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RSS / Longtail post - update

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Chris Anderson, editor-in-chief of Wired Magazine. who wrote the original The Long Tail acticle, has highlighted my RSS / Longtail post on his blog.

"Alex Barnett does some analysis on his blog traffic and discovers that the RSS feed flattens the curve. Because the feed "pushes" all the posts to readers, more of them get read. So there's less inequity between the popular and unpopular ones. Also: "at least 80% of the traffic I get to posts after 3 months are via the search engines that match niche content with niche interests - the Filters of the web. The rest of the traffic comes after 3 months, from referrers from other blogs and online resources (articles, guides, lists of useful links on a subject, etc.)" "

I'm showing off now, but hey, I'm proud :-)...I join some interesting name Chris quotes on the subject of the Long Tail (there is feed to his quotes list - see left sidebar of his LT blog): David Weinberger (author of the outstanding 'Small Pieces Loosely Joined' and co-author of the Cluetrain Manifesto) Joshua Allen (recent discovery for me, love his blog, Bokardo), Seth Godin (author of 'All Marketers Are Liars'), Mark Cuban (serial entrepreneur and billionaire) and Bob Frankston (co-creator of VisiCalc).

Another name to drop is Jakob Nielsen who posted the following comment on my How RSS thickened my Long Tail post (he's commented before on my blog):

"It's quite likely that your pageviews follow a Zipf distribution with classic long tail usage, since most websites have worked this way since at least 1996 (the first time I analyzed such data).

However, it would be easier to evaluate your data if you plotted the data on log-log diagrams (i.e., logarithmic scales for both x and y axes). See my essay on Zipf Curves and Website Popularity for sample charts. Basically, if the data shows as a straight line on log-log plots, then you have the expected distribution. If the curve droops on either end, then something else is going on. (See example at the bottom of the above reference with a plot from a site that had 10,000 pages in 1996 and needed 200,000 to fully meet the long tail requirements.

By now, I think this site is fully compliant, but I don't have its recent data.) A second question: what do you mean by "RSS views"? Is this number of times a page was *seen* by an actual human or is it simply the number of times it was downloaded by RSS software? It needs to be user-activated clickthroughs to be comparable with traditional pageviews."

Jakob - I'll look up the essay and re-run the numbers as you suggest. On your question of the definition of 'RSS views', this is defined by the number of times each item was viewed (NOT how many times the RSS file has been pinged - this is a different number I did not analyze).

You say "Is this number of times a page was *seen* by an actual human or is it simply the number of times it was downloaded by RSS software? It needs to be user-activated clickthroughs to be comparable with traditional pageviews". I respectfully disagree with you on this point - getting RSS clickthroughs would then also count in the PVs log, because a PV would register with each clickthrough). I'm interested in the number of times each item was viewed - so PVs + RSS views = total views per post/item. RSS-generated clickthroughs, although a good metric to measure, is beside the point of my post).

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