About the Author. Rédacteur en chef du magazine Wired, Chris Anderson est un des penseurs de la nouvelle économie de l’ère numérique. Avant de prendre la. La Longue Traîne: Comment Internet a bouleversé les lois du commerce Chris Anderson is Editor-in-Chief of Wired magazine, a position he’s held since Buy La longue traine by Chris Anderson from Waterstones today! Click and Collect from your local Waterstones or get FREE UK delivery on orders over £

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In statistics and businessa long tail of some distributions of numbers is the portion of the distribution having a large number of occurrences far from the “head” or central part of the distribution.

The distribution could involve popularities, random numbers of occurrences of events with various probabilitiesetc.

Anderson, Chris 1961-

In statistics, the term long-tailed distribution has a narrow technical meaning, and is a subtype of heavy-tailed distribution. In business, the term long tail is applied to rank-size distributions or rank-frequency distributions primarily of popularitywhich often form power laws and are thus long-tailed distributions in the statistical sense. This is used to describe the retailing strategy of selling a large number of unique items with relatively small quantities sold of each the “long tail” —usually in addition to selling fewer popular items in large quantities the “head”.

Sometimes an intermediate category is also included, variously called the bodybellytorsoor middle. The specific cutoff of what part of a distribution is the “long tail” is often arbitrary, but in some cases may be specified objectively; see segmentation of rank-size distributions.

The long tail concept has found some ground for application, research, and experimentation. It is a term used in online business, mass mediamicro-finance Grameen Bankfor exampleuser-driven innovation Eric von Hippelknowledge management, and social network mechanisms e. Frequency distributions with long tails have been studied by statisticians since at least The long tail was popularized by Chris Anderson in an October Wired magazine article, in which he mentioned Amazon.

The distribution and inventory costs of businesses successfully applying a long tail strategy allow them to realize significant profit out of selling small volumes of hard-to-find items to many customers instead of only selling large volumes of a reduced number of popular items.

The total sales of this large number of “non-hit items” is called “the long tail”. Given enough choice, a large population of customers, and negligible stocking and distribution costs, the selection and buying pattern of the population results in the demand across products having a power law distribution or Pareto distribution.

It is important to understand why some distributions are normal vs. Chris Anderson argues that while quantities such as human height or IQ follow a normal distribution, in scale-free networks with preferential attachmentspower law distributions are created, i. In “long-tailed” distributions a high-frequency or high-amplitude population is followed by a low-frequency or low-amplitude population which gradually “tails off” asymptotically.

The events at the far end of the tail have a very low probability of occurrence. Power law distributions or functions characterize an important number of behaviors from nature and human endeavor. This fact has given rise to a keen scientific and social interest in such distributions, and the relationships that create them. The observation of such a distribution often points to specific kinds of mechanisms, and can often indicate a deep connection with other, seemingly unrelated systems.

Examples of behaviors that exhibit long-tailed distribution are the occurrence of certain words in a given language, the income distribution of a business or the intensity of earthquakes see: Chris Anderson ‘s and Clay Shirky ‘s articles highlight special cases in which we are able to modify the underlying relationships and evaluate the impact on the frequency of events. In those cases the infrequent, low-amplitude or low-revenue events — the long tail, represented here by the portion of the curve to the right of the 20th percentile — can become the largest area under the line.

This suggests that a variation of one mechanism internet access or relationship the cost of storage can significantly shift the frequency of occurrence of certain events in the distribution. The shift has a crucial effect in probability and in the customer demographics of businesses like mass media and online sellers. However, the long tails characterizing distributions such as the Gutenberg—Richter law or the words-occurrence Zipf’s lawand those highlighted by Anderson and Shirky are of very different, if not opposite, nature: Anderson and Shirky refer to frequency-rank relations, whereas the Gutenberg—Richter law and the Zipf’s law are probability distributions.

Therefore, in these latter cases “tails” correspond to large-intensity events such as large earthquakes and most popular words, who dominate the distributions. By contrast, the long tails in the frequency-rank plots highlighted by Anderson and Shirky would rather correspond to short tails in the associated probability distributions, and therefore illustrate an opposite phenomenon compared to the Gutenberg—Richter and the Zipf’s laws.


Use of the phrase the long tail in business as “the notion of looking at chgis tail itself as a new market” of consumers was first coined by Chris Anderson. Anderson described the effects of the long tail on current and future business models beginning with a series of speeches in early and with the publication of a Wired magazine article in October Anderson later extended it into the book The Long Tail: Anderson argues that products in low demand ,ongue that have a low sales volume can collectively make trains a market share that rivals or exceeds the relatively few current bestsellers and blockbusters, if the store or distribution channel is large enough.

Smiththat showed that a significant portion of Amazon. The long tail is a potential market and, as trine examples illustrate, the distribution and sales channel opportunities created by the Internet often enable businesses to tap that market successfully. In his Wired article Anderson opens with an anecdote about creating a niche market for books on Amazon.

He writes about a book titled Touching the Void about a near-death mountain climbing accident that took place in the Peruvian Andes. Anderson states the book got good reviews, but didn’t have much commercial success. Anderson realized that this was due to Amazon’s recommendations.

lz This created a niche market for those who enjoy books about mountain climbing even though it is not considered a popular genre supporting the long tail theory.

An Amazon employee described the long tail as follows: Anderson has explained the term as a reference to the tail of longke demand curve. In the graph shown above, Amazon’s book sales would be represented along the vertical axis, 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. Smith andersson, who first used a log-linear curve on an XY graph to describe the relationship between Amazon. They found that a large proportion of Amazon.

They then quantified the potential value of the long tail to consumers. In an article published inthese authors showed that, while most of the discussion about the value of the Internet to consumers has revolved around lower prices, consumer benefit a. 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. Smith [17] finds that the long tail has grown longer over time, with niche books accounting for a larger longgue of total sales.

Their analyses suggested that byniche books accounted for In addition, their new methodology finds that, while the widely used power laws are a good first approximation for the rank-sales relationship, the slope may not be constant for all book ranks, with the slope becoming progressively steeper for more obscure books. In support of their findings, Wenqi Zhou and Wenjing Duan not only find a longer tail but also a fatter tail by an in-depth analysis on consumer software downloading pattern in their paper “Online user reviews, product variety, and the long tail” [1].

The demand for all products decreases, but the decrease for the hits is more pronounced, indicating the demand shifting from the hits to the niches over time. In addition, they also observe a superstar effect in the presence of the long tail. A small number of very popular products still dominates the demand. In a working paper titled “Goodbye Pareto Principle, Hello Long Tail”, [18] Erik BrynjolfssonYu Jeffrey Huand 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.

Anderson, Chris [WorldCat Identities]

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. The difference in the sales distribution is highly significant, even after controlling for consumer differences. 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.

For 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 online video rental provider such as Amazon. It 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: Anatomy of the Long Tail” [19] examined the long tail from both the supply side and the demand chriw 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, recommendation software, and sampling tools are allowing customers to find products outside 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. Not all recommender systems are equal, however, when it comes to expanding the long tail. A Wharton study details this phenomenon along with several ideas that may promote the long tail and greater diversity.

A recent study conducted by Wenqi L and Wenjing Duan [22] further points out that the oongue side factor online traaine reviews and the supply side factor product variety interplay to influence the long tail formation of user choices. Consumers’ reliance on online user reviews to choose products is significantly influenced by the quantity of products available.

Specifically, they find that the impacts of both positive and negative user reviews are weakened as product variety goes up. In addition, the increase in product variety reduces the impact of user reviews on popular products more than it does on niche products. The “crowds” of customers, users and small companies that inhabit the long-tail distribution can perform collaborative and assignment work.

Some relevant forms of these new production models are:. The demand-side factors that lead to the long tail can be amplified by the “networks of products” which are created by hyperlinked recommendations across products. The long-tail distribution applies at a given point in time, but over time the relative popularity of the sales of the individual products will change.

For example, new items constantly enter most fashion markets. A recent fashion-based model [27] of consumer choice, which is capable of generating power law distributions of sales similar to those observed in practice, [28] takes into account turnover in chrris relative sales of a given set of andesron, as well as innovation, in the sense that entirely new items become offered for sale.

There may be an optimal inventory size, given the balance between sales and the cost of keeping up with the turnover. An analysis based on this pure fashion model [29] indicates that, even for digital retailers, the optimal inventory may in many cases be less than the millions of items that they can potentially offer.

In other words, by proceeding further and further into the long tail, sales may become so small that the marginal cost of tracking them in rank order, even at a digital scale, might be optimised well before a million titles, and certainly before infinite titles.

This model can provide further predictions into markets with long-tail distribution, such as the basis for a model for optimizing the number of each individual item ordered, given its current sales rank and the total number of different titles stocked. Before a long tail works, only the most popular products are generally offered.

When the cost of inventory storage and lw fall, a wide range of products become available.

La longue traine : quand vendre moins, c’est vendre plus

This can, in turn, have the effect of reducing demand for the most popular products. For example, a small website that focuses on niches of content can be threatened by a larger website which has a variety of information such as Yahoo Web content.

The big website covers more variety while the small website has only a few niches to choose from. The competitive threat from these niche sites is reduced by the cost of establishing and maintaining them and the effort 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.

La longue Traîne: la nouvelle économie est là! – Chris Anderson – Google Books

Similarly, mass-market distributors like Blockbuster may be threatened by distributors like LoveFilmwhich supply the titles that Blockbuster doesn’t offer because they are not already very popular. Some of the most successful Internet businesses have used the long tail as part of their business strategy. Examples include eBay auctionsYahoo! These purely digital retailers also have almost no marginal cost, which is benefiting the online services, unlike physical retailers that have fixed limits on their products.

The internet can still sell physical goods, but at an unlimited selection and with reviews and recommendations.