There’s nothing like a good holiday for a good read.
On mentioning I was looking for reading material, a colleague thrust a copy of The Long Tail into my sweaty palm. It’s a revelation. I know it’s easy to get excited by these things – especially when you come to them late, like I have, and tend be a bit over-excitable by nature and start seeing long tails everywhere – but, well, I keep seeing long tails everywhere. Particularly – and notably – in the PowerPR index.
This shouldn’t come as a surprise. I would have expected a few blogs to carry a lot of traffic and then for it, quite literally, to tail off, but when you chart the metrics – any of them, all of them, combinations of them – you constantly get a long tail. In fact, it looks exactly like this (from Excel):
I’ve removed the figures because they don’t really matter – trust me, the curve looks the same no matter which figures you use, with the exception of Google Page Rank which doesn’t have the range of, say, Technorati Authority or Yahoo links.
This is interesting because it bears out my recent thinking on the latest issue of the index: that there are three ‘super blogs’ out there, the ‘superest’ being Micro Persuasion followed by Online Marketing Blog and the Center for Media and Democracy. Part of me wonders whether, by including them, I’m comparing apples with pears here because they seem to have a different nature from the rest. But then where do you stop? If I take them out, the next three or four will leap out and become the new heads, Hydra-like.
So, quick thoughts on this (it’s late because my body clock’s gone wrong after the holiday):
- I love the way this works according to my rough understanding of what a long tail is. No score is zero: everyone has been read/ hit/ indexed so that someone, somewhere has given them a score. This is because it is equally easy to find anything. My PR feed, for example, is aggregating them all as we speak. Shel Holtz may be influential but that’s not to say that Spudgun doesn’t have something interesting to say too. We just need to filter out the noise to identify the tail.
- Does this imply that I gain equal value from following the tail, as I would the three ‘hits’ of the head? If I look at the total figures there’s an equal divide between head and tail midway between the third and fourth plots on the chart. So, quantitatively this implies that I have as much ‘value’ in the tail as I do in the head. Given filtering/ aggregation/ indexing etc, does this work qualitatively too?
- I strongly suspect long tails are fractal. I haven’t actually finished the book yet but I’m hoping somewhere this will be raised. For example, Teaching PR doesn’t come very high in the PowerPR index but if I built a blogroll of blogs concerned exclusively with PR studies I’m confident another long tail would emerge. So, for every niche there’s another tail: every niche can also be a hit. People will also have their own long tails. Perhaps I should finish the book first.
- If we’re dealing with a long tail then this might account for why getting the figures to behave like a normal distribution didn’t work, because it isn’t one. However, this could just be a case of how you approach the plotting: longtail.com probably has the answers, if only I understood the question.
- This still raises the problem of how to provide meaningful illustrations of these figures. This page might help, but then again I see the alphas, betas and brackets and get scared, like a tiny white rabbit.
The other two books I read were the God Delusion – in every way the real version of Oolon Coluphid’s ‘Who is This God Person Anyway?’ – and, an impulse buy, Riding Rockets, the best way to find out what it’s like to be catapulted into space while wearing a nappy without actually suffering the indignity. Neither of them are particularly applicable to PR, copywriting or tech but I thought I’d mention them anyway.
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