The phrase The Long Tail (as a proper noun with capitalized letters) was first coined by Chris Anderson in an October 2004 Wired magazine article^[1] to describe certain business and economic models such as Amazon.com or Netflix. Businesses with distribution power can sell a greater volume of otherwise hard to find items at small volumes than of popular items at large volumes. The term long tail is also generally used in statistics, often applied in relation to wealth distributions or vocabulary use.

The long tail in statistics

The long tail is the colloquial name for a long-known feature of some statistical distributions (Zipf, Power laws, Pareto distributions and/or general Lévy distributions). The feature is also known as heavy tails, power-law tails, or Pareto tails. Such distributions resemble the accompanying graph.

In these distributions a high-frequency or high-amplitude population is followed by a low-frequency or low-amplitude population which gradually "tails off." In many cases the infrequent or low-amplitude events—the long tail, represented here by the yellow portion of the graph—can make up the majority of the graph.

The Long Tail by Chris Anderson

The phrase The Long Tail was, according to Chris Anderson, first coined^[2] by himself. The concept drew in part from an influential February 2003 essay by Clay Shirky, "Power Laws, Weblogs and Inequality"^[3] that noted that a relative handful of weblogs have many links going into them but "the long tail" of millions of weblogs may have only a handful of links going into them. 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 later extended it into the book The Long Tail: Why the Future of Business is Selling Less of More (2006).

Anderson argued 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, who first used a log-linear curve on an XY graph to describe the relationship between Amazon sales and Amazon sales ranking and found a large proportion of Amazon.com's book 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.

An 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."^[4]

Anderson has explained the term as a reference to the tail of a demand curve.[1] The term has since been rederived from an XY graph that is created when charting popularity to inventory. In the graph shown above, Amazon's book sales or Netflix's movie rentals would be represented along the vertical line, while the book or movie ranks are along the horizontal axis. The total volume of low popularity items exceeds the volume of high popularity items.

Academic research on long tail by Brynjolfsson, Hu, and Smith

In his Wired article, Anderson cites earlier research^[5] by Erik Brynjolfsson, Yu (Jeffrey) Hu, and Michael D. Smith, who first used a log-linear curve on an XY graph to describe the relationship between Amazon sales and Amazon sales ranking. They found a large proportion of Amazon.com's book sales come from obscure books that are not available in brick-and-mortar stores. They then quantified the potential value of the long tail to consumers. In an article published in 2003 these authors showed that, while most of the discussion about the value of the Internet to consumers has revolved around lower prices, consumer benefit (a.k.a. consumer surplus) from access to increased product variety in online book stores is ten times larger than their benefit from access to lower prices online. Thus, the primary value of the internet to consumers comes from releasing new sources of value by providing access to products in the long tail.

In a 2006 working paper titled "Goodbye Pareto Principle, Hello Long Tail"^[6], Erik Brynjolfsson, Yu (Jeffrey) Hu, and Duncan Simester found that, by greatly lowering search costs, information technology in general and Internet markets in particular could substantially increase the collective share of hard to find products, thereby creating a longer tail in the distribution of sales. They used a theoretical model to show how a reduction in search costs will affect the concentration in product sales. By analyzing data collected from a multi-channel retailing company, they showed empirical evidence that the Internet channel exhibits a significantly less concentrated sales distribution, when compared with traditional channels. An 80/20 rule fits the distribution of product sales in the catalog channel quite well, but in the Internet channel, this rule needs to be modified to a 72/28 rule in order to fit the distribution of product sales in that channel. The difference in the sales distribution is highly significant, even after controlling for consumer differences.

Demand-side and supply-side drivers

The key supply side 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 building overhead; 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 advantageous use of the Long Tail: Netflix finds that in aggregate "unpopular" movies are rented more than popular movies.

A recent MIT Sloan Management Review article, titled "From Niches to Riches: Anatomy of the Long Tail",^[7] examines the Long Tail from both the supply side and the demand side and identifies several key drivers. On the supply side, the authors point out how e-tailers' expanded, centralized warehousing allows for more offerings, thus making it possible for them to cater to more varied tastes.

On the demand side, tools such as search engines, recommender software and sampling tools are allowing customers to find products outside of their geographic area. The authors also look toward the future to discuss second order amplified effects of Long Tail, including the growth of markets serving smaller niches.

Cultural and political impact

The Long Tail has possible 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 works, minority tastes are catered to, and individuals are offered greater choice. In situations where popularity is currently determined by the lowest common denominator, a Long Tail model may lead to improvement in a society's level of culture. Television is a good example of this: TV stations have a limited supply of profitable or "prime" time slots during which people who generate an income will watch TV. These people with money to spend are targeted by advertisers who pay for the programming so the opportunity cost of each time slot is high. Stations, therefore, choose programs that have a high probability to appeal to people in the profitable demographics in order to guarantee a return. Twin Peaks, for example, did not have broad appeal but stayed on the air for two seasons because it attracted young professionals with money to spend. Generally, as the number of TV stations grows or TV programming is distributed through other digital channels, the key demographic individuals are split into smaller and smaller groups. As the targeted groups get into smaller niches and the quantity of channels becomes less of an opportunity cost, previously ignored groups become profitable demographics in the long tail. These groups along the long tail then become targeted for television programming that might have niche appeal. As the opportunity cost goes down with more channels and smaller niches, the choice of TV programs grows and greater cultural diversity rises as long as there is money in it.

Some of the most successful Internet businesses have leveraged the Long Tail as part of their businesses. Examples include eBay (auctions), Yahoo! and Google (web search), Amazon (retail) and iTunes Store (music and podcasts) amongst the major companies, along with smaller Internet companies like Audible (audio books) and Netflix (video rental).

Often presented as a phenomenon of interest primarily to mass market retailers and web-based businesses, the Long Tail also has implications for the producers of content, especially those whose products could not - for economic reasons - find a place in pre-Internet information distribution channels controlled by book publishers, record companies, movie studios, and television networks. Looked at from the producers' side, the Long Tail has made possible a flowering of creativity across all fields of human endeavour. One example of this is YouTube, where thousands of diverse videos - whose content, production value or lack of popularity make them innappropriate for traditional television - are easily accessible to a wide range of viewers.

Internet commercialization pioneer and media historian Ken McCarthy addressed this phenomenon in detail from the producers' point of view at a 1994 meeting attended by Marc Andreessen, members of Wired Magazine's staff, and others. Explaining that the pre-Internet media industry made its distribution and promotion decisions based on what he called "lifeboat economics" and not on quality or even potential lifetime demand, he laid out a detailed vision of the impact he expected the Internet would have on the structure of the media industry with what has turned out to be a remarkable degree of accuracy, foreshadowing many of the ideas that appeared in Anderson's popular book.^[8]

The recent adoption of computer games as tools for education and training is beginning to exhibit a long-tailed pattern. It is significantly less expensive to modify a game than it has been to create unique training applications, such as those for training in business, commercial flight, and military missions. This has led some to envision a time in which game-based training devices or simulations will be available for thousands of different job descriptions. Smith pursues this idea for military simulation, but the same would apply to a number of other industries.

Competition and the Long Tail

The Long Tail may threaten established businesses.^[9] Before a Long Tail works, only the most popular products are generally offered. When the cost of inventory storage and distribution fall, a wide range of products become available. This can, in turn, have the effect of reducing demand for the most popular products. For example, Web content businesses with broad coverage like Yahoo! or CNET 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 sites is reduced by 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. Similarly, mass-market distributors like Blockbuster may be threatened by distributors like Netflix, which supply the titles that Blockbuster doesn't offer because they are not aready very popular. In some cases, the area under the long tail is greater than the area under the peak.

Notes

Chris Anderson Speaking at The Long Now Foundation

References

Anderson, Chris (2006). The Long Tail: Why the Future of Business is Selling Less of More. Hyperion. ISBN 1-4013-0237-8.

External links

• "The Long Tail" by Chris Anderson, Wired, Oct. 2004 (Archived version)
• "The Long Tail" as a Change This Manifesto. Same as the Wired article; includes additional graphics and Adobe Reader interface
• "Consumer Surplus in the Digital Economy" by Erik Brynjolfsson, Yu (Jeffrey) Hu, and Michael D. Smith, November 2003
• "Goodbye Pareto Principle, Hello Long Tail" by Erik Brynjolfsson, Yu (Jeffrey) Hu, and Duncan Simester, December 2006
• "From Niches to Riches: Anatomy of the Long Tail" by Erik Brynjolfsson, Yu (Jeffrey) Hu, and Michael D. Smith, July 2006
• "Power Laws, Weblogs and Inequality" by Clay Shirky
• "The Digital Long Tail in Military Simulation Systems" by Roger Smith
• "Zipf, Power-laws, and Pareto - a ranking tutorial" by Lada A. Adamic
• The Long Tail Blog by Chris Anderson
• Long Tail Search by Michael Duz
• "Search's Long Tail" by Danny Sullivan
• The Rise and Fall of the Hit by Chris Anderson, Wired, Jul. 2006
• Tyranny of the Power Law from Econophysics Blog
• Interview with Russ Roberts, Library of Economics and Liberty
• Interview with Glenn Reynolds, Instapundit
• HitTail Video by Mike Levin (animation of long tail concept in real-world application)
• Shake That Tail by LaVern A. Pritchard, Law Technology News, Sept. 2006 (review and implications of the Long Tail for the legal sector)
• The Drooping Tail (sometimes the end of the Long Tail drops below that predicted by the theory)
• How to reduce PPC budgets using Long Tail analysis. by Gary Beal
• Chris Anderson and Will Hearst Discuss The Long Tail at the Long Now Foundation in San Francisco, May 12, 2006 (video)
• "The Long Tail" Video of Chris Anderson Keynote at SIIA Content Forum, November 2006.
• "A practical model for analyzing long tails" by Kalevi Kilkki, First Monday, May 2007.