I have taken my time with this book as I try to marry the concepts thrown, with our local or rather African settings. It however does make a good read with the author – Chris Anderson, arguing that products that are in low demand or have low sales volume can collectively make up a market share that rivals or exceeds the relatively few current bestsellers and blockbusters, if the store or distribution channel is large enough. Anderson cites earlier research by Erik Brynjolfsson, Yu (Jeffrey) Hu, and Michael D. Smith, that showed that a significant portion of Amazon.com’s sales come from obscure books that are not available in brick-and-mortar stores. The Long Tail is a potential market and, as the examples illustrate, the distribution and sales channel opportunities created by the Internet often enable businesses to tap into that market successfully.

The Substance of the Long Tail

A quarter of the way into his book The Long Tail: How Endless Choice Is Creating Unlimited Demand, Anderson explains, “The theory of the Long Tail can be boiled down to this: Our culture and economy are increasingly shifting away from a focus on a relatively small number of hits (mainstream products and markets) at the head of the demand curve, and moving toward a huge number of niches in the tail.”

What drives this Long Tail and the niches that populate it? Anderson identifies three ‘forces’.

1. More stuff is being produced. Technology and the internet make it cheaper and easier to record and distribute your own songs, publish your own writings and so on. This lengthens the tail.
2. There is better access to niches, again thanks to the reach and economies on the net. This fattens the tail.
3. Search and recommendations connect supply and demand. This drives business from hits to niches.

All this is good stuff. Anderson suggests that we all have niche interests; it’s just the constraints of mass media that have focused us on the common denominators of mainstream hits. Clearly this resonates with a lot of people (and I’m among them), who have been quick to adopt the term and apply to it to their own domains.

Anderson explains that the Long Tail is an example of a power law, and that “powerlaws come about when you have three conditions:

1. Variety (there are many different sorts of things)
2. Inequality (some have more of some quality than others)
3. Network effects such as word of mouth and reputation, which tend to amplify differences in quality.”

These conditions are important, for reasons I’ll come back to. Why do they breed Long Tails? “The characteristic steep falloff shape of a popularity powerlaw comes from the effect of powerful word-of-mouth feedback loops that amplify consumer preference, making the reputation-rich even richer and the reputation-poor relatively poorer. Success breeds success,” writes Anderson. Which brings me to the first area in the book that I’d like to see developed further.

Word-of-mouth, filters and network effects

If word-of-mouth feedback is what creates the steep fall-off shape, should the internet’s amplification and speeding up of word-of-mouth make the fall-off steeper? Why shouldn’t the amplification mean there is worse access to, or worse awareness of, the reputation-poor niches? Does the amplification apply unevenly, or does the third force (filters and recommendations to connect supply and demand) counteract it?

Anderson seems to imply that maybe both of these apply. He says, “filtering is often most effective at the genre level rather than across the entire market… between genres their [filters'] effect is more muted.” I struggled to follow the evidence to support this argument. How could filters and recommendations work best at genre/category scale, when genres and categories are abstract constructs that people impose over the data, and the genres I use to divide a catalogue may not be the same ones you use?

I wonder if perhaps what Anderson is grappling towards is the increased independence that the internet provides for communities of fans to organise themselves and communicate, separate from the mainstream. This scope for word-of-mouth amplification within small pockets of the market could help fatten the tail and boost awareness of niche products within niche communities. But if that is what Anderson meant, I couldn’t find it clearly articulated or explained.

Independence and the wisdom of crowds

In general, the book seems muddled in its treatment of the role that individual, independent opinions play in creating filters, and in the circumstances under which it’s helpful to aggregate or average these opinions. Anderson refers several times to the term The Wisdom of Crowds, named after James Surowiecki’s book of the same name. In charting how ‘the many can be smarter than the few’, Surowiecki specifies clear conditions on which the wisdom of the crowds depends (summarised in Wikipedia), and gives many examples of circumstances when crowds are the opposite of wise.

Anderson’s liberal, broad-brush references to the wisdom of crowds ignore these conditions and imply that it can be taken for granted across many situations: “Yahoo music ratings, Google PageRank, MySpace friends, Netflix user reviews — these are all manifestations of the wisdom of the crowd”. No, they’re not. Many of them fail Surowiecki’s conditions, and fall prey to what he calls ‘information cascades‘ (a lack of independence between the people making the ratings or reviews). Anderson even contradicts himself in this area. Referring to Top 10 lists, he asserts, “There’s nothing wrong with ranking by popularity — after all, that’s just another example of a ‘wisdom of the crowds’ filter.” But then he says things that don’t sell well may be just as good as those that do, and argues a few pages later that, “The movies don’t get worse at rank 100 (some would argue they actually get better)”. Apparently he puts little store in the ‘wisdom’ of the rankings.

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