The Long Tail
From Biocrawler, the free encyclopedia.
The phrase The Long Tail (as a proper noun with capitalized letters) was first coined by Chris Anderson in a 2004 Wired Magazine article [1] (http://www.wired.com/wired/archive/12.10/tail.html) to describe certain business and economic models such as Amazon.com or Netflix. The term long tail is also generally used in statistics, often applied in relation to wealth distributions or vocabulary use.
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The long tail in probability theory statistics
The long tail is the colloquial name given to a long-known feature of statistical distributions (Zipf, Power-laws, Pareto distributions and/or Levy distributions ). They are also known as "heavy tails", "power-law tails" or "Pareto tails". Such distributions can be visualized by the image of the graph on this page. In these distributions a vast population of events occur very rarely in the yellow (or more generally have low amplitude on some scale, e.g., popularity or sales) while a small population of events occur very often in the red (or have high amplitude). The huge population of rare (or low amplitude) events is referred to as the long tail. In many cases most of the events are in the tail.
Such distributions are surprisingly common. Three examples: The word "is" is very common in English text, while the word "disintermediation" isn't; most words in English are part of the long tail. Lots of energy was released by the earthquake of December 26 2004, but there are tiny earthquakes all the time; most earthquakes are part of the long tail. Lots of loaves of bread are sold every day, but very few jars of pickled pig's feet; most food items sold are part of the long tail (assuming that the store carries them at all).
The Long Tail by Chris Anderson
The phrase "The Long Tail", as a proper noun, was first coined1 by Chris Anderson. Beginning in a series of speeches in early 2004 and culminating with the publication of a Wired Magazine article in October 2004, Anderson described the effects of the long tail on current and future business models. Anderson observed 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. Examples of such mega-stores include Amazon.com, Netflix and even Biocrawler. The Long Tail is a potential market and, as the examples illustrate, successfully tapping in to that long tail market is often enabled by the distribution and sales channel opportunities the Internet creates.
A former Amazon employee described the Long Tail as follows: "We sold more books today that didn't sell at all yesterday than we sold today of all the books that did sell yesterday." In the same sense Biocrawler has many low popularity articles that, collectively, create a higher quantity of demand than a limited number of mainstream articles found on a professional site such as Britannica.
The term is derived from the XY graph that is created when charting popularity to inventory. For example, in the graph shown on this page the total inventory of Biocrawler articles is along the bottom line, while the popularity rating (web page hit statistics) is along the vertical axis. So, for example, the Biocrawler homepage would receive the most views and be on the far left in the red, while this page might be on the far right in the yellow, as would most of Biocrawler's articles. The same could be said for Amazon's book inventory or Netflix's movie inventory. The total volume of low popularity items exceeds the volume of high popularity items.
Relationship between the Long Tail and storage and distribution costs
The key factor that determines whether a sales distribution has a Long Tail is the cost of inventory storage and distribution. Where inventory storage and distribution costs are insignificant, it becomes economically viable to sell relatively unpopular products; however when storage and distribution costs are high only the most popular products can be sold. Take movie rentals as an example: A traditional movie rental store has limited shelf space, which it pays for in the form of monthly rent; to maximize its profits it must stock only the most popular movies to ensure that no shelf space is wasted. Because Netflix stocks movies in centralized warehouses, its storage costs are far lower and its distribution costs are the same for a popular or unpopular movie. Netflix is therefore able to build a viable business stocking a far wider range of movies than a traditional movie rental store. Those economics of storage and distribution then enable the Long Tail to kick in: Netflix finds that in aggregate "unpopular" movies are rented more than popular movies.
Cultural and political impact of the Long Tail
The Long Tail has strong implications for culture and politics. Where the opportunity cost of inventory storage and distribution is high, only the most popular products are sold. But where the Long Tail kicks in, minority tastes are catered to and individuals are offered greater choice. In situations where popularity is determined by the lowest common denominator, the Long Tail will thus lead to improvement in a society's level of culture. Television is a good example of this: TV stations have limited time slots, so the opportunity cost of each time slot is high; stations therefore choose programs that have the broadest appeal. But as the number of TV stations grows or TV programming is distributed through other digital channels, the choice of TV programs grows and the cultural level rises.
The most successful Internet businesses have leveraged the Long Tail as part of their businesses. Examples include eBay, Yahoo!, Google, and Amazon amongst the majors along with smaller Internet companies like Audible and Netflix (cited above).
Competition and the Long Tail
The Long Tail is not just a positive economic effect; it can also threaten established businesses. Before a Long Tail kicks in the only products on offer are the most popular, but when the costs of inventory storage and distribution fall then a wide range of products suddenly becomes available; that can in turn have the effect of reducing demand for the most popular products. For example, Web content businesses with broad coverage like Yahoo!, CNET or even TheStreet.com may be threatened by the rise of smaller Web sites that focus on niches of content, and cover that content better than the larger sites. The competitive threat from these niche "category killer" sites is related to the cost of establishing and maintaining them and the bother required for readers to track multiple small Web sites. These factors have been transformed by easy and cheap Web site software and the spread of RSS.
See also
- Professional amateurs
- Pareto principle
- Network effect
- Collaborative Filtering
- Matthew effect
- Gini coefficient
- Lorenz curve
Probability distributions with "long tails"
Notes
- Note 1: See The origins of "The Long Tail" (http://longtail.typepad.com/the_long_tail/2005/05/the_origins_of_.html) by Chris Anderson
External links
- "Zipf, Power-laws, and Pareto - a ranking tutorial" (http://www.hpl.hp.com/research/idl/papers/ranking/ranking.html) by Lada A. Adamic
- "The Long Tail" (http://www.wired.com/wired/archive/12.10/tail.html) by Chris Anderson, Wired Magazine Oct. 2004.
- "The Long Tail" (http://www.changethis.com/10.LongTail) as a Change This Manifesto. Same as the Wired article, includes additional graphics and Adobe reader interface.
- The Long Tail Blog (http://longtail.typepad.com/the_long_tail/) by Chris Anderson.
- "Competition and The Long Tail" (http://www.internetstockblog.com/2005/03/competition_and.html) by David Jackson.
- "Personalization, The Long Tail, And The Charge Against The Customer Monoculture" (http://socialcustomer.typepad.com/the_social_customer_manif/2005/02/personalization.html) by Christopher Carfi.
- "The long tail of software. Millions of Markets of Dozens" (http://bnoopy.typepad.com/bnoopy/2005/03/the_long_tail_o.html).
- "Search's Long Tail" (http://blog.searchenginewatch.com/blog/050314-164653) by Danny Sullivan.
- Profiting from obscurity (http://economist.com/finance/displayStory.cfm?story_id=3936129) from The Economist
