O'Reilly Media | Web 2.0: A Strategy Guide

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WEB 2.0 TAKES A FUNDAMENTALLY DIFFERENT VIEW of how businesses, customers, and partners interact, and in doing so, it opens up a range of new business models. Back in 1980, Alvin Toffler's bestseller The Third Wave (Bantam) predicted a new type of "pro-sumer," someone who is a mix of a DIY (do-it-yourself) producer and consumer in offline marketplaces. It was a great vision, but without the recent advances in web and digital technologies, most online broadband and mobile users could not make the quantum leap from being passive viewers and readers to becoming actively participating, socially engaged, and collaborative uploaders—personal contributors and creators of the Web.

Web 2.0 turbocharges network effects because online users are no longer limited by how many things they can find, see, or download off the Web, but rather by how many things they can do, interact, combine, remix, upload, change, and customize for themselves. This online DIY self-expression benefits businesses and other users, not just individual uploaders.

Flickr, a Web 2.0 photo-sharing site, illustrates the business and financial impact of uploaders and their remarkable collective user value. We'll analyze Flickr's multiple revenue streams and cost structures, making you familiar with how to evaluate the customer profitability and financial valuation pros and cons of moving to a Web 2.0 business model.

We'll also contrast it with Netflix, an online video rental company founded during the dot-com era, which uses many of the same technologies but has a fundamentally different—and more difficult—business model.

Most chapters in this book will lead with theory and then go into detail. To get started, though, it makes sense to see what a Web 2.0 company looks like.

Flickr, shown in , is a poster child for Web 2.0. It offers users a way to share photos easily, starting with the simple stream of photos shown in .

Figure : Interacting with the Flickr photo sharing service

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Flickr, shown in , is a poster child for Web 2.0. It offers users a way to share photos easily, starting with the simple stream of photos shown in .

Figure : Interacting with the Flickr photo sharing service

Figure : A user's stream of photos, showing the most recent first

Flickr users who accept the default mode of public photos don't have to do anything more to share their pictures. They can upload them and add captions and comments (metadata) for their own convenience, and other people can see them immediately. If users want to see the latest photos their friends have posted, they can simply visit their Flickr pages. Those photos can also be better organized (), and presented as slideshows ().

Figure : Photos organized by subject

Figure : A slideshow of related photos

This is just the beginning, of course. Flickr offers users a variety of ways to upload and manipulate their photos, several ways to organize them, a fun set of tools for connecting photos to maps, and options for printing photos in a variety of different formats. For a more detailed explanation of what Flickr offers, visit .

Flickr's friendly and easy-to-use web interface and its free photo-management and storage service are great examples of a Web 2.0 "freemium" business model—fine-tuned to leverage collective user value, positive network effects, and community sharing.

The term "freemium" was first introduced on venture capitalist Fred Wilson's blog, A VC (). He described it this way:

Give your service away for free, possibly ad supported but maybe not, acquire a lot of customers very efficiently through word of mouth, referral networks, organic search marketing, etc., then offer premium priced value added services or an enhanced version of your service to your customer base.

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The core business message of Flickr is neatly summarized in a slide from its 2004 launch at the O'Reilly Emerging Technology Conference:

Don't build applications. Build contexts for interaction.

In March 2005, Flickr was a Fast Company 50 winner for "Reinventing a category whose flashbulb burnt out." In the magazine interview, founders Catarina Fake and Stewart Butterfield summed up the basis of their success—their users:

We have quickly created the largest and best-organized online photo library in existence with 1.8 million images, of which 81% are public, and 85% have some human-added metadata. What this means is you can find photographs of anything that strikes your fancy. Flickr is infinitely shareable and easily searchable.

Flickr photo sharing introduces individually uploaded digital content—photos and images—to a global online community. When users upload photos to Flickr, they are usually sharing them not only with friends and family but with communities of Flickr users and the whole Internet as well. Because Flickr's default photo visibility setting is public rather than private, after its first year, more than 80% of all photos were public.

Opening up user-generated and uploaded digital content is the next stage of the open-systems movement started by Linux and followed by Google's open application programming interfaces, or APIs. Open systems and open APIs have a significant impact on hardware and software developers, products, and services. Unrestricted uploaded digital content has a much broader impact on the mass-media market, the millions of broadband and mobile users, and consumers of all media.

This type of shared digital content sets off a positive direct network effect on the breadth and variety of the image database and sparks viral marketing. Each new member adds his uploaded digital photos to the completely user-generated collective Flickr photo database rather than maintaining (or hoarding) a proprietary cache of private photos. Of course, Flickr has given users the choice of sharing their photos openly while maintaining control over licensing and ownership. Almost 130 million photos have been posted by some 3 million registered users. Open photo sharing enables Flickr to be a completely user-generated image database. Clearly, this is the same route that YouTube took a few years later but with a slightly different target: a user-generated video database and open community for online public sharing.

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How does Flickr capture value, and how can it be measured?

Business managers inside a company can analyze their internal business model to characterize and visually diagram a company's profit engine.
Industry analysts or strategists evaluating a company from the outside can compare it with competitors and industry players to assess its stock market capitalization value, acquisition value, or total enterprise value. They can use industry structural analysis and consumer-focused financial valuation.

We'll use the first of these two perspectives—the business model as a profit engine—which is appropriate for managers and entrepreneurs who are making key business decisions and trade-offs to turn their ideas into profits and a sustainable business. We start by asking whether the business has single, multiple, or interdependent revenue streams. Then, we look at each of the sources of revenue, the revenue streams, their growth potential, and the cash flow timing for new customers.

To kick-start or fine-tune a business profit engine, let's start with identifying the inner workings of revenue sources, key cost drivers, investment size, and key success factors. Typically, companies have four choices of how to use revenue streams:

Single stream: The company relies on one predominant revenue stream stemming from one product or service.
Multiple streams: The company collects multiple revenue streams from different products or services.
Interdependent streams: The company sells one set of products to stimulate revenue and growth from another set, for example, razors and blades.
Loss leader: Not every revenue stream of multiple streams are independently profitable, but those that lose money drive traffic to spur other purchases and together they achieve profitability.

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To get at the inner workings of cost structures, the key questions to answer are the following:

What are the largest cost drivers, and are they fixed, semi-variable, variable, or nonrecurring?
How will the cost drivers change over time, by unit volume and by number of customers and usage?

From the outset, Flickr found innovative ways to avoid the four major cost drivers of the retail photo printing business and online stock photo companies. Flickr's collective user value strategies convert its significant cost savings into a competitive advantage and positive network-effects generator.

The first key cost driver is inventory. A typical stock photo company—online or offline—must acquire a high-quality stock photo inventory and develop a cataloging and management capability to make a large and broad inventory accessible and easily distributable to viewers, potential buyers, and image licensors.

The second key cost driver is payroll. A retail photo printing business has direct payroll costs for employees who are involved in the photo development and printing process, as well as indirect or support payroll for employees who are at the checkout counter or involved with the maintenance of the store equipment or supplies.

The third key cost driver is information technology systems and developers. Most web stores spend a large proportion of their costs on IT design, development, maintenance, and payment systems compared with offline retail stores that instead have space/rental costs (driven by real estate in square footage) for office or retail space.

The fourth key cost driver is marketing, advertising, and customer relationship management (CRM). Marketing and advertising costs are higher pre-sales, and customer relationship management costs are often higher post-sales. Because the barriers to entry are low in the retail photo printing business and online stock photo business, marketing, advertising, and customer relationship management are critical for differentiation, as well as for traffic and new customer acquisition.

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Yahoo! bought Flickr for an estimated $30 to $40 million in March 2005. Although Flickr's founders reported () that they would "no longer have to draw straws to see who gets paid," the reality was much brighter. Flickr could bring its hypergrowth strategies to Yahoo!, and Yahoo! could provide additional publicity and infrastructure to the growing photo service.

Flickr's value, though, is a tough question. Value is clearly not just the infrastructure of the company, or even the brand. For a company growing like this, the value depends on the customers. In the past, this statement was agreed to in principle but difficult to quantify. Financial valuations of companies were calculated on earnings multiples and on forecasts of market and unit production growth. However, new forms of "customer-based" company valuation formulas and models were developed to analyze the many subscriber businesses and services such as cable and cell phone services, in which revenues are directly tied to customer fees, not unit prices.

Tracking individual customer behavior and metrics rather than unit sales volume as the actual "basis" for revenue growth and business models leads to terminology that is relatively unfamiliar to most business managers and M.B.A.s. Analysts use the terms "individual customer profitability," "average lifetime customer value," and "loyalty" to emphasize that quantitative metrics in many customer-focused industries—including the gaming and casino industries—can be aggregated to arrive at fine-grained financial enterprise valuations. These metrics can also be analyzed strategically to dramatically improve profitability at the individual customer level. Harrah's Casino is an exemplary case: quantitative individual customer analysis of its "VIPs and high-rollers" changed the company's service and business model dramatically.

Using the basic total enterprise value formula with a discounted cash flow model for lifetime values is particularly important when the average lifetime of an average subscriber can range from one month to five years. It is also important when there is a high risk that users in the installed base will "churn" or "switch" between different plans or companies, but fees are received on a regular schedule, such as monthly.

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Netflix is a proud survivor of the dot-com boom and bust, and in the years since then, it has added more and more community features to its site. Like Flickr, Netflix:

Appeared at a time when the nature of a communications medium was changing
Distributes a huge quantity of visual information to its users
Depends on an ever-evolving web interface for interacting with its customers
Grew rapidly thanks to users reporting their experiences to their friends (quickly developing market share that couldn't easily be challenged)

Unlike Flickr, however, Netflix began in an era when it was still difficult for people to create shareable content, and delivering its services meant physically moving a DVD from its warehouse to the customer and back. The physical nature of the DVD and the cost of purchasing DVD content gave Netflix a set of problems whose solutions point the way toward many of the advantages of a pure-web approach.

"Burn rate" was a popular term during the dot-com boom. Because economies of scale were a critical advantage of the Web, the general idea was to grow a company's market share rapidly. The cash flow curve that looks like a J-curve, shown in , demonstrates what would happen as startup companies tried to buy new customers and market share with their investors' dollars.

Figure : A J-curve for cash flow

The first part of the slope reflects the period when a company is spending more to build market share than it's making in revenue. The burn rate is initially steep, as the company spends money on marketing, hiring, and expanding infrastructure, but customers haven't yet rewarded that investment. As more customers come in, revenue should start to exceed expenditures, and the curve should fall less sharply, flatten, and then start climbing. When the curve climbs, cash flow is positive, and that will (hopefully) lead to eventual profit.

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Flickr and Netflix have carefully crafted web sites and substantial paying user bases. Flickr's path forward yielded different results for a number of reasons.

The most obvious business difference between Flickr's digital photo-sharing community and Netflix's DVD movie-sharing club is Netflix's customer acquisition costs. These costs were directly tied to how much it cost to build and keep the media-lending library/inventory/database up-to-date. Flickr still has an easier time of it than Netflix, despite Netflix's major changes, as shown in .

Table : Comparing Netflix and Flickr
	NETFLIX BEFORE REVENUE SHARING	NETFLIX AFTER REVENUE SHARING	FLICKR
New customer acquisition cost	$100 (five DVDs at $20/each) DVDs + $5 shipping + platform	$3 DVDs + $3 shipping + platform	0+ Platform
Number of customers	300,000 after three years	600,000 after five years	2 million in two years

Flickr's digital photo database of 100 million-plus photos—85% of which are tagged—is completely user-generated. Netflix's DVD inventory comes from suppliers that expect to be compensated. So, collective user value has an immediate and recognizable impact on the cost structure and cash flow requirements in growing a customer-focused business.

Flickr followed the Web 2.0 curve in rather than Netflix's Web 1.0 curve or a more typical physical-world curve.

Figure : Comparing cash flow in the physical world, Web 1.0, and Web 2.0

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Flickr and Netflix may seem far from your own plans, whether they include an existing business or a startup. The following questions will help you evaluate the lessons of this chapter and possibly apply them to your own projects.

Consider how your business and industry currently work...: To what degree have you opened up to collective user value—multiplying the ways that users inside and outside of your project, team, or organizational unit can easily leverage, aggregate, and spark collective work, knowledge, and systems?
If you took the perspective of a CEO and strategic leader...: How and when do you see Web 2.0-enabled collective user value disrupting the current practices, business model, competitive advantages, and economics of your business and industry? What's the risk of being a leader or laggard? When should this become a boardroom agenda item?
If you took the perspective of a CIO and program manager...: How could you better benchmark, analyze, compare, and quantify the impact of shifts in collective user value and community in key functional areas, such as marketing and sales, product and services development, customer support, inventory management, logistics and operations, recruitment and training, partner and supplier relations and procurement? How can quantifying new customer acquisition costs, cash flow curves, per-user analytics, and per-click metrics provide a new basis for enterprise and financial valuation?
If you are a project team member...: Are you ready to brainstorm together with your group members on how the collective user value practices described for Flickr could be applied effectively in your business—whether consumer-focused or industrial, product or service-oriented, offline or online, local or global, small or large? What event could become a pilot project?

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FOR MOST OF US IN THE REAL (OFFLINE) WORLD, TRAFFIC IS A BAD THING. More cars on the highway at rush hour create negative network effects. Each driver reduces the quality of the experience by congesting and overloading the highway network past its limit. But in the online world, traffic is a powerfully good thing.

Positive network effects created the Web 2.0 network platforms and contributed to the online hypergrowth of networks such as Google, Yahoo!, eBay, Skype, Wikipedia, Craigslist, Flickr, and others. These enterprises have strategically combined different kinds of network effects—including direct, indirect, cross-network, and demand-side—to multiply the overall positive impact of network value creation. Positive network effects explain, for example, why it could make brilliant but counterintuitive economic sense for GoTo—an early search engine innovator—to pay 5 cents to acquire a new search user just to get advertisers to pay 1 cent or more for that search user's pay-per-click keyword advertising.

Latecomer Google demonstrated a complete set of two-sided network effect multipliers that enabled it to be the first to reach critical mass and sustainable profitability in the paid keyword search race, even before first-movers GoTo and Excite. Ad-revenue-based online competitors, like Google, are disrupting the rules of the game for their offline rivals in the technology and media industries by providing free services to search engine users (the consumer-focused side of the Google platform), subsidized by advertisers (the second side or group linked to the Google platform by the AdWords self-service advertising network).

U.S. advertising expenditures were about $100 billion in 2007, nearly half of the global total. Just for comparison, U.S. venture capital investment in all stages (from early to late) during the first quarter of 2007 was a relatively modest $7 billion and was probably less than $30 billion for the year. U.S. marketers will continue to shift their spending into online advertising for a projected total of $19.5 billion in 2008, with $8.3 billion being spent on paid search ads, which are typically PPC, cost-per-action (CPA), and online sponsorships. Growth is coming from "new money": 44% of the companies in search advertising started in the past two years and are buying more keywords, leading to higher prices and overall increases in budgets and spending.

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Positive network effects increase the value of a good or service as more people use or adopt it. The simplest network effects are direct: increases in usage lead to direct increases in the value of the system. Telephone service is a great example of this. The more people available to call, the more valuable the system becomes.

Web-enabled online networks have generated several new types of positive network effects. They combine the powerful economic characteristics of digital economics—high upfront costs but negligible incremental costs—with the opportunities of exponential network growth in users and usage, as well as willingness to pay. When increases in usage create more value across all users, a rise in returns is generated that alters the nature of the competition substantially. Achieving critical mass offers the potential for exponential growth, as we saw with Flickr in the previous chapter.

In Web 2.0, managing combinations of online network effects is key to competitive success for the following reasons:

Upfront capital costs have dropped so that there are lower barriers to entry and frictionless scalability in online networks compared with physical networks. As a result, customer acquisition costs are reduced, and free basic services (rather than only promotional or trial usage) are relatively low-cost and sustainable in the long term.
Online networks have strong demand-side scale economies where users bring other users. Social and/or late users can increase the overall global value of the network for all members and create a bandwagon or "tippy" effect, whereby the market tips in favor of one company or another. This is rarely seen in physical networks—which tend to be dominated by economies of scale in production—where higher volume leads to lower unit costs and commoditization, rather than higher or premium prices and increased market attractiveness.
Online networks form faster, more frequently, and more interactively than before. Active one-percenters

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Most markets connect only two groups: buyers and sellers. Buyers are the source of revenue; sellers provide goods or services in return. Economists call markets that connect two or more different groups of customers/users to sellers/partners n-sided markets, with the n referring to the number of different groups (see , which was modified from tables and examples in Marco Iansiti and Roy Levien's book The Keystone Advantage (Harvard Business School Press) and HBR article "Strategies for Two-Sided markets" (Eisenmann et al.), see end notes N-sided markets and ecosystems.).

American Express, eBay, Kaiser Permanente, Nintendo, and Microsoft are all examples of companies that orchestrate or provide a platform for n-sided markets.

Visa is often cited as an n-sided market because its credit cards connect communities of retailers, banks, and consumers. In the case of credit cards, it's easy to see that n-sided markets unite interdependent communities. The whole ecosystem would fall apart if there weren't enough of each group present to provide a critical mass. So, although some markets can operate with a small number of customers—maybe by pricing a premium amount for each additional user or customer—Visa has zero value to retailers without a critical mass of cardholders, and vice versa. We can see a cross-network effect: the more retailers that participate worldwide, the more beneficial the card is to its users. Thus, it is important to Visa to be "Everywhere you want to be"; American Express positions itself similarly with "Don't leave home without it."

Table : N-sided markets in a variety of sectors
INDUSTRY	PLATFORM	SIDE 1	SIDE 2	FREE OR MINIMAL	SOURCES OF REVENUE
Search

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Google had a great foundation to build on: the PageRank algorithm that used links among sites to determine their likely relevance in a search. Google succeeded because it was able to build on network effects PageRank created in one area, then spread the results of that work to other areas where more network effects could multiply its resources still further. Consider the following:

Direct search engine network effects: Each new search query from users dynamically updates the PageRanking and user relevance of the search engine. Google also increased traffic and usage through affiliate deals with AOL, AskJeeves, and others, using a different revenue split with affiliates than was normal at the time.
Direct advertiser network effects: Performance-based pay-per-click made it easy for customers (and Google) to monitor advertising. Google made AdWords cheap and easy to use for small- and medium-size businesses that were new to online advertising, giving them a do-it-yourself system for creating and monitoring ads. Google's $5 to enroll and 5 cents paid per click enticed a lot of new people and got them talking.
Advertiser-searcher cross-network effects: Both small and large advertisers wanted the search engine with the most search queries and users.
Demand-side network effects: the advertiser's willingness to pay: AdRanking dynamically priced keywords and created pricing auctions for advertisers. Pay-per-click delivered return-on-investment metrics and customer behavior information, and revealed the cost-effectiveness of online versus offline advertising for direct marketing and branding. Advertisers started putting more marketing and ad dollars into Google's coffers.

All four of these effects reinforced each other. Before we talk about the first three—the better-known direct, indirect, and cross-network effects—let's backtrack and fill in some background on the last network effect.

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Positive feedback can easily be confused with rapid growth because with positive network effects, success seems to feed on itself—the strong get stronger and the weak get weaker. Positive feedback amplifies virtuous cycles—the strong getting stronger. Just as quickly, however, positive feedback can amplify the shift in the other direction, a vicious cycle where the weak get weaker. is a conceptual illustration of this.

Figure : Virtuous and vicious cycles created by network effects

When two or more companies are in a competitive race for market share where there is strong positive feedback due to network effects, only one company emerges as the winner. (Economists call this market tippy because it can tip in favor of one company or the other.) Strong positive feedback can lead to a winner-take-all market dominated by a single firm or technology.

To show how a winner-take-all market evolves, Carl Shapiro and Hal R. Varian developed the diagram shown in and in their book Information Rules: A Strategic Guide to the Network Economy (Harvard Business School Press). A race may be very close, with one company or technology starting with an initial lead and more than half the market, and then experiencing a virtuous cycle and growing to nearly 100%. However, the company or technology that lags in this critical period with a little less than half the market will experience a vicious cycle that drives a decline to less than 10%. The positive feedback that starts the virtuous or vicious cycle is amplified by the perception and bandwagon desire of the users to select the company or technology that looks like it is going to win and have the most users. No one wants to be stuck with an incompatible (or worse, orphaned) technology that no one else uses or services.

Figure : Competitive race with positive feedback

A classic example of this kind of tippy market is the videotape recorder market in the 1980s, when the VHS standard (backed by and licensed to a global group of companies led by JVC and Matsushita) competed against the Beta standard (backed by Sony). Notice in that the key crossover point between the VHS technology standard and Beta actually occurred in 1978 at the 50% market share point.

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The two natural experiments in Google's past turned out to be tipping points early in its evolution and tippy markets a few years later:

Google, as a latecomer, was able to match or copy several paid search network strategies innovated by Bill Gross of GoTo/Overture. However, its distinctive positive network multipliers—as featured in PageRanking, AdRank, and AdWords—were critical deciding factors.
AOL helped tip the paid search market to make Google's average U.S. search revenue per query more than three times that of its competitors. Positive network effects explain why AOL's 7–9% market share points were worth as much as $4 billion to Google, even though analysts argued at the time that $1 billion was too much to protect Google's traffic from falling into Microsoft's hands.

Google's experience may seem unique, as its explosive growth and status as an icon have led to tremendous capitalization. However, although Google has seized the search engine market, there is still plenty of room for others to follow a similar path in other markets—and even use Google's tools. shows a critical sequence of events on the path to success.

Figure : A Web 2.0 path to growth

Following these curves—and not sliding back on them, or suddenly stopping—requires several events to occur in the right combination:

Starting up the adoption curve: If no one ever hears about your product, it's going to be very hard for it to succeed. To create buzz, you must combine ease of use, attractive results, and an initial user base. Early adoption is critical, and the climb up the S-curve is rarely easy.
Avoiding the chasm: Too many products reach a certain market of early adopters and then halt, unable to reach a broader mainstream audience. Product cost is a classic adoption barrier, one that's fairly easy to avoid in a web environment. Reputation is also critical; anything that alienates adopters may send them to your competitors. Try to ensure that in addition to providing users with direct benefits, you also make it easy for them to stay with your service.

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Your company may not be Google, and even if you work at Google, you're probably not planning to reinvent what's been done. However, these questions will help you apply the lessons of its experience to your own projects.

Think about positive network effects...: Taking place in your business, ecosystem, and industry. To what extent do you actively consider and work with positive network effects as a fundamental process for accelerating and multiplying your business value? Are you effective at monetizing network effects? Why or why not?
If you considered positive network effects as a fundamental strategy...: What specific implications would it have for how you run your business and compete effectively?
What are some immediate and practical ways...: You can imagine to raise the awareness of those in your business, organization, and ecosystem about the power of monetizing and multiplying network effects?
As a project team member...: Are you ready to systematically analyze with your group members the full range of network effects described for Google that could be applied effectively in your business—whether consumer-focused or industrial, product- or service-oriented, offline or online, local or global, small or large? What event could become a pilot project?

As users visit your site, do you learn from them, or just present information to them?
Can you make users happy by helping them find information you don't control?
Are you prepared to serve large numbers of users if they arrive?
Can you reach critical mass for your business by buying other businesses or providing them with services?

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IN OCTOBER 2007, SILICON VALLEY WAS BUZZING. Microsoft's $240 million advertising deal and investment in Facebook, for a 1.6% equity share, valued the 3-year-old company at a total enterprise valuation of $15 billion (compared to Google's public stock valuation of $181 billion at a stock price of $600 a share). Some observers immediately dismissed the number as a throwback to the dot-com bubble, the "irrational exuberance" of naïve and enthusiastic stock purchasers in the late 1990s. But the "smart money" venture capitalists and private-equity firms took notice.

After all, Microsoft and its investment bankers were sophisticated mergers-and-acquisitions dealmakers. There were whispers of a closed round of bidding where Google's outright offer of $11 billion had been the "floor" for anteing up, with all of the large multinationals and media firms expressing interest. From the point of view of Facebook and Microsoft, the final deal was a win-win. Facebook's privately held stock was ratcheted up as if it were already publicly valued by the $240 million transaction, and Microsoft's stock gained as well upon the announcement.

Financial deal making aside, what kind of financial analysis might tell us whether Facebook was worth $15 billion? Let's turn to the generalized framework of the customer-based financial valuation model we explained in , in valuing Netflix as the sum total of the lifetime value in subscription fees of its installed customer base (a methodology originally developed for cable and cell phone subscription companies).

A Web 2.0 online social network like Facebook has three immediate and powerful advantages over those previous customer-based enterprises:

Facebook has proven itself to be a much more powerful customer-acquisition engine, using its viral social marketing and distribution online to attract 47 million customers in less than 3 years.
These 47 million free users are highly interactive and engaged with Facebook.
Facebook is a social network advertising platform. The value of this installed base of 47 million free users is immediately monetized through target advertising revenues—cash flows in much faster and more predictably than it would from monthly subscription fees. More importantly, the cross-network value to the advertiser is

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In The Tipping Point: How Little Things Can Make a Big Difference (Back Bay Books), Malcolm Gladwell tells the story of Paul Revere and William Dawes. Every American schoolkid knows the basics of the story. In April 1775, in Boston, a young stable boy overheard a British army officer tell another that there would be "hell to pay tomorrow." The stable boy's news tip was passed to the local silversmith Paul Revere, who mounted his horse and began his famous midnight ride from Boston to Lexington, crying, "The British are coming! The British are coming!" He spread the news like a virus and mobilized a critical mass of neighbors, farmers, and merchants who jumped out of bed and armed themselves.

But not many people remember William Dawes. Dawes rode just as far, on a different route, knocking on just as many doors. Why is Paul Revere remembered while William Dawes is not? As Gladwell tells it, because Revere had a gregarious and social personality that could bring people together. Dawes had only ordinary social abilities. Gladwell suggests that certain kinds of people matter to "tipping" word-of-mouth epidemics; we're all familiar with them in our everyday offline social world (see ):

Connectors: The "social glue" who know and want to introduce you to everyone "you should know" whether for matchmaking or career mentoring
Mavens: "Information brokers" who can't wait to tell you about the best deals and give you advice on where to stay and what to buy
Salesmen: "Evangelists" who get you to act and convince you to buy

Figure : Key roles and linkages in social networks

Paul Revere was a potent combination of connector, maven, and salesman, with late-breaking news to broadcast, thanks to the news tip from the stable boy—who was a natural maven.

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In some ways, online networking is much like offline networking—the social skills you know from the offline world are still helpful. However, connecting by web sites and email makes it more like a network of people who are all in the same room, ready to make introductions without the small talk. It's not a replacement for face-to-face conversation, but it's certainly a supplement that changes the rules.

Two things change the "tipping" of word-of-mouth epidemics in the online world:

The availability of personal content uploaded online
The speed of connecting online to someone who you don't know but want to be linked to or get a message to

Online is a small world. With just a few clicks, users can reach people they want to know. Increasingly, people get their first impressions from online rather than offline encounters.

In the late 1960s, the sociologist Stanley Milgram investigated what came to be known as the "small-world phenomenon." He conducted an experiment to find connections linking people in the United States who did not know each other. He gave a letter to someone in Nebraska, with instructions that the letter had to reach a particular person in Massachusetts. The first person was told only basic information about the "target," such as his address and occupation, and was told to give or send the letter to someone she knew on a first-name basis, and that person was given the same direction, to deliver the letter to the target as efficiently as possible. Anyone who received the letter would follow the same instructions until the target was reached. Through repeated trials, Milgram found that it took five or six "steps," on average, to get a letter from Nebraska to Massachusetts. This formed the basis for the well-known concept of "six drgrees of separation" (shown in ).

Figure : Degrees of separation

In his book Six Degrees (W. W. Norton & Company), Duncan Watts points out that certain paths were considerably shorter because the Milgram package reached a "hub" or "broker" node that shortcut the average six steps. illustrates this by putting an additional circle on the hubs or broker nodes and showing the different paths on the right and left side.

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Facebook, YouTube, Skype, MySpace, and Flickr show that a Web 2.0 company's business and financial valuation depends on the number of users and how quickly those users accept, adopt, and bring their positive network effects to a new online service. In the social networks and advertising platforms, these users can be monetized immediately, through advertising and n-sided market sponsorship. Clickstreams, average revenue per user (ARPU), individual customer profitability, and advertising ROI can be tracked with web analytics daily and even hourly.

In the study of high-tech marketing and management of innovation, the Rogers Adoption Curve is often used to explain the rate of adoption of a new technology or product.

In 1962, Everett M. Rogers, in his book Diffusion of Innovations, gauged how populations adopt new products and technologies. He later suggested that five factors explain why some new products succeed with high growth rates and rapid customer adoption and others fail:

Relative advantage: How much better the new product is compared with the old one. Angioplasty is 10 times more effective than open-heart surgical bypasses, it is less invasive, and it allows faster recovery.
Compatibility: If a new product fits with current values and usage, it broadens the initial audience. Major changes are more risky and appeal to a relatively smaller group of early adaptors, independent thinkers, and innovators.
Complexity: Ease of use and understanding of features make adoption faster and easier.
Trialability: Products can sell themselves if customers experiment with them and get hooked by the personal experience. Free trials, demos, and test drives reduce the risk.

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For a lot of people, LinkedIn defines business networking. Its contact management enables people to connect to each other easily, offering a self-updating contact list that helps them find the connections they need. It even looks a bit like a classic address book, as shown in .

Figure : LinkedIn's connections list for a small set of connections

Even this simple address book, however, leads into the possibilities that electronic contact management offers. Note the icons in the right column, just to the left of the ad. The address book tells users how many contacts their contacts have, letting them see at a glance how well-connected their contacts are. Clicking on that icon displays the other person's contacts, making it easy for users to dive into a network of people they might be interested in knowing.

Searches also let users find more people they might want to contact and tells them how many degrees of separation stand between their personal contacts and them, as shown in .

Figure : Search results with relationship information

The relationship column shows how many degrees of separation stand between the searcher and the contact. Clicking on a name brings up a profile, with a "Get introduced through a connection" option. Mutual friends can then help establish a more direct LinkedIn connection.

LinkedIn put members' existing networks of business relationships and business contact information onto the Web. By putting members' rolodexes (the rotating file devices used to store business contact information such as business cards) online, these networks became more easily searchable, and the networks of people who knew each other could be easily connected and linked. The signup or joining process had a strong viral online word-of-mouth effect—anyone could become a member, but 90% of members joined in response to an email invitation from an existing member.

Most businesspeople have received scores of email invitations to join LinkedIn or Plaxo, and now Facebook. The email invitation allowed you to click through to a membership page. Then you could upload a simple profile with name, region, and industry, or a longer bio with photo, education, career, and other professional affiliations. As soon as the profile was loaded, new members were linked to the member who invited them and could then extend their networks by inviting others to join, asking existing members to connect to them, or accepting invitations to connect from existing members. Connections had to be agreed to by both parties, and members were free to disconnect from any unwanted contact.

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It started out as a pretty simple application—an upgraded version of the classic print photobooks some universities hand out to new students—and has grown into a much richer set of tools. shows a typical profile, and shows the interface for editing that profile. Users can present a lot of information without having to master a complex interface.

Figure : A Facebook profile

Figure : Editing that Facebook profile

Facebook (like most social networks) also lets users communicate within their network, as shown in .

Figure : Communicating within Facebook

The hypergrowth of the Facebook user base continued as it developed, from 5 million online users in late October 2005 to more than 7.5 million in mid-April 2006.

Facebook enjoyed an exponential growth pattern much like the S-curve discussed in . It benefited from direct network usage effects: the more a user's friends use Facebook, the more valuable it is to the user. Additionally, peer pressure and social influence fuel the "contagion" and word-of-mouth effect. If your friends are not using Facebook, why should you?

College students didn't want to have to wait to see their friends show up and start using Facebook. So, speed of adoption is important to get to critical mass quickly.

Speed is also important in the race to reach a high enough market share to tip the market and lock out competitors. Facebook reached critical mass and tipped the market before other competitors entered the same space. The Korean social network site Cyworld seized a similar early-mover advantage in its national market. When first-movers in strong network-effects markets reach a dominant market share, they become hard to displace.

The usage patterns were impressive for the frequency as well as retention. Facebook's Mark Zuckerberg explained:

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The online social networking experience teaches three critical lessons:

The importance of social networks and network effects for building your business to scale
The value that users can generate by sharing even basic information with a larger group
The incredible acceleration provided by bringing this kind of task to the Web

While all of these clearly apply to the explicit social networking applications examined in this chapter, they also apply to other projects that may not be thought of as explicit social networks.

Social networks have always been a key part of sales and marketing. When you're trying to sell a product, you want to find key influencers. The acceleration that social networks provide in a Web 2.0 market has two major effects in this regard:

Social networks (even informal clusters) can make or break a product by spreading positive news of its existence to other potential users or by recommending a competitor.
The potential of online social networks to help people meet others they want to meet can entice ever-growing numbers of people to join an existing network.

LinkedIn provides clear paths for its customers to invite other customers to join its system. Members who invite their friends receive clear and direct benefits, and joining the network costs nothing (except time) for the invitee. This makes it very easy for people to give or get a positive impression of LinkedIn, accelerating its growth tremendously. Facebook's viral marketing benefited from similar effects, amplified by its appeal to contained groups of people. shows how growth curves may vary by the nature of the kinds of people who spearhead the use of the system and their social influence.

Some people have taken this message to mean that marketing will have the greatest effect if it's targeted to key influencers. It's a good idea as a general rule, but always remember that influencers are already used to being targeted and the pool of influencers is constantly changing. Achieving critical mass requires not only reaching influencers but also making it easy for everyone to feel welcome at the party.

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Your business probably isn't Facebook, LinkedIn, or even something that loo

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