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In statistics, the term long tailed distribution has a narrow technical meaning, and is a subtype of heavy tailed distribution see that article for details. Intuitively, a distribution is right long tailed if, for any fixed amount, when a quantity exceeds a high level, it almost certainly exceeds it by at least that amount large quantities are probably even larger. Note that statistically, there is no sense of the long tail of a distribution, but only the property of a distribution being long tailed. In business, the term long tail is applied to rank size distributions or rank frequency distributions primarily of popularity, which 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 tailusually in addition to selling fewer popular items in large quantities the head. Sometimes an intermediate category is also included, variously called the body, belly, torso, or 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 media, micro finance Grameen Bank, for example, user driven innovation Eric von Hippel, and social network mechanisms e. IT Security threat hunting within a SOC Informationsecurityoperationscenter. HistoryeditA frequency distribution with a long tail has been studied by statisticians since at least 1. The term has also been used in the finance6 and insurance business7 for many years. The work of Benot Mandelbrot in the 1. The long tail was popularized by Chris Anderson in an October 2. Wired magazine article, in which he mentioned Amazon. Apple and Yahoo as examples of businesses applying this strategy. Anderson elaborated the concept in his book The Long Tail Why the Future of Business Is Selling Less of More. BusinesseditThe 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 attachments, power law distributions are created, i. Malcolm Gladwells mavens in The Tipping Point. Statistical meaningeditThe tail becomes bigger and longer in new markets depicted in red. In other words, whereas traditional retailers have focused on the area to the left of the chart, online bookstores derive more sales from the area to the right. The long tail is the name for a long known feature of some statistical distributions such as Zipf, power laws, Pareto distributions and general Lvy distributions. 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. As a rule of thumb, for such population distributions the majority of occurrences more than half, and where the Pareto principle applies, 8. What is unusual about a long tailed distribution is that the most frequently occurring 2. 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 GutenbergRichter law. Chris Andersons and Clay Shirkys 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 2. 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 GutenbergRichter law or the words occurrence Zipfs law, and those highlighted by Anderson and Shirky are of very different, if not opposite, nature Anderson and Shirky refer to frequency rank relations, whereas the GutenbergRichter law and the Zipfs 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 GutenbergRichter and the Zipfs laws. Chris Anderson and Clay ShirkyeditUse of the phrase the long tail in business as the notion of looking at the tail itself as a new market of consumers was first coined by Chris Anderson. The concept drew in part from a February 2. Clay Shirky, Power Laws, Weblogs and Inequality,1. Anderson described the effects of the long tail on current and future business models beginning with a series of speeches in early 2. Wired magazine article in October 2. Anderson later extended it into the book The Long Tail Why the Future of Business is Selling Less of More 2.