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.

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