This week’s installment of ‘Jakon Nielsen’s Alertbox’ has the title of “Data Visualization of Web Stats: Logarithmic Charts and the Drooping Tail“.

I got all excited at this post (before reading it) because I thought Jakob would be taking on visualization usability (is that even a concept?) however, Jakob seems to be more interested in challanging the ‘Long Tail’ theory than discussing visualization. Not that Jakob totally disagrees with the Long Tail theory, he just seems to think that it’s difficult to exploit and only a few uniquely positioned companies will be able to exploit it in any realistic way. Ok, enough paraphrasing, here’s what Jakob concludes:

It probably wouldn’t pay for our sample site to take advantage of the opportunity that log analysis revealed. The long tail’s end pays for aggregators who get their products from others, but companies who must develop their own are usually better served by staying away from the full tail.

That said, pursuing the tail’s end might be valuable if a site meets one of two conditions: it has a better way than low-value ads to monetize traffic, or it has so many users that the total income would be substantially more than the cost of developing the new functionality.

In any case, you should certainly run through such exploratory ROI scenarios for your own site. To do so, you need correct data analysis and this typically requires more advanced visualizations than you see in most places. It’s here that logarithmic plots deserve a chance — despite their intimidating name.

Ok, back to my point, Jakob’s visualizations aren’t particularly advanced, what is advanced however, or at least more advanced than what we tend to use in our everyday work, is the application of Zipf’s Law and the use of a logarithm to show how a site has a ‘drooping tail’. Which proves that if he wants to exploit the tail his example site needs to perk its tail up a bit.

I guess the key take-away for me is (and it should be for you) make sure you understand the theory (any theory) that you are applying to your site or web analytics and do it correctly. If you don’t you’ll most likely reach the wrong conclusion and that is going to be painful.

The great thing about a theorum, lemma or other model is that if you can measure something in relation to it you’re going to quickly see ‘areas of interest’ - e.g. where emperical evidence does not match the predicted value.

Via Live Science, Technovelgy and some Japanese blog that I can’t read comes this very cool gewgaw.

AMOEBA Tank Forms Letters Today, Aliens From ‘Abyss’ Tomorrow - Create letters with standing waves; will it be possible to create effects like the water aliens in Abyss sometime soon?

Talk about an amazing and inventive visualization…

Photo Source: FujiSankei Business i on the web

Creating relief images in water - that’s SO COOL!

• Web Analyst
• Data Visualization Journeyman
• Husband
• Father
• Son
• Brother
• Dog Owner
• Sci-Fi Fan
• Voracious Reader

That might be how an analyst or analytics package would summarize me so we’ll go with that.

I’ve also got to unclude the obligatory disclaimer which is that the opinions, points of view or musings expressed here are my own and are not reflective of the same at my employer, nor does my employer in any way endorse my opinions.

Ok,
so the first try was a complete bust (ugh). But I think I have 95% working solution now that’s been up since Monday night. I had to go after a completely different solution for the 3 column problem but I found it here, thanks to Paul O’brien in the UK.

Other than Avinash’s comment about this being a standard blogger design (modified to the 3 column format) - I think I’ve got most of the issues worked out. At least, the traffic hasn’t dropped to zero and I haven’t received a ton of hate-mail.

If anyone has any idea about why the most recently published post on the home page is freaking out and listing multiple copies of ghost links that aren’t actually there, I’d appreciate some help. If you check the post links on the individual post page, they look fine.

Just caught this post from David Schatsky at Jupiter Reasearch. It seems that Jup and Kagan are merging. I have to (humbly) admit that I don’t know Kagan at all (humbly because I am in the Entertainment/Media business) so I have no personal sense of whether this is a good thing or not.

I do like David’s relative frankness about why the deal makes sense from both his perspective (business)

“The overlap in our client bases is minimal, and where we do share clients, we tend to have different buyers: Kagan’s users tend to be on the financial and strategic planning side, while our users are typically in marketing (to oversimplify).”

With little overlap in their clients, they won’t be cannibalizing too much revenue.

and from the client perspective (product)

“Our business models are complementary as well. Jupiter’s business is mostly renewable syndicated research, with a hearty slice of custom research and consulting that extends and personalizes our research services and often feeds back into our syndicated capabilities. Kagan’s got a strong consulting and appraisal business–if you are weighing a deal in the entertainment and media sector, Kagan can give you a rigorous appraisal of the true value of your deal.”

Based on the above, Kagan looks like a go-to player for business development (does this deal make sense). Which adds a new dimension for Jup clients to explore/use while Kagan clients potentially gain access to a great library of syndicated research.
With David taking the President role and Tim Baskerville (Kagan) taking the CEO title, it will be interesting to see how this plays out.