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.The reason for this is simple: The vast majority of everything in the world is in the Tail.One of the consequences of living in a hit-driven culture is that we tend to assume that hits are a far bigger share of the market than they really are.Instead, they are the rare exception.This is what Nassim Taleb calls the “Black Swan Problem.”The phrase comes from David Hume, the eighteenth-century Scottish philosopher, who gave it as an example of the complications that lie in deriving general rules from observed facts.In what has now become known as Hume’s Problem of Induction, he asked how many white swans one need observe before inferring that all swans are white and that there are no black swans.Hundreds? Thousands? We don’t know.(The Black Swan is not just a hypothetical metaphor: Until the discovery of Australia, common belief held that all swans were white.That belief was shattered with the sighting of the first Cygnus atratus.)The problem is that we have a hard time putting rare events in context.In any given population there will be a few people who are tremendously rich.Some are smart and some are lucky and we really can’t tell which is which.In Fooled by Randomness, Taleb pokes fun at a bestseller called The Millionaire Next Door, which catalogs the investing tricks and work habits of multimillionaires, so that you can follow them and get rich, too.But as Taleb notes, random factors are just as likely to be responsible for that neighborly millionaire as investing strategies.He defines a Black Swan as:A random event satisfying the following three properties: large impact, incomputable probabilities, and surprise effect.First, it carries upon its occurrence a disproportionately large impact.Second, its incidence has a small but incomputable probability based on information available prior to its incidence.Third, a vicious property of a Black Swan is its surprise effect: at a given time of observation there is no convincing element pointing to an increased likelihood of the event.He could just as easily be describing a blockbuster hit.The reality is that the vast majority of content (from music to movies) is not hits.Indeed, the vast majority of content is about as far from a hit as it’s possible to be, counting its audience in hundreds rather than millions.Sometimes that’s because it’s not very good.Sometimes it’s because it wasn’t marketed well or made by people with the right connections.And sometimes it’s because of some random factor that got in the way, which is just as likely as the random factors that sometimes make a blockbuster out of the flimsiest novelty fare (“Who Let the Dogs Out” comes to mind).This is simply the natural consequence of what’s called a “powerlaw” distribution, a term for a curve where a small number of things occur with high amplitude (read: sales) and a large number of things occur with low amplitude.A few things sell a lot and a lot of things sell a little.(The phrase comes from the fact that the curve has a 1/x shape, which is the same as x raised to the–1 power.)Since most stuff doesn’t sell very well, the volume of the material available—and by extension the volume of stuff you don’t want—rises as the Long Tail falls.Here’s some actual data from the book industry, showing the number of titles in each sales category for 2004:The consequence of this is that whatever you are looking for, there’s more stuff you aren’t looking for the farther you go down the Tail.That’s why the signal-to-noise ratio gets worse, despite the fact that you’re often more likely (i.e., if you have access to good search and filters) to find what you want as you go down the Tail.It sounds like a paradox, but it isn’t.It’s just a problem for filters to solve.PRE-FILTERS AND POST-FILTERSWhen you think about it, the world is already full of a different kind of filter.In the scarcity-driven markets of limited shelves, screens, and channels that we’ve lived with for most of the past century, entire industries have been created around finding and promoting the good stuff.This is what the A&R talent scouts at the record labels do, along with the Hollywood studio executives and store purchasing managers (“buyers”).In boardrooms around the world, market research teams pore over data that predicts what’s likely to sell and thus deserves to win a valuable spot on the shelf, screen, or page…and what’s unlikely to sell and therefore doesn’t deserve a spot.The key word in the preceding paragraph is “predicts.” What’s different about those kinds of filters and the ones I’ve been focusing on is that they filter before things get to market.Indeed, their job is to decide what will make it to market and what won’t.I call them “pre-filters
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