The Long Tail

by Chris Anderson

  SAP soon followed with its own online platform strategy, as did several smaller companies with similar models. All the usual Long Tail conventions applied. Such companies aggregate niche software on their respective platforms and provide filter mechanisms (ranging from best-seller lists within categories to user reviews). This helps people move with confidence down the curve into niche applications that may suit their needs better than the monolithic one-size-fits-all software that has dominated the market to date. This model neatly connects head to tail.

  It’s too early to say how well these new software markets will work, but they are yet another example of how lowering the costs of reaching niches can change the game. As Joe Kraus, CEO of JotSpot (another software company attempting to apply this strategy), puts it, “Up until now, the focus has been on dozens of markets of millions, instead of millions of markets of dozens.” He, like a growing number of others, is now betting on the rise of the latter.

  GOOGLE

  The traditional advertising market is a classic, hit-centric industry where high costs enforce a focus on the biggest sellers and buyers. The way it works is that an advertiser, say General Motors, has a marketing budget. GM commissions an advertising firm to create some ads and then a media buyer to place those ads in television, radio, and print and online.

  Meanwhile on the other side, those ad-driven media have their own ad sales forces. They pitch the advertisers and their media buyers on the virtues of their advertising vehicles. If all goes well, millions of dollars change hands. All of it is labor-intensive and made even more costly by the expensive schmoozing that’s required in businesses where a lack of trusted performance metrics makes salesmanship and personal relationships key to winning business.

  Most ads, whether they run in the Yellow Pages or during the Super Bowl, are actively sold phone call by phone call, visit by visit. Very few just appear because somebody decided to advertise. These days salespeople don’t just twist arms, they also serve as advertising consultants, informing advertisers about the most effective ways to use a given medium or brainstorming creative new approaches to getting the advertisers’ message out. That works well enough, but because it’s expensive, it imposes a subtle cost: a focus on just the largest and most lucrative of potential advertisers. In other words, the system is biased toward the head of the advertising curve.

  As with every other market we’ve looked at, that head is just a tiny fraction of the potential market. But because it’s so expensive to sell advertising the traditional way, the smaller potential advertisers have been left to their own devices, mostly picking up a phone and placing a classified ad or sending some homemade display copy to the local newspaper.

  That’s pretty much how advertising has worked for most of the past century. But in 2001, a two-year-old Google, the fastest-growing search engine on the planet, started looking for a proper business model. And just as it had done search differently from its predecessors, it decided to do advertising differently, too. Borrowing a model pioneered a few years earlier by Bill Gross, the entrepreneur who started Overture, Google built what would become the most effective Long Tail advertising machine the world has ever seen.

  What Google realized is that if it could take most of the cost out of both selling and buying advertising, it could dramatically increase the pool of potential ad buyers and sellers. Software could do almost all the work, thereby lowering the economic barrier to entry and reaching a much larger market.

  Google’s advertising model has three important Long Tail characteristics. First, it is based on search keywords, rather than banner images, and as we’ve already seen, there is a virtually infinite Long Tail of words and word combinations. Search terms work the same way—here’s a chart of search terms (circa 2001) provided by Joe Kraus, the cofounder of the Excite search engine:

  The top ten words account for just 3 percent of all searches. The rest are spread between tens of millions of other search terms. What Google realized is that each one of those unique search terms is an equally unique advertising opportunity: tens of millions of expressions of interest and intent, each of which could be converted into a highly targeted advertising opportunity if the ad placement were determined by exactly the same PageRank algorithms as those that return Google’s search results.

  But how to sell tens of millions of unique ads? There was only one answer: Let software do it. Thus Google’s second Long Tail technique—dramatically lowering the cost of reaching the market. Its technique is based on a simple and very cheap self-service model. Anybody can become a Google advertiser by buying a keyword in an automated auction process where the minimum bid is just $0.05 per click.

  Not only is it cheaper for both Google and an advertiser to use the self-service model, but it also results in more effective ads. Google provides tools to customize and test ads to achieve the highest “click-throughs” (when a consumer clicks on the ad and goes to the advertiser’s site), and it’s not uncommon for advertisers to obsessively tweak their keywords and ad copy until they get the results they want. After all, who knows their businesses better than they do?

  The effect of this model has been to extend Google’s advertising business farther down the tail than any company ever has. Today, there are thousands of small Google advertisers who had never advertised anywhere before. Because of the self-service model, the measurable performance, the low cost of entry, and the ability to constantly tweak and improve the ads, advertisers are flocking to this new marketplace. They don’t have to have their arms twisted; no human at Google need ever contact them at all. The result: fewer employees and a model that is as efficient in the tail as it is in the head.

  Finally, Google did the same for publishers. Traditionally, there were only two significant ways for Web publishers to make money from advertising. They could either hire their own ad sales forces and court likely advertisers, or they could join an ad network and take whatever they were given at rock-bottom prices. Google’s insight was that the same relevance-finding technology that could match the right ad with a keyword search could also put the right ad on a third-party content site.

  Today, whether you’re the New York Times or a blog, you can put a couple lines of HTML code on your site and it will display Google ads—targeted to whatever content you’re providing. Again, it’s self-service: no permission or phone call required. Every time an ad is clicked on, the advertiser pays Google, and Google passes some of the money on to you.

  Google doesn’t care whether you’re a professional or an amateur, or how narrow or broad your content may be. If the ads aren’t working, Google will automatically replace them with different ads to see if they work better. Because the pages (“inventory”) cost Google nothing, it can afford to wastefully run ads that no one ever clicks on—the “opportunity costs” of the lost potential revenues are borne by the third-party publisher. It’s a remarkable way to extend the advertising market down the Long Tail of publishing, which includes hundreds of thousands of blogs.

  At Google’s first shareholders meeting, CEO Eric Schmidt elaborated on why he describes Google’s mission as “serving the Long Tail.”

  He started by showing a slide of a powerlaw with dollars on the vertical axis and people on the horizontal one. Wal-Mart was at the very head. The number “6 billion” was at the end of the tail. Schmidt explained:

  We took a look at our market last year and asked ourselves: “How are we doing?” If you look at the advertiser, the market we’re in from the largest companies—Wal-Mart—in the world, all the way down to the smallest companies in the world, the single individual. We call this The Long Tail. A lot of people have been talking about it—it’s a very interesting idea.

  We looked at this and we said, “We’ve been doing really well up until now in the middle part of this—well-run, mid-sized businesses, smart people solving interesting problems. But how well do we do against the problems of the very largest customers?” So last year we brought out a whole suite of tools for v
ery large advertisers who can use our services in all of their divisions to generate lots and lots of revenues because, of course, in our model the advertising drives predictability, it drives conversions, and so forth.

  And what about the individual contributor, the small business, the company where Joe or Bob is the CEO, the CIO, the CFO and the worker and the support person—a one-person company, a two-person company, a three-person company? We built a whole bunch of small, self-service tools which allowed them to almost automatically use this service.

  So [we went] in both directions. By going to the bottom with self-service, we were able to reach advertisers who fell below the threshold of traditional advertising. And by going all the way to the top, we were able to capture very large and historically undeserved businesses as well as a whole new area that never had access to these kinds of online services.

  Schmidt later explained to me how these millions of small to mid-sized customers represent a huge new Long Tail ad market:

  The surprising thing about the Long Tail is just how long the Tail is, and how many businesses haven’t been served by traditional advertising sales. The recognition that businesses such as ours show a Pareto distribution appears to be a much deeper insight than anyone realized. It’s something that scientists have known for a long time, but it’s never gotten any attention. When we looked at our business, we concluded that we built a model that works particularly well in the middle of the curve. After reading the [original Wired] article, we looked at the Tail and asked ourselves, “How are we doing against this opportunity?”

  Take a Pareto curve of the world’s businesses, ranked by revenue. Number one is Wal-Mart. So what is the last entry? It turns out it’s a person in India with a basket selling something they made. The area under that curve, which includes about a billion people, is essentially the world’s GDP. So start at the bottom and move up the curve until you’ve got people with an Internet connection. They’re reasonably educated, they’re a small business, and they want to market their goods. And we ask ourselves, “What benefit can our model bring them to increase their revenues?” And the answer is that if we let them do business outside their own villages, they’re reaching a larger market, have got more suppliers, better price competition, and so on.

  There are a lot of reasons why this is slow to happen, mostly having to do with infrastructure. So let’s say for the purpose of argument that we don’t focus on 90 percent of the people. That still leaves 100 million people. The numbers are so large that you can lop off a large chunk and it’s still a huge market.

  Google now has revenues of more than $5 billion a year, and that’s doubling every nine months. Although most of its revenues come from the head of the curve, most of its customers are somewhere in the tail, which suggests that this is where much of its growth will come in the future. And Google’s just getting started.

  One of the interesting things about Google is how many ways it plays the Long Tail game. As discussed, it’s an advertising aggregator, creating a market where the Long Tail of advertisers can reach the Long Tail of ad-driven publishers. But Google is even better known as an information aggregator, and as such it has shown some interesting techniques in evolving away from a one-size-fits-all model.

  One of the problems with Apple’s iTunes music aggregator is the limited way it displays very different genres of music. The same challenge exists with information—it may all start with words, but they can appear in many different contexts. Google realized that different contexts need different presentations. So if you’re searching for a place, you probably want a map view. If you’re searching for an image, you probably want a visual view. If you’re searching for video, you probably want a video view. Again, one size doesn’t fit all—even in the case of a search. Google now offers different styles of “vertical search” (search just within a single category): Google Local, Google Scholar (academic papers), Google Maps, Google Product Search, Google News, Google Book Search, Google Video, and so on.

  Now that Google has been joined by Yahoo!, Microsoft, and others, the rise of the vertical search market is simply a case of slicing aggregation into niches, optimized for different needs. Each of Google’s search products has a unique presentation and pulls from a subset of the information universe that gives the most appropriate and useful results. In other words, it customizes the display of searches in a way that’s meaningful for each particular medium.

  The virtue of this is that if you know at least the kind of thing you’re looking for, and if you use a focused, fine-sliced aggregator rather than a generalized aggregator, you’ll get better results. And the better the result, the more likely people are to continue digging deeper, barreling down the Long Tail of everything.

  14

  LONG TAIL RULES

  HOW TO CREATE A CONSUMER PARADISE

  The secret to creating a thriving Long Tail business can be summarized in two imperatives:

  Make everything available.

  Help me find it.

  The first is easier said than done. Fewer than a dozen of the 6,000 films submitted to the Sundance Film Festival each year are picked up for distribution, but most of the rest of them cannot be legally shown outside of a festival because their music rights have not been cleared. Likewise for most TV programming in the networks’ archives: It’s too expensive to clear the DVD or streaming distribution rights to the music.

  Similar rights issues also keep classic music and video games under lock and key. Until we have some way to clear the rights to all the titles in all the back catalogs—thoughtlessly, automatically, and at industrial scale—legal restrictions will continue to be the primary barrier to growing the Long Tail.

  The second necessary element is moving more quickly. From collaborative filtering to user ratings, smart aggregators are using recommendations to drive demand down the Long Tail. This is the difference between push and pull, between broadcast and personalized taste. Long Tail businesses treat consumers as individuals, offering mass customization as an alternative to mass-market fare.

  For the entertainment industry, recommendations are a remarkably efficient form of marketing, allowing smaller films and less mainstream music to find an audience. For consumers, the simplified choice that comes from following a good recommendation encourages exploration and can reawaken passions for music and film, potentially creating a far larger entertainment market overall. (The average Netflix customer rents seven DVDs a month, three times the rate of the bricks-and-mortar faithful.) The collateral cultural benefit is much more diversity, reversing the blanding effects of a century of distribution scarcity and ending the tyranny of the hit.

  Now that you’ve got the big picture, here are nine rules of successful Long Tail aggregators:

  LOWER YOUR COSTS

  Rule 1: Move inventory way in…or way out.

  Sears blazed the trail. It achieved its first big efficiencies with the old mail-order advantage of large, centralized warehouses. Today, the online sides of Wal-Mart, Best Buy, Target, and many others are using their existing warehouse networks to offer far more variety online than they do in their stores, because centralized inventory is so much more efficient than putting products on shelves in hundreds of stores.

  To offer even more variety, companies such as Amazon have expanded to “virtual inventory”—products physically located in a partner’s warehouse but displayed and sold on Amazon’s site. Today, its Marketplace program aggregates such distributed inventory, products held at the very edge of the network by thousands of small merchants. Cost to Amazon: zero.

  Digital inventory—think iTunes—is the cheapest of all. We’ve already seen the effect the switch from shipping plastic discs to streaming megabits has had on the music industry; soon the same will come to movies, video games, and TV shows. News has left the paper age, podcasting is challenging radio, and who knows, you may already be reading this book on a screen. Eliminating atoms or the constraints of the broadcast spectrum is a powerful way to
reduce costs, enabling entirely new markets of niches.

  Rule 2: Let customers do the work.

  “Peer-production” created eBay, Wikipedia, Craigslist, MySpace, and provided Netflix with hundreds of thousands of movie reviews. At the same time, self-service enabled Google to sell advertising for a nickel a click and Skype to sign up 60 million users in two-and-a-half years. Both are examples where users happily do for free what companies would otherwise have to pay employees to do. It’s not outsourcing, it’s “crowdsourcing.”

  The advantage of crowdsourcing is not just economic; customers can do a better job, too. User-submitted reviews are often well informed, articulate, and most important, trusted by other users. Collectively, customers have virtually unlimited time and energy; only peer production has the capacity to extend as far as the Long Tail can go. And in the case of self-service, the work is being done by the people who care most about it, and best know their own needs.

  THINK NICHE

  Rule 3: One distribution method doesn’t fit all.

  Some customers want to go to stores. Some customers want to shop online. Some customers want to research online, then buy in stores. Some customers want to browse in stores, then buy online. Some want it now; others can wait. Some customers are near stores; others are scattered to the winds. Some products have concentrated demand; others have distributed demand. If you focus on distributing to just one customer group, you risk losing the others.