The Long Tail

by Chris Anderson

  BIRDMONSTER

  This last example is a much smaller one, but one I know well, since it involves a former colleague. In the course of researching this book, I decided to track the progress of Birdmonster, an up-and-coming San Francisco band fronted by Peter Arcuni, an editorial assistant at Wired. The experience proved all too instructive.

  Birdmonster is a prime example of how the three forces of the Long Tail are overturning the status quo in the music industry. Like all new rock bands, Birdmonster started by hustling for gigs. But rather than pestering club owners for a break, the band members realized that there was now a smarter way. In club booking, the headliners are typically signed up first. Then, once the dates are set in the calendar, the club looks for opening acts to support them. Since virtually all club schedules are now online, opportunities for opening acts can be found simply by searching for the letters “TBA” and some other keywords to limit the search to local clubs. Then it’s simply a matter of contacting the club and offering to fill that gap in their lineup.

  But getting the club owners’ attention isn’t enough; they need to know that you’ll be able to attract a crowd, too. For that Birdmonster used grassroots Internet marketing. It started an online mailing list and encouraged fans to register as “friends” on the band’s MySpace page. It put a few songs on that page and listed its other gigs, along with pictures. Bookers could check it out, listen to songs, and see pictures from previous shows, while reading raves from the band’s fans.

  Birdmonster also courted Internet radio stations, which have none of the constraints of traditional broadcast. As it happened, it was “Ted,” the owner of San Francisco’s BagelRadio.com, who convinced the booker to give Birdmonster its first big break, an opening gig for Clap Your Hands Say Yeah. That (and a battle-of-the-bands contest) led to opening for the White Stripes, which was at that moment the pinnacle of indie rock. Birdmonster had arrived.

  It was time to go beyond live gigs. The band recorded three tracks in a local independent studio and self-published them as a mini album, which they sent to a music service called CD Baby, which takes albums on consignment and sells them online. CD Baby, in turn, transferred the digital tracks to iTunes and other top music services, so they could be bought or streamed just like the biggest label hits.

  The band then emailed song tracks and personal notes to various MP3 blogs, getting a positive mention on several, such as Music for Robots, which brought yet more attention. The band’s MySpace page started filling up with fans, and soon managers, labels, and industry folks came calling with deals.

  But then something surprising happened: Birdmonster turned the offers down. As Arcuni put it, “We’re not anti-label in principle, but the numbers (risk vs. reward) didn’t add up.”

  A music label exists primarily to fulfill four functions: (1) talent scouting; (2) financing (the advances bands get to pay for their studio time is like seed capital invested by a venture capitalist); (3) distribution; and (4) marketing.

  From Birdmonster’s perspective, they didn’t need a label to provide that. A growing local fan base, amplified online, had already spotted their talent. Improving digital recording technology had made studio time cheaper than ever—they could record the tracks in a few days in the studio and then mix and overdub them at home using personal computers. The cost to record the entire album was less than $15,000, which they covered with credit cards and savings. CD Baby and a similar company called Cinderblock provided the distribution, which gave them a reach as broad as iTunes, Rhapsody, and the other top services. And MP3 blogs and MySpace were free marketing.

  Why sign their life away now to a label, they reasoned, when they could record and distribute their music themselves and keep their creative independence? If the first self-released album did well, they’d be in a much stronger negotiating position with the label, for rereleasing the first album in stores, or for the second album, much as My Chemical Romance was after its first album. And if it didn’t, there were still live shows and touring, which are really the best part of being in a band anyway. And so Arcuni quit his day job (our loss!) and set off to become a professional musician, emboldened in a DIY age where technology has shifted the balance of power from label to band.

  THE POWER OF COLLECTIVE INTELLIGENCE

  Yahoo! music ratings, Google PageRank, MySpace friends, Netflix user reviews—these are all manifestations of the wisdom of the crowd. Millions of regular people are the new tastemakers. Some of them act as individuals, others are parts of groups organized around shared interests, and still others are simply herds of consumers automatically tracked by software watching their every behavior.

  For the first time in history, we’re able to measure the consumption patterns, inclinations, and tastes of an entire market of consumers in real time, and just as quickly adjust the market to reflect them. These new tastemakers aren’t a super-elite of people cooler than us; they are us.

  The trend watchers at Frog Design, a consultancy, see this as nothing less than an epochal shift:

  We are leaving the Information Age and entering the Recommendation Age. Today information is ridiculously easy to get; you practically trip over it on the street. Information gathering is no longer the issue—making smart decisions based on the information is now the trick…. Recommendations serve as shortcuts through the thicket of information, just as my wine shop owner shortcuts me to obscure French wines to enjoy with pasta.

  Amplified word of mouth is the manifestation of the third force of the Long Tail: tapping consumer sentiment to connect supply to demand. The first force, democratizing production, populates the Tail. The second force, democratizing distribution, makes it all available. But those two are not enough. It is not until this third force, which helps people find what they want in this new superabundance of variety, kicks in that the potential of the Long Tail marketplace is truly unleashed.

  The new tastemakers are simply people whose opinions are respected. They influence the behavior of others, often encouraging them to try things they wouldn’t otherwise pursue. Some of these new tastemakers are the traditional professionals: movie and music critics, editors, or product testers. As our interests expand with the exploding availability of wide variety, the demand for such informed and trusted advice is now extending to the narrowest niches. Companies such as Weblogs, Inc. have built thriving businesses around starting blogs to serve narrow interests, from scuba diving and the WiMax wireless standards, to medical informatics.

  Other tastemakers are celebrities, who are another sort of trusted guide, and whose influence on consumption continues to grow. From product placement in TV shows to the remarkable success of InStyle magazine (its great innovation was not cropping the photos at the knees, so as to show the shoes), the power of celebrity is increasingly measured in terms of their ability to move merchandise. Whether you like it or not, Jessica Simpson is a tastemaker.

  But not all celebrities are Hollywood stars. As our culture fragments into a million tiny microcultures, we are experiencing a corresponding rise of microcelebrities. In the technology world, these take the form of power bloggers, such as the team that writes DailyCandy, a fashion blog, or BoingBoing, a site focusing on technology and subculture, which is at the time of this writing the world’s most popular blog. BoingBoing has the capacity to discover a cool toy, such as a $15 “20Questions” game built on a neural network trained online, and drive enough traffic to an online marketplace to sell it out in a day. Other microcelebrities are even more micro, ranging from high-ranking playlist contributors on iTunes to the taste mavens behind popular music blogs such as Pitchfork Media.

  And then there is crowd behavior, which is best seen as a form of distributed intelligence. Examples of crowds are taggers on Flickr, the photo-sharing site that encourages you to invent your own categories for pictures (you may see Paris Hilton in the picture, but I see her Sidekick phone, and so I tag the photo “Sidekick”), and linkers who build online lists of Web pages they want to be ab
le to find again.

  People who are part of such a crowd may not think of themselves as offering recommendations or guidance at all. They’re just doing what they do for their own reasons. But every day there is more and more software watching their actions, and drawing conclusions from them. The rise of the search engine as the economic force of Silicon Valley is simply a reflection of the value that we now recognize in the measurement and analysis of the actions of millions of individuals.

  FILTERS RULE

  The catch-all phrase for recommendations and all the other tools that help you find quality in the Long Tail is filters. These technologies and services sift through a vast array of choices to present you with the ones that are most right for you. That’s what Google does when it ranks results: It filters the Web to bring back just the pages that are most relevant to your search term. It’s also what the “Most Popular Tracks” in the acid jazz subgenre on Rhapsody is doing.

  Filters make up what Rob Reid, one of the founders of Listen.com, calls the “navigation layer” of the Long Tail. It’s not unique to the Internet and, as he points out, it’s not new:

  Interestingly, the power and importance of the navigation layer is not strictly an online phenomenon. For many years American Airlines made more money from its Sabre electronic reservation system (essentially the travel industry’s shared navigation layer for the bewildering world of routes and airfares in the seventies and eighties) than the entire airline industry made collectively from charging people money to ride on planes. From time to time, certain Baby Bells were bringing in more profits from their yellow pages—essentially the navigation layer of all local business before the Web came along—than from their inherited monopolies. And at its peak, TV Guide famously rivaled the actual networks in profitability.

  In a world of infinite choice, context—not content—is king.

  In today’s Long Tail markets, the main effect of filters is to help people move from the world they know (“hits”) to the world they don’t (“niches”) via a route that is both comfortable and tailored to their tastes. In a sense, good filters have the effect of driving demand down the tail by revealing goods and services that appeal more than the lowest-common-denominator fare that crowds the narrow channels of traditional mass-market distribution.

  Reed Hastings, the CEO of Netflix, describes the effect of filters—in this case, sophisticated recommendation engines and ranking algorithms—in driving demand down the DVD Tail on his site.

  Historically Blockbuster has reported that about 90% of the movies they rent are new theatrical releases. Online they’re more niche: about 70% of what they rent from their website is new releases and about 30% is back catalog. That’s not true for Netflix. About 30% of what we rent is new releases and about 70% is back catalog and it’s not because we have a different subscriber. It’s because we create demand for content and we help you find great movies that you’ll really like. And we do it algorithmically, with recommendations and ratings.

  Hastings believes that recommendations and other filters are one of Netflix’s most important advantages, especially for non-blockbusters. Recommendations have all the demand-generation power of advertising, but at virtually no cost. If Netflix suggests a film to you based on what it knows about your taste and what others thought of that film, that can be more influential than a generic billboard aimed at the broadest possible audience. But these recommendations arise naturally from Netflix’s customer data, and it has an infinite number of “billboards” (Web pages customized for each customer and each visit) on which to display them.

  Advertising and other marketing can represent more than half of the costs of the average Hollywood blockbuster, and smaller films can’t play in that game. Netflix recommendations level the playing field, offering free marketing for films that can’t otherwise afford it, and thus spreading demand more evenly between hits and niches. They’re a remarkable democratizing force in a remarkably undemocratic industry.

  ONE SIZE FILTER DOESN’T FIT ALL

  As we get deeper into filters and how they work, it helps to get an overview of their many types. Let’s start with music. Here are some of the many different filter types a typical user on Rhapsody might encounter in a single session as he or she looks for new music. From the front page, a user might start with categories, which is a form of a multi-level taxonomy.

  Let’s say you begin in Alternative/Punk and then choose the subgenre Punk Funk. In that category, there’s a best-seller list, which is led by Bloc Party as I write. If you click on Bloc Party, you’ll find that pattern matching has created a list of related artists, which includes the Gang of Four. A click on that produces a list of “followers” (the Gang of Four created the category of Punk Funk in their first incarnation, in the early eighties), which is a form of editor recommendation (you may also be persuaded by the editorial review).

  Among those Gang of Four followers is the Rapture. Click on that, and if you like it, try a custom radio station tailored around that artist, which is a stream of songs by the Rapture and bands that other people who like the Rapture also like, which is a form of collaborative filtering. As you listen to that custom stream, you may find that among the bands that play, the one you like best is LCD Soundsystem. Click on that, listen for a while, and when you hunger for something new, try a playlist that features the band. That, in turn, will introduce you to Zero 7, where you may want to stay awhile.

  A half dozen recommendation techniques have taken you from punk to soul, from the middle of the Head to the bottom of the Tail, and every step along the way made sense.

  As great as music recommendations are getting these days, they aren’t perfect. One of the problems is that they tend to run out of suggestions pretty quickly as you dig deeper into a niche, where there may be few other people whose taste and preferences can be measured. Another problem is that even where a service can provide good suggestions and encourage you to explore a genre new to you, the advice often stays the same over time. Come back a month later, after you’ve heard all the recommendations, and they’re probably pretty much as they were.

  Yet another limitation is that many kinds of recommendations tend to be better for one genre than for another—rock recommendations aren’t useful for classical and vice versa. In the old hit-driven model, one size fit all. In this new model, where niches and sub-niches are abundant, there’s a need for specialization. An example of this is iTunes, which, for all of its accomplishments, shows a pop-music bias that undermines its usefulness for other kinds of music.

  In iTunes and services like it different genres—such as rock, jazz, or classical—are all displayed in a similar way, with the main classification scheme being “artist.” But who is the “artist” for classical—the composer, the orchestra, or the conductor? Is a thirty-second sample of a concerto meaningful? In the case of jazz, you may be more interested in following the careers of the individual performers, rather than the band, which may have come together only for a single album. Or perhaps you’re more interested in the year, and would like to find other music that came out at the same time. In all these cases, you’re out of luck. The iTunes software won’t let you sort by any of those.

  These are the failures of one-size-fits-all aggregation and filtering. ITunes may be working its way down the Tail, but its emphasis on simplicity—and lowest-common-denominator metadata—forces it into a standard presentational model that can’t cater effectively to every genre—and therefore, every consumer. And this is not to pick just on iTunes—the same is true for every music service out there.

  Because no one kind of filter does it all, listeners tend to use many of them. You may start your exploration of new music by following a recommendation, then once it’s taken you to a genre you like, you may want to switch to a genre-level top ten list or browse popular tracks. Then, when you’ve found a band you particularly like, you might explore bands that are like it, guided by the collaborative filters. And when you come back a week later and f
ind that nothing’s changed, you’ll need another kind of filter to take you to your next stop on your exploration. That could be a playlist—catching a magic carpet ride on someone else’s taste—which can take you to another genre, where you can settle in and start the process again.

  NOT ALL TOP TEN LISTS ARE CREATED EQUAL

  Not long ago, there were far fewer ways to find new music. Aside from personal recommendations, there were editorial reviews in magazines, perhaps the advice of a well-informed record store clerk, and the biggest of them all, radio airplay. Radio playlists, especially today, are the prime example of the best-known filter of all, the popularity list. The Top 10, 40, and 100 are the staples of the hit-driven universe, from Nielsen ratings to the New York Times book best-seller list. But in a Long Tail world, with so many other filters available, the weaknesses of Top 10 lists are becoming more and more clear.

  There’s nothing wrong with ranking by popularity—after all, that’s just another example of a “wisdom of crowds” filter—but all too often these lists lump together all sorts of niches, genres, subgenres, and categories into one unholy mess.

  A case in point: blogs. As I write, Technorati lists the top ten blogs as:

  BoingBoing: A Directory of Wonderful Things

  Daily Kos: State of the Nation

  Drew Curtis’ FARK.com

  Gizmodo: The Gadgets Weblog

  Instapundit.com

  Engadget

  PostSecret

  Talking Points Memo: by Joshua Micah Marshall

  Davenetics Politics Media Musings

  dooce

  What have we learned? Well, not much. There are a couple of gadget blogs in the list, two or three political blogs, some uncategorizable subculture ones (BoingBoing, FARK, PostSecret), and a personal blog (dooce).