I'll take it as a compliment that I now warrant a proper Wall Street Journal takedown for crimes of...well, I'm not quite sure what the crimes are. But Lee Gomes has tried mightily to find flaws with the Long Tail theory and deserves a response of some sort. I have no doubt that there are many parts of my analysis and data that could be improved. Unfortunately, Gomes, in his haste to find them, stumbles over statistics and more, and in the end simply makes a muddle of what might have been an interesting debate over the magnitude of the Long Tail effect.
In the book's main sections, Mr. Anderson writes that as things move online, sales of misses will increase -- so much so that they can equal or exceed the sales of hits. The latter is the book's showstopper proposition; it's mentioned twice on the book's jacket.
I was thus a little surprised when Mr. Anderson told me that he didn't have any examples of this actually occurring.
First, the book doesn't claim that there are any cases where sales of products not available in the dominant bricks-and-mortar retailer in a sector (my definition of "tail") are larger than the sales of products that are available in that retailer ("head").
What it does say is that the current data at Rhapsody, Netflix and Amazon show that the tail amounts to between 21% and 40% of the market, with the head accounting for the rest. Although I don't discuss this in detail in the book, in the case of Rhapsody, the trend data suggests that the tail (as defined above) actually will equal the head within five years. Which is why the language Gomes cites from the book jacket is actually all phrased in the future conditional tense ("What happens when the combined value of all the millions of items that may sell only a few copies equals or exceeds the value of a few items that sell millions each?"). I asked him to quote the jacket copy in full context, but it apparently wasn't convenient to his thesis to do so, so he didn't.
Mr. Anderson told me the lack of an example of misses outselling hits doesn't diminish his basic point, which he said is simply that the role of the tail "is big and getting bigger."
By Mr. Anderson's calculation, 25% of Amazon's sales are from its tail, as they involve books you can't find at a traditional retailer. But using another analysis of those numbers -- an analysis that Mr. Anderson argues isn't meaningful -- you can show that 2.7% of Amazon's titles produce a whopping 75% of its revenues. Not quite as impressive.
Sigh. Gomes was determined to make this point, even after I and others pointed out the statistical fallacy at the core of it. As I wrote in this post, trying to define "head" and "tail" in percentage terms is meaningless in a market with unlimited inventory, because the denominator can grow infinitely large. Let me give you an example of why this doesn't work:
Let's say you have 1,000 items and the top 100 (10%) account for 50% of the sales. Then you add another 99,000 items to the catalog, and the sales of that top 100 fall to just 25% of the total, while it takes another 900 items to make up the next 25%. I would say that demand has shifted down the tail, because those top 100 items have dropped from half the market to just a quarter of it and the rest of the demand is spread over more items.
But by Gomes' math, we've gone from a market where 10% of products make 50% of the revenues to one where 1% of the products make 50% of the revenues--in other words, it's become more hit-centric. I think this is simply a misunderstanding of basic statistics, and I'm disappointed that Gomes, despite many emails from me and at least one economist to him on this point, chose to simply say that I don't agree with that approach (but not why).
Finally, a very annoying point. Gomes writes:
Other economists, of course, are looking into these same questions, though some seem to be reaching far more restrained conclusions. Harvard's Anita Elberse, whom Mr. Anderson said was a consultant during his two-year research project, studies the video sales market, both online and off.
She said in an email that her work to date shows a "slight shift" toward the tail. But she also noted "a rapidly increasing number of titles that never, or very rarely, sell," which suggests "it is difficult for content providers to profit from the 'tail.' "
As Professor Elberse told Gomes, she was only describing Nielsen VideoScan data, which is almost entirely taken from bricks-and-mortar sources. The Netflix data, which was the basis of the Long Tail analysis that she and I worked on together, tells a very different story (Elberse's terms of data access don't allow her to share that data; my terms allowed me to share what I published in the book). We both urged Gomes to make clear that the "slight shift" measured didn't refer to the Netflix data that was at the core of the book's conclusions. But he chose to make the point he wanted to make.
I'm actually quite an admirer of Gomes' work and he certainly did do a lot of research for this piece. But he started off with the wrong end of the stick (looking at the market in percentage terms, which doesn't work because the definition of "head" keeps changing) and sadly wouldn't let it go. As an editor, I've seen this happen before and we try to watch out for it. But sometimes the lure of the gotcha is too much to resist.