Over in the UK, Will Page, who works for the copyright collection society there, presented some interesting data at a music conference last week that suggests that the Long Tail's usual powerlaw shape doesn't fit the sales they're seeing.
I can't find his presentation online [UPDATE: there's more information in a long interview with him here], so I have to go with the good coverage by Yankee Group analyst Benoit Felten and the comically angry coverage of The Register. The basics are that Page and the founders of Mblox, a mobile music provider, presented research that showed that a dataset of the sales of 13 million tracks showed a lognormal distribution, rather than the usual powerlaw, and as a result the total sales in the Tail were lower than the theory would predict.
Here are the two specific datapoints that came out in the coverage
- 80% of the revenue came from the top 52,000 songs (which is the inventory in a typical music store, my definition of "head"). In my own Rhapsody research, only 60% of the downloads were in top 52,000. So the tail was half as big in their dataset as it was in mine.
- Of the 13 million available tracks on iTunes UK, 10 million don't sell at all. They don't say over what period.
And here are my three thoughts on that:
- Page did not reveal where the data came from. Felten suspects it was iTunes UK, but given that Page's partner in this research was Mblox, a mobile music provider, it seems more likely that it was a mobile carrier or their partner. If so, this is nothing new. I've already discussed why the Long Tail doesn't work for mobile music, due to the lack of good "filters"--easy search, recommendations (social and otherwise) and sampling methods--on such limited devices.
- If it is iTunes UK, that would be a little bit more surprising, and I'd need to look at the data to see why it didn't follow the powerlaw shape that we saw in the data from Rhapsody (another digital music provider). It could be that the pay-per-track model discourages risk-taking and exploration of new music, which is not an issue with Rhapsody, which uses an all-you-can-eat subscription model. It could say something about iTunes' less effective music recommendation tools. Or it might just mean that the UK iTunes consumer is not like the US consumer.
- I've discussed many times that some markets that look like Long Tails (powerlaws) may in fact be lognormals, both in the book (Chapter 8 Notes) and in speeches and here on the blog. The two distributions look similar at first glance, and you have to plot them log-log (or fit them with a statistical package) to tell the difference. Long Tails are "heavy-tailed" distributions, where a lot of the total volume is the tail, while lognormals are more like the classic top-heavy hit distribution. The theory (and the Rhaspody) data puts music the powerlaw camp in a marketplace with vast choice and good filters, but it would not be a surprise to find that in markets with poor filters, music demand reverts to a lognormal.
Unfortunately, Page didn't send me the data or reveal its source, so we may not be able to answer these questions. He's a good economist, so I'm sure his analysis is excellent. But without knowing where the data came from, we really have no way of knowing whether he's discovered anything about music demand broadly, or has just been reminded once again that some music markets, such as mobile, don't work very well.
Search: LT is huge
Finally, just a reminder that the Long Tail effect is seen in many markets, not just music. One of the best examples is search, and Google is usually held up as the largest company based on monetizing the Long Tail. Over at the Hitwise site, Dustin Woodard has a new post with some data (sample below) that shows why this is.
In a study of 14 million search terms, he found the following:
- Top 100 terms: 5.7% of the all search traffic
- Top 500 terms: 8.9% of the all search traffic
- Top 1,000 terms: 10.6% of the all search traffic
- Top 10,000 terms: 18.5% of the all search traffic
This means if you had a monopoly over the top 1,000 search terms across all search engines (which is impossible), you’d still be missing out on 89.4% of all search traffic. There’s so much traffic in the tail it is hard to even comprehend. To illustrate, if search were represented by a tiny lizard with a one-inch head, the tail of that lizard would stretch for 221 miles.
The truth is my research is still greatly understating the true size of the tail because:
• The Hitwise sample contains 10 million U.S. Internet users and a complete data set would uncover much larger portions of the long tail.
• The data set I used filtered out adult searches.
• I only looked at 3-months worth of data (which were some of the slower months for search engines).
In summary, the long tail aspect of the search is true, but the data tells us that there may really be no head or body. When it comes to search, virtually all traffic is long tail and the word “long” doesn’t do the length of the tail justice.