Around the Christmas season each year there are a flurry of stories about hit toys, books and other retail blockbuster phenomena that seem to defy the overall trend towards more niche demand. This year is no exception, so I’ll round up a couple of the recent pieces here:
1) Quite a good article in New Scientist surveys recent research on consumer behavior in the face of massive variety, and concludes that we still like to buy stuff that other people buy. It mentions the Elberse research as well as comments from Duncan Watts about how socially connected groups tend to clump in their taste. (Image from the article shown above.)
My take: I’ve already discussed the problems with Elberse’s research (it’s based on percentages, not absolute numbers, which become meaningless when inventory grows by orders of magnitude. She also defines head and tail in a way that doesn’t make sense and doesn’t correspond to my own definitions).
Watts’ work is more interesting, and touches on the same point Eric Schmidt from Google made about network effects creating winner-take-all consequences. My answer to that is that fortunately social media creates an infinite number of networks, many of them focused on niche subjects, so that many winners can take “all” of their micromarket, while still having the collective effect of redistributing demand in the entire market over more variety. This is the “fractal dimension” of the Long Tail that I’ve written about in the blog and the book.
2) The Times UK did a piece on Will Page’s work on music sales, which I wrote about here. The piece is a bit confused, and seems to think this refers to all music online, rather than some UK online retailer(s) that has not been disclosed, as is actually the case.
My take: Nothing new, and my problem with the work remains. Because Will hasn’t published the data or said where it came from, we can’t really know what it means. Is it iTunes UK? Some mobile provider? Ringtones? Some streaming provider? Some combination of the above? Ugh.
His observation that the data is fit better by a lognormal than a powerlaw is interesting, but until we know what filters were available in that marketplace (or marketplaces), we can’t say whether that’s surprising or not. In general, marketplaces with good filters (recommendations and other discovery tools) tend to follow a powerlaw, where marketplaces with poor filters follow the steeper lognormal of the older bricks-and-mortar markets. Again, there’s a whole chapter on this in the book.
Interestingly, the article says that Page and his co-author plan to write a book on this. No doubt they’ll come up with a better title than “Some Online Markets are Better Fit by a Lognormal Than a Powerlaw”, but it will be fun to see how far they can take this.