) as string
set theDate to (played date of theTrack) as string
set theCount to (played count of theTrack) as string
display dialog "Podcast: " & theAlbum & "
" & "Podcaster: " & theArtist & "
" & "Episode: " & theTitle & "
" & "Your Rating: " & theRating & "
" & "Last Played: " & theDate & "
" & "Times Played: " & theCount
end if
end repeat
end tell
Now, we can use Applescript to connect the iTunes ratings to the Votio plugin in WordPress. To do that, we need some common bit of information between the mp3 file and the podcast’s website. What I’ve done is put the Votio rating URL in the ID3 tags ‘grouping’ field.
"http://firstcrackpodcast.com/wp-content/plugins/votio.php?id=297&index=" for example.
tell application "iTunes"
repeat with theTrack in (get every track of playlist "Recently Played")
if (genre of theTrack) is "podcast" and (grouping of theTrack) contains "votio" then
set theRating to ((rating of theTrack) / 20) as integer
set theDate to (played date of theTrack) as string
my sendRating((grouping of theTrack), theRating)
end if
end repeat
end tell
on sendRating(theURL, theRating)
open location theURL & theRating
end sendRating
Running this script incrementally updates the average rating and total votes (listens) on FirstCrackPodcast.com for the individual episode.
In the end, it provides a very low barrier, low commitment way for listeners to tell podcasters what they’ve heard, and what they like on a per episode basis – on the podcasters own site (where this information belongs).
There are a number of ways to refine and extend this script – like integrating it into Jon Link’s iRate Dashboard widget or Last.FM’s iTunes plugin. Things are moving so fast, by the time you read this – those extensions might exist. Or, an altogether more sophisticated method.
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