The phrase “The Long Tail” was first coined by Chris Anderson in 2004 and later expanded in his book, The Long Tail: Why the Future of Business Is Selling Less of More in 2006. It was also popularized as another of O’Reilly’s Web 2.0 patterns (mentioned in this series). The Long Tail consists of the less popular interests of users. O’Reilly describes it as, “the collective power of the small sites that make up the bulk of the web’s content.”
The Long Tail as a graph looks like this (also called a ‘power law’ or ‘Pareto’ distribution curve) –
With some imagination it might also look like this –
Wikipedia states that The Long Tail “refers to the statistical property that a larger share of population rests within the tail of a probability distribution than observed under a ‘normal’ or Gaussian distribution. This has gained popularity in recent times as a retailing concept describing the niche strategy of selling a large number of unique items in relatively small quantities – usually in addition to selling fewer popular items in large quantities.” Kroski (2008) puts it simply as “the less popular interests of users.”
She adds that “when creating a power law distribution chart to map out popular topics among users, the minority topics form a long tail leading to the end of the chat. What makes the long tail interests so fascinating is that when they are added up, these non-mainstream interests far outnumber the popular ones.” (Kroski, 2008, p. 6). Additionally, Anderson (2006) points out that the long tail accounts for between 25 percent to 40 percent of Amazon.com’s sales, and that one-fifth of all Netflix (DVD rentals) rentals are from titles other than their top 3,000 titles. There are long-tail enthusiasts and critics (Anita Elberse on Anderson’s devotion to Rhapsody and Quickflix data; or David Hornik).
“The potential for online retailers to make more money than their bricks and mortar counterparts because there is virtually unlimited “shelf space” to offer products. Another key factor is that merchandise is offered via recommendations with links from one product to another so that people who purchase one item are encouraged to look at several others. Most notably, book, video and music sales, where there is a vast supply of product, have benefited significantly from this approach, exemplified by Amazon.com, Netflix and Rhapsody.” (Computer Dictionary Definition)
There are many examples of ‘The Long Tail’ including NetFlix, Blockbuster, Rhapsody, Google’s advertising & other Google services & mission, Amazon.com, CustomFlix, BookSurge, Barnes & Noble, New York Times, Captchas, WordPress.com, Skype, eBay, Craigslist, Flickr, iTunes, lulu.com, SocialText, Confluence, and Kapow Technologies. I would like to present to you the “Wired” editor and author, Chris Anderson explaining his theory of “The Long Tail.” This “blew me away”! Please watch Chris’ fantastic lecture…
The Long Tail – YouTube featuring Chris Anderson
The Long Tail – example: Remember the Milk
Remember the Milk (RTM) enables its members to create to-do lists which are arranged and displayed in a tabbed interface. Users can include detailed information about tasks, set priorities for items, designate due dates, and tag tasks with keywords.
Listmakers may create contacts and groups with whom they may share their lists. RTM lists may be accessed via modules on Netvibes (see my previous blog on Rich User Experience – Netvibes) and Goggle start pages, and through Sidekicks and other mobile devices. Users can opt to be reminded about tasks with upcoming due dates by email, IM, or text messages sent to their mobile phone.
In conclusion, combination of the power law probability graph (see graph/illustration above) showing popularity ranking and the direct access to consumers via Web technology (the invisible crowd) has opened up new business opportunities in the “long tail”. Consequently, Web 2.0 applications are designed to serve not only the mainstream and the widespread, but also the fringe interests!