Indentify increased organic search traffic opportunities in a drooping tail (speaking at SMX)

I attended my 5th Emetrics (in Stockholm last week) this year, probably making Aurélie and I the most ‘educated’ people in the industry :-) ...and Jim! - medals? :-) he he

But beyond that – I was invited to speak at SMX Stockholm at the session:

Harnessing Web Analytics Tools
Web analytics tools take raw data and transform it into a wealth of information that allows you to gain an in-depth understanding of how searchers are finding you and interacting with your web site. These tools also help you fine tune and experiment with alternative search marketing approaches, helping you maximize the effectiveness of your efforts.

Moderated by my good friend, Rand Fishkin, from SEOmoz.

Speakers:
Dennis R. Mortensen, COO, IndexTools
Jan Rencke, CEO & Founder, Destination Stockholm
Richard Zwicky, CEO, Enquisite
Patrick Price, CEO & Founder, Idealizer AG

I zoomed in on the wording “alternative search marketing approaches” and had an opportunity to bring up one of my pet subjects – the drooping tail.

Believing in the long tail concept – a plethora of opportunities arise, such as the ability to spot a drooping tail.. and taking advantage of this phenomenon to increase organic search traffic. Learn how to do this using a Web Analytics tool!

View Upload your own

Well... Back to ad:tech New York! :-)
Cheers.

Do you have a “Fat head”? (Long tail)

As a reply to my post about how to spot a drooping tail and thus create an opportunity to increase revenue, I had a great question from Greg, which I simply had to answer as part of a separate post. The question goes like this:

Q. “I don't think we have a drooping tail (organic keywords dataset). It seems like we have the opposite! Is there any meaning from such a chart?”



This is a fantastic question that I actually cannot give a direct answer to. There is not much reliable literature available in regards to the proposed “Fat Head” – where on the other hand, there is a very well documented set of theories about the “Fat Tail” – which I would like to go into detail about later (from a “Making more money” point of view).

That said, we (as in me on Greg’s behalf) could assume that there is an “artificially” increased demand for those 4 or 5 outliners in his dataset that represents the “Fat Head” due to specific circumstances (aggressive SEO optimization on those words in particular, etc.)

On the contrary, the essential question is whether the form of the function in the middle part of the head, in the first place, can give any reliable estimation about the behaviour of the head itself. This reliability question cannot be answered by assessing this individual case; it requires the careful evaluation of various diverse cases.

Finally we should remember that there are some fundamental limitations using Zipf's law as the “truth” for all given business models. You even see some uses of the long tail theory deliberately delete head and tail outliners.

So to conclude: Looking at the above data, I think we have a near perfect distribution and that we do definitely not have a drooping tail and the “Fat Head” is most likely “just” an effect of artificially increased demand for 4 or 5 keywords.

Cheers and thank you very much for a great question like this!

N.B.

I am very open to other interpretations of the indicated Fat head, so you are more than welcome to email or comment critically on this. :-)

9 Ways to Make Money on Analytics

Eric Enge had a great post over at Search Engine Watch and with a title like this: 9 Ways to Make Money on Analytics - I just had to reference it here. This being a blog about how to increase publisher revenue through analytics! :-)

..And on top of that; I am of course proud that he chose to add my “The Long Tail (drooping tail theory)... and how to calculate missing Revenue” as tip #5:

“Spot a missing long tail: There was a great post recently by Dennis Mortensen about Spotting a missing long tail (another person whose blog you should read on a regular basis). Dennis explains it really well, but the basic idea is that the traffic on your highest volume page should be matched by the traffic on a larger number of lower volume pages on your site. If this is not the case, then you are missing out on an opportunity. Check out Dennis' post for more details on this suggestion.”

Go check out his post.. it is always worth having a look at what Eric has to say.

Cheers... off to Emetrics San Francisco.

The Long Tail ... and how to calculate missing Revenue

Inspired by Avinash’s “long tail” post today I thought it would be appropriate to take it a step further and indicate how you as an affiliate with revenue generation based on content can calculate how much revenue you are leaving on the table - spotting a drooping tail. I know this is going to be a bit long haired, but stay with me for a second.

First lets draw our own graph (based on an anonymous dataset from the perfect IndexTools client).

Graph: "The number of visits per page" - the homepage got 16241 visits in the given period and was the most popular page




This is the traditional Long Tail graph, telling us that a few pages generates a lot of traffic, BUT the same amount of traffic is generated by a large pool of lesser visited pages. Without going into detail, I think we can agree that it is fair to assume (just by looking at it) that a standard long tail distribution as the above is inversely proportional and thus follows Zipf's law. With that said, let’s try to plot the same information into a double-logarithmic chart, to confirm that we indeed have a straight line.




I think it’s fair to say (from this perfect dataset) that we do indeed have a straight line and thus a distribution that follows Zipf’s law. However; let try to look at a less perfect dataset, another IndexTools client, who will not know how much revenue they are leaving on the table, if they are using traditional long tail linear graphs visualizations. I will have Sales call them up tommorow ... :-)

Graph: "The number of visits per page" - the homepage got 319270 visits in the given period and was the most popular page



And by looking at it (using a linear graph) – everything looks "normal" and I could assume that this is the traditional long tail distribution. But using a double-logarithmic chart, we all of a sudden see that there is a drooping tail.





And if we keep the assumption that the long tail should be inversely proportional and as indicated follow Zipf's law – we are missing something here. And what we are missing is more CONTENT! – this client simply do not have enough content to support the long tail.

We could therefore say that additional content would increase Revenue. With the above as an example, the perfect distribution would roughly add an additional 1.7M visits per week, it would also mean that they had to move from 3600 something content pages to more than 300.000+ content pages.

For the fun of it, let’s assume (based on my latest Google AdSense experience) that you have an average ECPM on $2 and that each visit resulted in 5 page views. That’s a $17000 per week revenue increase!! – whether this offset the cost of creating 300.000+ pages is another debate.

But we should have in mind that this approach is not just for Content Pages – it might as well be for keywords (as Avinash used in his post), referring URLs and other metrics generating the typical long tail distribution.

Conclusion:
There is a Revenue opportunity in the dropping tail that most content sites miss out on – because they do not have optimal reporting on their data.

NB:
If you are an IndexTools client and this does not make sense – Add a comment (including your account name) – and I, ..probably outsourced to someone else. :-) will show you how to do the right exports and Excel setup’s to see if YOU are missing out and whether you have a drooping tale opportunity.

.