More Long Tail debate: mobile music no, search yes

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:

1. 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.
2. 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.
3. 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.

Comments

[Sprizouse]

I just analyzed a Harvard case study about Haier, the Chinese white-goods manufacturer, for my Global Business Strategy class (I'm an MBA student).

It's a classic long tail case and one you might want to read (I think it's only 8 pages long). It's titled: Haier: Taking a Chinese Company Global.

What I noticed from reading the case was that Haier's long tail model came to them organically. The humongous and diverse Chinese populace forced Haier to adopt a long tail strategy that was able to quickly adapt fridges, washers and dryers to the varying needs of a billion people spread across China’s many demographic markets. I think we, in the west, tend to think of the Chinese and Indian populations as largely homogeneous, but they're not. They’re not even close to being homogeneous in fact.

Anyway, in some of the more rural markets in China, Haier discovered the people were using their washing machines to wash potatoes and beets as well as clothing. Haier had been answering service calls to fix clogged drains and broken washers (from the caked mud) so they created a washing machine capable of washing food as well as clothing. This was just the beginning.

Haier created an innovative modular system for building a bunch of customized products quickly and easily (which you should read about in the case) and now the company is growing at remarkable rates. The question this posited in my mind (and the one I posed to my professor and the class) was whether or not certain industries from certain countries were being forced into long tail economics by their own populations? If so, would these companies gain an advantage over traditional western companies that served much smaller and more homogeneous populations?

As I realized from the Haier case, no matter how Haier arrived at their long tail strategy, it has helped position them to possibly become America’s white-goods leader in the next few years (especially since current western manufacturers seem loathe to adopt long tail strategies).

The digital long tail isn’t the only long tail (as you so excellently noted in your book) and I personally believe western companies are in real trouble if they don’t adapt rather quickly.

Your thoughts?

[C. Enrique Ortiz]

Isn't the whole issue here interpretation of the LT or how it is being applied?

For example, when popular products are introduced, they will at first generate lots of revenue (volume) at the Head part, but *over time*, most or all of the revenue will come from the LT.

And that LT is directly proportional to popularity and awareness (or lack of).

And, that LT distributions can repeat (or spike/head again) again and again, perhaps many years later, again, if it becomes popular again for whatever reason, and then will fall back to LT behavior.

When it comes to consumption, both lognormal and LT/Pareto distribution are the "same" or embedded within each other, and it all depends how you slide it, based of time-frames and other variables such as popularity, awareness/over time, etc.

Note that I am no statistical person / expert of any kind, but the above is how I've seen behavior over time.

ceo

[Bertil Hatt]

As a statistician (a job that consist of spending 60% of your time asking: where that data came from) I can only concur. However, one thing can easily be seen: the first 18 top searches are sites so popular it would be wrong to label them as searches. Those are bookmark-use of Google. I doubt those can successfully be sorted out from the head — but you can't talk about it the same way. Search head don't really make sense, does it? Searching for Yahoo! on Google isn't about trying to get information about that company you heard of: it's laziness.

[Andrew Knight]

Hi Chris,

I'm emailing you in regards to an email I sent to you last month about a partnership, have you had a chance to think about it?

If you have any questions or would more information, please advise me and we can go from there.

Kind Regards,
Andrew Knight

[Guy Pressault]

Adding to the debate and more so to its perenity is this recent strategy post by MacKinsey which most likely has popped up on your screens.
http://www.mckinseyquarterly.com/Strategy/Growth/Using_power_curves_to_assess_industry_dynamics_2222
The question is asked: «As the importance of intangible assets increases across sectors, for example, will power curves in media and insurance resemble the currently much steeper ones found in today’s intangible-rich sectors such as software and biotech?»

Some speak of inequality? But in the LT view, needs being met are still provided by the Long Tail. But will this last as smaller players close shop? Will the promise that we live in a Long tail world remain true? The world's middle-class is a very long tail and still holds most of the value.

[Guy Daniels]

You might be interested to learn that we filmed interviews with the keynote speakers at the Telco 2.0 conference in London last week, and used the Mobile Music Long Tail analysis as the lead story on our weekly NewsDesk programme. There are comments by the MCPS-PRS alliance economists Will Page and Gary Eggleton, plus mBlox founder Andrew Bud. They give more background on their analysis of the music, and the evidence of a lack of a tail (or rather, a profitable tail). It's free to watch: http://tinyurl.com/5lm72z (or just look for the Newsdesk programme on www.TelecomTV.com.

We'll be producing a longer version of the discussion later this week. They've done some very interesting and comprehensive work, from the sound of it.

Regards
Guy

Head of Content
TelecomTV

[Texas Insurance Man]

I would agree that I-tunes lack of an adequate music recommendation application is most likely the reason for their patrons limited musical exploration.

[Electrician Houston]

I would agree with the comment stated above. This generic pricing scheme we have accepted, does not factor in quality and in most cases quantity. For example, I would like to see movies possibly offered without additional content for a reduced price.

[Seth Godin]

Chris, I think some critics are missing the point, largely because they're ignoring the subject of your new book.

Take a look at this video:
http://www.youtube.com/watch?v=IrTnaPa9BaA
It's an obscure forty year old song, and it's been watched a quarter of a million times.

If I'm interested in an obscure song, I'm much more likely to listen to it once via YouTube than to go to the trouble to find and search a site that may or may not sell it to me. If all you do is count the for money sales on one site, I wouldn't be surprised at all to see it hit focused.