Archive for the 'podcast' Category

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At last: car stereos with frontal mini-jacks

Published on December 29, 2005 in podcast. 4 Comments

JVC car stereo with line-in
You need portable MP3 player for when you’re on the move. On the move includes: in the car. Why would you want to listen through tiny white earphones, if you have dozens of Watt of pure musical power already at your disposal in that car of yours? Or: how to connect your iPod to your car stereo.

FM Transmitter

First of all, they’re illegal in Belgium, so you can’t buy them anywhere here. Thanks to my numerous maffia friends however, I’ve been able to try 2 Griffins and a white-label gizmo, but my experiences have always been disappointing: impossible to tune right or get an acceptable sound.

Fake tape

There are these cassette look-alikes that you can put in your tape player. Only, who still has a tape player in his car? And what does the conversion electric-to-magnetic-to-electric do for your sound quality?

Custom interfaces

Alpine has a special solution for iPod (didn’t BMW have something like that too?), but we don’t like vendor lock-in.

Line/Aux in

  • One year ago I had already talked about Kenwood making car radios with line-in possibility. But Kenwood used the RCA jack on the back of the device, which might have been a good idea in a hifi-stereo world, but not so for portable audio players.I wanted a mini-jack, damn it, but no vendor had that.
  • But now: behold the mini-jack!
    - Sony has the CDX-GT200 (about € 130) and its bigger brothers CDX-GT300 and CDX-GT400 (not in Europe).
    - JVC has the KD-G612 (bout € 150) with “Front AUX Input”, as well as the KD-G510 or KD-ADV6160 (last one even plays DVDs)

I hope the rest of the vendors get the message and provide a frontal AUX in on their products. Car stereos, boomboxes, mini-chains, DVD players, DivX players, …
Rip, Mix, Plug it in!

Technorati: – – –

Christmas present: podcast feed validator!

Published on December 25, 2005 in podcast. Closed Tags: , , , .

I get a lot of “what is wrong with my podcast feed?” kind of questions because I have written a fairly popular tutorial on podcasting with Blogger and Feedburner, and a lot of people start doing podcasts that way. There’s a couple of things that can go wrong:

  • Not a valid RSS feed
  • RSS feed without enclosures
  • Feed not updated when posting new article
  • …

To check some of those things, I needed to read and interpret the RSS feed by hand. That’s why I decided to make a podcast feed validator to do the checks automatically. Let’s take Adam Curry‘s DailySourcecode podcast as an example:

  • the URL of the feed is radio.weblogs.com/ 0001014/ categories/ dailySourceCode/ rss.xml, so I input it into the input field and the results are:
  • #1: feed URL exists and can be reached
  • #2: feed is a valid RSS feed (but does not conatin the iTunes extensions),
  • #3: feed items have audio enclosure (but not all, as you see in the image below. The reason is that two enclosures are wrongly specified as text/html instead of audio/mpeg.)
  • #4: the audio enclosure (MP3 file) exists and can be reached

podcast feed validator
So the enhancements for this feed would be: make sure all enclosures have the right type, and provide iTunes meta data. Better still: use Feedburner to get that and more: subscriber statistics and lots of feed tools.

Try it out for yourself:
Check your podcast RSS feed!

Some more features of the podcast feed check:

  • estimation of mean-time-between-posts (MTBP), a metric I talked about in RFM for RSS feeds
  • estimation of required bandwidth/storage per month (DailySourcecode: 600MB/month, 175-25.be podcast: 10MB/month)
  • works with MP3 audio enclosures and AAC (MPEG-4) audio/video enclosures (any audio/mp* enclosure)
  • detailed (technical) information is hidden by default and can be shown through some AJAX functionality.

Technorati: – – – –

New podcast icons based on Firefox/IE feed logo

Published on December 16, 2005 in podcast. Closed

Original Firefox feed iconYou might have heard that the Microsoft IE team (and Outlook 12 team) is adopting the orange square ‘feed’ logo for its web feeds:

I’m excited to announce that we’re adopting the icon used in Firefox. John and Chris were very enthusiastic about allowing us (and anyone in the community) to use their icon. This isn’t the first time that we’ve worked with the Mozilla team to exchange ideas and encourage consistency between browsers, and we’re sure it won’t be the last.
(from blogs.msdn.com)

So I decided to update my previous podcast logos with the new graphic:
(If you want to use them, and need the HTML code to copy/paste, check my podcast icon wizard)

Simple icons

Podcast RSS (generic): Podcast RSS (generic)

Audio podcasts

Audio RSS: Audio RSS
Audio RSS (Apple iTunes AAC): Audio RSS (Apple iTunes AAC)
Audio RSS (MP3): Audio RSS (MP3)
Audio RSS (QuickTime MP4): Audio RSS (QuickTime MP4)
Audio RSS (Ogg Vorbis): Audio RSS (Ogg Vorbis)
Audio RSS (RealAudio RAM): Audio RSS (RealAudio RAM)
Audio RSS (Windows Media WMA): Audio RSS (Windows Media WMA)

Video podcasts

Video RSS: Video RSS
Video RSS (Windows AVI): Video RSS (Windows AVI)
Video RSS (DivX): Video RSS (DivX)
Video RSS (Quicktime MOV): Video RSS (Quicktime MOV)
Video RSS (Quicktime MP4): Video RSS (Quicktime MP4)
Video RSS (Quicktime): Video RSS (Quicktime)
Video RSS (Windows WMV): Video RSS (Windows WMV)
Video RSS (XVid): Video RSS (XVid)

If you want to know whyI don’t use the acronyms “RSS” or “XML” in the icons, check Web feeds are like RSS, only different.

Technorati: – – – –

RFM for RSS feeds: Recency, Frequency, Momentary Value

Published on December 13, 2005 in podcast. 2 Comments

I’ve been throwing round an idea in my head for a while: how the RFM method for analyzing and prediction customer behaviour could be applied to RSS feeds (blogs, podcasts, …).

Recency, Frequency, Monetary Value – customer segmentation

What does RFM do: it analyses 3 parameters for each customer:

  • date of last purchase (recency)
  • # purchases per month/quarter (frequency)
  • average amount of money spent per purchase (monetary value)

It then does a cluster analysis of the numbers (or in the simple version: a marketing guy decides based on gut feeling) and defines boundaries for each parameter, in order to split them up into categories.

Example:
Recency: R1 is everyone who purchased in the last 2 months, R2 is everyone who bought in the last year and R3 is the rest.
Frequency: F1 is every customer that purchased on average 3 or more times per quarter, F2 purchased at least 1 time per quarter and F3 is the rest.
Monetary Value: M1 are those who purchased more than �500 per visit and M2 are the rest.

In this scenario you have split up your heterogeneous customer group into 18 (3x3x2) more or less homogeneous subgroups that you can address in different ways. Your supercustomers R1-F1-M1 don’t need the same approach as the R3-F2-M1 (the big spenders that haven’t been around to your shop in the last year). And you hope you can predict the behaviour of each customer by analyzing his past behaviour.
(Side note: I learned this stuff while working in Sopres for Stefaan Vermeiren, who’s now teaching the Kiwis to do online banking)

RFM for RSS – feed segmentation

 

Now how would this work for RSS feeds?
RFM analysis for RSS feeds

  • Recency: date of last post
  • Frequency: average # posts per month, or mean-time-between-posts (important is that you only take into account the period from the first to the last post: if the feed contains 1 item per week but the last one was 1 year ago, the frequency is still 1/week i.e. around 4/month)
  • Momentary Value: (I know ‘momentary’ is not a great term, just couldn’t come up with a better 4-syllable alternative for ‘monetary’ yet) this is the most creative part: you can count the # of words, # of links, # images, filesize of the podcast audio or the video file, …

What can you do with this kind of statistic? Well, I see some applications:

  • is a blog ‘alive’? when do you decide if a blog is no longer active: it will be a combination of recency and frequency. If someone posted 1/week and there has not been any activity for 2 months: probably (momentary) dead. If someone posts 1/quarter and no activity for 2 months: perfectly normal. In statistic terms: calculate mean-time-between-posts MTBP and standard deviation STDEV. If the last post was MTBP days ago, there is a 50% chance that the feed is no longer updated. If it is (MTBP + STDEV) days ago, then the chance is 84%. (MTBP + 2 * STDEV): 97%, etc …
  • what kind of blog is it? if average # words/post is low, and # links per post is around 1 (and frequency is 1/day): it’s probably a linkblog (like e.g. bnox). If the #words/post is high, the MTBP is 1 month with a very low STDEV, it is probably a monthly newsletter.
  • do I have time for this blog? Now you subscribe to a blog without an idea of how often the author posts, and how long the articles are. With an RFM analysis, the blog could be marked as ‘low traffic’ (2 posts of 500 words per month) or ‘high maintenance’ (60 posts of 300 words per month).
  • how much data does this podcast deliver? There is a big difference between a show like DailySourcecode (about 20 podcasts of 40MB per month: 800MB/month) or IT Conversations (2 posts/day of 14 MB each: 840MB/month) and a humble effort like my Mash-up podcast (2 to 5 posts per year of 4,5MB: 1,5 MB/month). For a mobile device, where storage and bandwidth aren’t so readily available (nor cheap), this is an important distinction.

This RFM analysis could be done by a company like Technorati, Bloglines or Feedburner, and they could combine it with language, location, topic and popularity stats to create an excellent segmentation of blogs. Or if someone feels tempted to set it up?