Читать книгу Blitzscaling: The Lightning-Fast Path to Building Massively Valuable Companies - Reid Hoffman - Страница 8

Of the three core techniques of blitzscaling, the first and most foundational is to design an innovative business model capable of exponential growth.

The story of entrepreneurship in the Internet era is a story of this kind of business model innovation.

Think back to the dot-com era, which stretched roughly from the IPO of Netscape in 1995 until the NASDAQ began to crash in 2000. During this period, enormous numbers of start-ups and pretty much every established company tried to build great Internet businesses, yet nearly all of them failed. The problem was, most of them simply tried to cut and paste existing business models onto the new online medium. You can’t transplant a heart from one species into another and expect it to thrive.

If you had asked stock market analysts in 1995 which companies were best positioned to dominate the Internet, most would have pointed to existing giants like Microsoft and Time Warner, which invested millions in Internet businesses like MSN and Pathfinder. Others would have mentioned “pure play” dot-com start-ups like eToys, which combined proven business models like the “category killer” store with the new online medium.

Yet when the wreckage of the dot-com crash cleared, the most successful companies still charging full steam ahead were the few start-ups that were designed around totally new business models, such as Amazon, eBay, and Google.

Walmart should have dominated online retail, yet Amazon emerged and practically wrote the bible for e-commerce, including consumer reviews, shopping carts, and free shipping. Newspapers and phone book companies should have been able to transfer their information businesses to the online world, but Yahoo! and then Google stepped up to the plate. They built the search engines that indexed the world’s information, and Google developed the business model that made it worth more than all traditional media companies combined.

In contrast, and much to their misfortune, start-ups that relied purely on technology innovation without any real business model innovation largely went bust. Companies like eToys that tried to “Amazon” various markets, but without Amazon’s front- and back-office innovations, crashed and burned once the financial markets began to demand profits rather than just expensive revenue growth. Even Netscape, whose Netscape Navigator mainstreamed Web browsing, and whose IPO kicked off the dot-com boom, was forced to sell itself off to AOL. Netscape engineers invented JavaScript, SSL, and all kinds of cool technology for the Internet that are still used today, but Netscape accepted the status quo when it came to using tried-and-true business models rather than developing new ones that were enabled by its own technology innovation. Unfortunately for Netscape, its competitor Microsoft already understood those business models all too well and knew exactly how to use its economic might and resources to pull their levers. In the first “browser war,” Microsoft preinstalled its Internet Explorer on all new Windows computers, then gave away its Web server software, Internet Information Server (IIS), which effectively destroyed Netscape’s business model.

Could Netscape have succeeded with a different strategy? We believe so. Consider that one of the ways that Netscape monetized its Navigator browser was to sell the sponsorship of its Net Search button to the Excite search engine for $5 million. Netscape believed that the browser itself was the key, while search was simply a sideline. It was left to two pairs of Stanford graduate students, Jerry Yang and David Filo (Yahoo!) and Larry Page and Sergey Brin (Google), to prove that search was a much bigger business. Google’s innovative model of selling text ads next to search results via an automated marketplace allowed it to build a franchise so dominant that it later withstood a series of frontal assaults by Microsoft, including a marketing program in which Microsoft essentially paid people to use its Bing search engine.

The same story has been repeated in multiple waves since. Facebook and LinkedIn dominate social networks even though AOL, Microsoft (Hotmail), and Yahoo! (Yahoo! Mail) controlled most consumer online identities when those social networks first emerged. Alibaba beat eBay in China. Uber outflanked the taxi companies. Airbnb has more room listings than any hotel company in the world.

These success stories are technology companies, sure. But as we’ve seen, technological innovation alone is insufficient—even when its impact on the future is huge. Services like Craigslist, Wikipedia, and IMDb (the Internet Movie Database) were early, influential Internet innovators, but they still never became massively (financially) valuable on their own.

The real value creation comes when innovative technology enables innovative products and services with innovative business models. Even though the business models of Google, Alibaba, and Facebook might seem obvious—even inevitable—after the fact, they weren’t widely appreciated at the time they launched. How many people in 1999 would have realized that running tiny text ads next to the equivalent of an electronic card catalog would lead to the world’s most valuable software company? Or that setting up an online shopping mall for China’s emerging middle class would lead to a $100 billion business? Which of you in 2004 would have predicted that letting people see what their friends are talking about by staring at a tiny screen on a handheld computer would become the dominant form of media? Great companies and great businesses often seem to be bad ideas when they first appear because business model innovations—by their very definition—can’t point to a proven business model to demonstrate why they’ll work.

To really understand why these business models succeed, we need to clearly define what we mean by “business model” in the first place. Part of the problem is that the term can be interpreted in so many different ways. The great management thinker Peter Drucker wrote that business models are essentially theories composed of assumptions about the business, which circumstances might require to change over time. Harvard Business School professor and author Clay Christensen believes that you need to focus on the concept of the “job-to-be-done”; that is, when a customer buys a product, she is “hiring” it to do a particular job. Then there’s Brian Chesky of Airbnb, who said simply, “Build a product people love. Hire amazing people. What else is there to do? Everything else is fake work.”

As Andrea Ovans aptly put it in her January 2015 Harvard Business Review article, “What Is a Business Model?”, it’s enough to make your head swim! For the purposes of this book, we’ll focus on the basic definition: a company’s business model describes how it generates financial returns by producing, selling, and supporting its products.

What sets companies like Amazon, Google, and Facebook apart, even from other successful high-tech companies, is that they have consistently been able to design and execute business models with characteristics that allow them to quickly achieve massive scale and sustainable competitive advantage. Of course, there isn’t a single perfect business model that works for every company, and trying to find one is a waste of time. But most great business models have certain characteristics in common. If you want to find your best business model, you should try to design one that maximizes four key growth factors and minimizes two key growth limiters.

DESIGNING TO MAXIMIZE GROWTH: THE FOUR GROWTH FACTORS

GROWTH FACTOR #1: MARKET SIZE

The most basic growth factor to consider for your business model is market size. This focus on market size may sound obvious, and it’s right out of Pitch Deck 101 for start-ups, but if you want to build a massive company, you need to begin with the basics and eliminate ideas that serve too small of a market.

A big market has both a large number of potential customers and a variety of efficient channels for reaching those customers. That last point is important; a market consisting of “everyone in the world” might seem large, but it isn’t reachable in any efficient way. We’ll discuss this in greater depth when we look at distribution as a key growth factor.

It’s not easy to judge the size of a market, or what pitch decks and venture capitalists often refer to as TAM (total available market). Predicting TAM and how it will grow in the future is one of the main sources of uncertainty in blitzscaling. But predicting it correctly and investing accordingly when others are still paralyzed by fear is also one of the main opportunities for unexpectedly high returns, as we’ll see in the cases of Airbnb and Uber.

Ideally, the market itself is also growing quickly, which can make a smaller market attractive and a large market irresistible.

In Silicon Valley, the competition for venture capital exerts a strong pressure on entrepreneurs to focus on ideas that are going after big markets. Venture capital firms might raise hundreds of millions or even billions of dollars from their investors—limited partners like pension funds and university endowments—who are seeking above-market returns to compensate them for taking a chance on privately held companies rather than simply investing in the Coca-Colas of the world. To deliver these above-market returns, venture capital funds need to at least triple their investors’ money. A $100 million venture capital fund would need to return $300 million over the typical seven- to ten-year life of a fund to achieve an above-market internal rate of return of 15 to 22 percent. A $1 billion fund would need to return $3 billion. Since most venture capital investments either lose money or barely break even, the only realistic way that venture capitalists can achieve these aggressive goals is to rely on a small number of incredibly successful investments. For example, Benchmark Capital invested $6.7 million in eBay in 1997. Less than two years later, eBay went public, and Benchmark’s stake was worth $5 billion, which is a 745 times return. The specific fund that made that investment, Benchmark Capital Partners I, took $85 million from investors and returned $7.8 billion, for a 92 times return. (The initial investors in Facebook did even better, but were individuals rather than firms.)

Given the desire for home runs like eBay, most venture capitalists filter investment opportunities based on market size. If a company can’t achieve “venture scale” (generally, a market of at least $1 billion in annual sales), then most VCs won’t invest, even if it is a good business. It simply isn’t large enough to help them achieve their goal of returning more than three times their investors’ money.

When Brian Chesky was pitching venture capitalists to invest in Airbnb, one of the people he consulted was the entrepreneur and investor Sam Altman, who later became the president of the Y Combinator start-up accelerator. Altman saw Chesky’s pitch deck and told him it was perfect, except that he needed to change the market-size slide from a modest $30 million to $30 billion. “Investors want B’s, baby,” Altman told Chesky. Of course, Altman wasn’t telling Chesky to lie; rather, he argued that if the Airbnb team truly believed in their own assumptions, $30 million was a gross underestimate, and they should use a number that was true to their convictions. As it turns out, Airbnb’s market was indeed closer to $30 billion.

When evaluating market size, it’s also critical to try to account for how lower costs and product improvements can expand markets by appealing to new customers, in addition to seizing market share from existing players. In 2014, Aswath Damodaran, a professor of finance at NYU’s Stern School of Business, estimated that Uber was probably worth roughly $6 billion, based on its ability to ultimately win 10 percent of the global taxi market of $100 billion, or $10 billion. According to Uber’s own projections, in 2016 the company processed over $26 billion in payments. It’s safe to say that the $10 billion market was a serious underestimate, as the ease of use and lower cost of Uber and its competitors expanded the market for transportation-as-a-service.

As Aaron Levie, the founder of the online file storage company Box noted in a tweet in 2014, “Sizing the market for a disruptor based on an incumbent’s market is like sizing a car industry off how many horses there were in 1910.”

The other factor that can lead to underestimating a market is neglecting to account for expanding into additional markets. Amazon began as Amazon Books, the “Earth’s Biggest Bookstore.” But Jeff Bezos always intended for bookselling to serve as a beachhead from which Amazon could expand outward to encompass his massive vision of “the everything store.” Today, Amazon dominates the bookselling industry, but thanks to relentless market expansion, book sales represent less than 7 percent of Amazon’s total sales.

The same effect can be seen in the financial results of Apple. In the first quarter of 2017, Apple generated $7.2 billion from the sale of personal computers, a category the company pioneered and once dominated. That’s a great number to be sure, but, over that same financial quarter, Apple’s total revenue was a whopping $78.4 billion, which meant that Apple’s original market accounted for less than 10 percent of its total sales.

My Greylock colleague Jerry Chen, who helped Diane Greene scale VMware’s virtualization software into a massive business, likes to point out, “Every billion-dollar business started as a ten-million-dollar business.”

But whether you are creating a new market, expanding an existing market, or relying on adjacent markets to get to those “B’s” that investors want (baby), you need to have a plausible path to get from here to there. This leads us to one of my favorite growth factors to discuss with entrepreneurs: distribution.

GROWTH FACTOR #2: DISTRIBUTION

The second growth factor needed for a strong, scalable business is distribution. Many people in Silicon Valley like to focus on building products that are, in the famous words of the late Steve Jobs, “insanely great.” Great products are certainly a positive—we’ll discuss the lack of product quality as a growth limiter later on—but the cold and unromantic fact is that a good product with great distribution will almost always beat a great product with poor distribution.

Dropbox is a company with a great product, but it succeeded because of its great distribution. In an interview for Reid’s Masters of Scale podcast, founder and CEO Drew Houston said that he believes that too many start-ups overlook the importance of distribution:

Most of the orthodoxy in Silicon Valley is about building a good product. I think that’s because most companies in the Valley don’t survive beyond the building-the-product phase. You have to be good at building a product, then you have to be just as good at getting users, then you have to be just as good at building a business model. If you’re missing any of the links in the chain, the whole chain is broken.

The challenge of distribution has become even greater in the “mobile first” era. Unlike the Web, where search engine optimization and e-mail links were broadly applicable and successful distribution channels, mobile app stores offer little opportunity for serendipitous product discovery. When you go to Apple’s or Google’s app store, you’re searching for a specific product. Few people install apps just for the hell of it. As a result, the business model innovators who have succeeded (e.g., Instagram, WhatsApp, Snap) have had to find creative ways to get broad distribution for their product—without spending a lot of money. These distribution techniques fall into two general categories: leveraging existing networks and virality.

A) Leveraging Existing Networks

New companies rarely have the reach or resources to simply pour money into advertising campaigns. Instead, they have to find creative ways to tap into existing networks to distribute their products.

When I was at PayPal, one of the major vehicles for distribution of our payment service was settling purchases on eBay. At the time, eBay was already one of the largest players in e-commerce, and by the beginning of 2000 already had ten million registered users. We tapped into this user base by building software that made it extremely easy for eBay sellers to automatically add a “Pay with PayPal” button to all of their eBay listings. The amazing thing is that customers did so even though eBay had its own rival payments service, Billpoint! But sellers were required to add Billpoint manually to each of their listings; PayPal did it for them.

Many years later, Airbnb was able to perform a similar feat by leveraging the online classified service Craigslist. Based on a suggestion from Y Combinator’s Michael Seibel, Airbnb built a system that allowed and encouraged its hosts to cross-post their listings to the much-larger Craigslist. Hosts were told, “Reposting your listing from Airbnb to Craigslist increases your earnings by $500 a month on average,” and were allowed to do so by clicking a single button. This took serious technology skills—unlike many platforms, Craigslist doesn’t have an application programming interface (API) that allows other software to interact with it—but it was technology innovation for the purposes of distribution innovation, not product innovation. “It was a kind of a novel approach,” Airbnb founder Nathan Blecharczyk said of the integration. “No other site had that slick an integration. It was quite successful for us.”

Leveraging an existing network can have downsides, of course. What the existing network gives (or unknowingly allows to be taken), the existing network can also take away. Zynga, the leading social games company, achieved great success leveraging Facebook for distribution, but had to dramatically reengineer its distribution model after Facebook decided to stop allowing people playing Zynga games to post their progress to their Facebook friends. (Disclosure: I am a member of Zynga’s board of directors.) Zynga founder Mark Pincus was farsighted enough to build a strong enough franchise to survive the change.

In contrast, so-called content farms like Demand Media that leveraged Google’s search platform to generate website traffic and advertising revenues never recovered after Google tuned its algorithms to deprioritize content from what it called “junk” websites.

Despite these dangers, leveraging existing networks can be a critical part of a business model, especially if these networks can provide a “booster rocket” that is later supplemented with virality or network effects.

B) Virality

“Viral” distribution occurs when the users of a product bring more users, and those users bring additional users, and so on, much like an infectious virus spreads from host to host. Virality can either be organic—occurring during the course of normal usage of the product—or incentivized by some kind of reward.

After launching LinkedIn, the team and I devoted significant time and energy to figuring out how to improve organic virality; that is, how to make it easier for existing users to invite friends to use the service. One way we did this was to refine what have become some of the standard tools of virality, such as address book importers. For example, we built software that allowed LinkedIn to connect to our users’ Outlook contacts, which made it very easy for them to invite their most important connections.

But equally important was an unanticipated source of virality. As it turned out, users wanted to use their LinkedIn pages as their primary professional identity on the Internet. Having a page like this to point others to—with all the details of their professional life together in one place—generated value not only for the user, but for the people viewing the page, and it made viewers realize that they should get their own LinkedIn profile. As a result, we added public profiles as a systematic tool to boost both the member value proposition and our viral growth rate.

At PayPal, we combined organic and incentivized virality. The payment product was inherently viral; if someone e-mailed you money using PayPal, you had to set up an account to get paid. But we enhanced this organic virality with monetary incentives. If you referred a friend to PayPal, you got $10, and your friend got $10. This combination of organic and incentivized virality allowed PayPal to grow 7 to 10 percent per day. As the PayPal network grew, we reduced the incentives to $5 and $5, then finally eliminated them altogether.

Incentives don’t have to be monetary; like PayPal, Dropbox used a similar combination of organic virality (as users share files with nonusers) and incentivized virality (Basic account holders get 500 MB of extra storage per user they refer; Pro account holders get 1 GB) to grow. Even though Dropbox invested in partnerships with leading PC makers like Dell, Drew Houston credits virality with driving the company’s rapid growth, helping it double its one hundred thousand users at launch to two hundred thousand users just ten days later, then skyrocket to one million users just seven months after that.

If your distribution strategy focuses on virality, you also have to focus on retention. Bringing new users in through the front door doesn’t help you grow if they immediately turn around and leave. According to Houston, Dropbox discovered this truth the hard way, when activation rates revealed that only 40 percent of the people signing up were actually putting files in their Dropbox and linking them to their computers. In an interview for my Masters of Scale podcast, Drew described a scene reminiscent of the television show Silicon Valley (but with a happier ending):

What we did is we went on Craigslist and offered $40 to anyone who’d come in for half an hour—a poor man’s usability test. We’re like, “All right, sit down. This is an invitation to Dropbox in your e-mail. Go from here to sharing a file with this e-mail address.” Zero of the five people we tested succeeded. Zero of the five even came close. This was just stunning. We’re like, “Oh my God, this is the worst product ever created.” So we made a list of like eighty things in this Excel spreadsheet, then just sanded down all these rough edges in the experience, and watched our activation rate climb.

Virality almost always requires a product that is either free or freemium (i.e., free up to a certain point, after which the user has to pay to upgrade—Dropbox, for example, offers 2 GB of free storage). We can’t recall a single instance of a company that grew to a massive scale by leveraging the virality of a paid product.

One of the most powerful distribution innovations is to combine both strategies. Facebook was able to do this by harnessing the organic virality of a social network (where users invite other users to join them) and leveraging existing networks centered around campuses by rolling out the product on a college-by-college basis. We’ll discuss Facebook’s rollout strategy in greater depth when we consider network effects.

GROWTH FACTOR #3: HIGH GROSS MARGINS

One of the key growth factors that entrepreneurs often overlook is the power of high gross margins. Gross margins, which represent sales minus the cost of goods sold, are probably the best measure of long-term unit economics. The higher the gross margin, the more valuable each dollar of sales is to the company because it means that for each dollar of sales, the company has more cash available to fund growth and expansion. Many high-tech businesses have high gross margins by default, which is why this factor is often overlooked. Software businesses have high gross margins because the cost of duplicating software is essentially zero. Software-as-a-service (SaaS) businesses have a slightly higher cost of goods sold because they need to operate a service, but thanks to cloud providers like Amazon, this cost is becoming smaller all the time.

In contrast, “old economy” businesses often have low gross margins. Growing wheat is a low-margin business, as is selling goods in a store or serving food in a restaurant. One of the most amazing things about Amazon’s success is that it has been able to build a massive business based on retailing, which is generally a low-margin industry. And even Amazon now relies heavily on its high-margin SaaS business, Amazon Web Services (AWS). In 2016, AWS accounted for 150 percent of Amazon’s operating income, which means that the retail business actually lost money.

Most of the valuable companies we’re focusing on in this book have gross margins of over 60, 70, or even 80 percent. In 2016, Google had a gross income of $54.6 billion on sales of $89.7 billion, for a gross margin of 61 percent. Facebook’s gross income was $23.9 billion on sales of $27.6 billion, for a gross margin of 87 percent. In 2015, LinkedIn’s gross margin was 86 percent. As we’ve already discussed, Amazon is the outlier, with a 2016 gross income of $47.7 billion on $136 billion in sales, for a gross margin of 35 percent. Yet even Amazon’s gross margins are greater than those of a “high margin” traditional company like General Electric, which in 2016 had a gross income of $32.2 billion on sales of $119.7 billion, for a gross margin of 27 percent.

High gross margins are a powerful growth factor because, as noted below, not all revenue is created equal. The key insight here is that even though gross margins matter a great deal to the seller, they are irrelevant to the buyer. How often do you consider the gross margin involved when you make a purchase? Would you ever choose Burger King over McDonald’s because Whoppers are lower margin than Big Macs? Typically, you focus solely on the cost to you, and the perceived benefits of the purchase. This means that it’s not necessarily any easier to sell a low-margin product than a high-margin product. If possible then, a company should design a high-gross-margin business model.

Second, high-gross-margin businesses are attractive to investors, who will often pay a premium for the cash-generating power of such a business. As the prominent investor Bill Gurley wrote in his 2011 blog post, “All Revenue Is Not Created Equal,” “Investors love companies where, all things being equal, higher revenues create higher profit margins. Selling more copies of the same piece of software (with zero incremental costs) is a business that scales nicely.” Appealing to investors makes it easier to raise larger amounts of money at higher valuations when the company is privately held (we’ll delve into the details of why this is so important later on), and lowers the cost of capital when the company is publicly traded. This access to capital is a key factor in being able to finance lightning-fast growth.

It’s important to note the difference between potential gross margin and realized gross margin. Many blitzscalers, such as Amazon or the Chinese hardware makers Huawei and Xiaomi, deliberately price their products to maximize market share rather than gross margins. As Jeff Bezos is fond of saying, “Your margin is my opportunity.” Xiaomi explicitly targets a net margin of 1 to 3 percent, a practice it credits Costco for inspiring. All other factors being equal, investors almost always place a much higher value on companies with higher potential gross margins than companies that have already maximized their realized gross margins.

Finally, most of a company’s operational challenges scale based on revenues or unit sales volume, not gross margin. If you have a million customers who generate $100 million per year in sales, the cost to serve those customers doesn’t change whether your gross margin is 10 percent or 80 percent; you still need to hire enough people to respond to their support requests. But it’s a lot easier to afford good customer support when you have $80 million in gross margin to spend rather than $10 million.

Conversely, it’s a lot easier to sell and service 125,000 customers who generate $12.5 million per year in sales and $10 million in gross margin than it is to have to sell and service a million customers who generate $100 million in sales to achieve that same $10 million in gross margin. That’s eight times as many customers and eight times the revenues, which means eight times as many salespeople, customer service representatives, accountants, and so on.

Designing a high-gross-margin business model makes your chances of success greater and the rewards of success even greater. As we’ll see in a later section, high gross margins have helped even nontech businesses, such as the Spanish clothing retailer Zara, grow into global giants.

GROWTH FACTOR #4: NETWORK EFFECTS

Market size, distribution, and gross margins are important factors in growing a company, but the final growth factor plays the key role in sustaining that growth long enough to build a massively valuable and lasting franchise. While the past twenty years have driven improvements in the first three growth factors, the rise in Internet usage around the world has pushed network effects to levels never before seen in our economy.

The increasing importance of network effects is one of the main reasons that technology has become a more dominant part of the economy.

At the end of 1996, the five most valuable companies in the world were General Electric, Royal Dutch Shell, the Coca-Cola Company, NTT (Nippon Telegraph and Telephone), and ExxonMobil—traditional industrial and consumer companies that relied on massive economies of scale and decades of branding to drive their value. Just twenty-one years later, in the fourth quarter of 2017, the list looked very different: Apple, Google, Microsoft, Amazon, and Facebook. That’s a remarkable shift. Indeed, while Apple and Microsoft were already prominent companies at the end of 1996, Amazon was still a privately held start-up, Larry Page and Sergey Brin were still a pair of graduate students at Stanford who were two years away from founding Google, and Mark Zuckerberg was still looking forward to his bar mitzvah.

So what happened? The Networked Age happened, that’s what.

Technology now connects all of us in ways that were unthinkable to our ancestors. Over two billion people now carry smartphones (many of them made by Apple, or using Google’s Android operating system) that keep them constantly connected to the global network of everything. At any time, those people can find almost any information in the world (Google), buy almost any product in the world (Amazon/Alibaba), or communicate with almost any other human in the world (Facebook/WhatsApp/Instagram/WeChat).

In this highly connected world, more companies than ever are able to tap into network effects to generate outsize growth and profits.

We’ll use the simple layman’s definition of network effects in this book:

A product or service is subject to positive network effects when increased usage by any user increases the value of the product or service for other users.

Economists refer to these effects as “demand-side economies of scale” or, more generally, “positive externalities.”

The magic of network effects is that they generate a positive feedback loop that results in superlinear growth and value creation. This superlinear effect makes it very difficult for any node in the network to switch from an incumbent to an alternative (“customer lock-in”), since it is almost impossible for any new entrant to match the value of plugging into the existing network. (Nodes in these networks are typically customers or users, as in the canonical example of the fax machine, or the more recent example of Facebook, but can also be data elements or other fundamental assets valuable in a business.)

The resulting phenomenon of “increasing returns to scale” often results in an ultimate equilibrium in which a single product or company dominates the market and collects the majority of its industry’s profits. So it’s no surprise that smart entrepreneurs strive to create (and smart investors want to invest in) these network effects start-ups.

Several generations of start-ups have tapped these dynamics to build dominant positions, from eBay to Facebook to Airbnb. To accomplish these goals, it’s critical to develop a rigorous understanding of how network effects work. My Greylock colleague Simon Rothman is one of the world’s premier experts on network effects from building eBay’s $14 billion automotive marketplace. Simon warns, “A lot of people try to bolt on network effects by doing things like adding a profile. ‘Marketplaces have profiles,’ they reason, ‘so if I add profiles, I’ll be adding network effects.’” Yet the reality of building network effects is a bit more complicated. Rather than simply imitate specific features, the best blitzscalers study the different types of network effects and design them into their business models.

Five Categories of Network Effects

On his industrial organization of information technology website, the NYU professor Arun Sundararajan classifies network effects into five broad categories:

1) Direct Network Effects: Increases in usage lead to direct increases in value. (Examples: Facebook, messaging apps like WeChat and WhatsApp)

2) Indirect Network Effects: Increases in usage encourage consumption of complementary goods, which increases the value of the original product. (Example: Adoption of an operating system such as Microsoft Windows, iOS, or Android encourages third-party software developers to build applications, increasing the value of the platform.)

3) Two-Sided Network Effects: Increases in usage by one set of users increases the value to a different set of complementary users, and vice versa. (Example: Marketplaces such as eBay, Uber, and Airbnb)

4) Local Network Effects: Increases in usage by a small subset of users increases the value for a connected user. (Example: Back in the days of metered calls, certain wireless carriers allowed subscribers to specify a limited number of “favorites” whose calls didn’t count against the monthly allotment of call minutes.)

5) Compatibility and Standards: The use of one technology product encourages the use of compatible products. (Example: within the Microsoft Office suite, Word’s dominance meant that its document file format became the standard; this has allowed it to destroy competitors like WordPerfect and fend off open-source solutions like OpenDocument.)

Any of these different network effects can have a major impact; Microsoft’s ability to tap into multiple network effects with Windows and Office contributed greatly to its unprecedentedly durable franchise. Even today, Windows and Office remain dominant in the PC market; it’s simply that other platforms like mobile have achieved similar or greater importance.

Network Effects Both Produce and Require Aggressive Growth

A key element of leveraging network effects is the aggressive pursuit of network growth and adoption. Because the impact of network effects increases in a superlinear fashion, at lower levels of scale, network effects actually exert downward pressure on user adoption. Once all your friends are on Facebook, you have to be on Facebook too. But conversely, why would you join Facebook if none of your friends had joined yet? The same is true for the first user of marketplaces like eBay and Airbnb.

With network effects businesses, you can’t start small and hope to grow slowly; until your product is widely adopted in a particular market, it offers little value to potential users. Economists would say that the business has to get past the “tipping point” where the demand curve intersects with the supply curve. Companies like Uber subsidize their customers in an attempt to manipulate the demand curve to reach that tipping point faster; the bet is that losing money in the short term may allow you to make money in the long term, once you’re past the tipping point.

One challenge that this approach produces is the (eventual) need to eliminate the subsidies in order to make the unit economics work. When I was at PayPal, one of the things we did to encourage adoption was to proclaim that the service would always be free. This meant eating the transaction costs of accepting credit card payments. I wish I could say we had a grand plan. We had hoped that we could make up for the credit card transaction fee subsidy by making money off the float—the funds being kept in PayPal. Unfortunately, this came nowhere close to offsetting the fee subsidies, and the company was hemorrhaging money. So we switched PayPal from “always free” to “ACH always free” and started charging fees to accept credit card payments. Fortunately, we already had a loyal following, and our customers accepted the change.

When the business can’t change the economics of the product (free services like Facebook can’t lower their prices), it can instead sway the expectations of potential users. The value users place on the service when deciding whether or not to adopt it depends on both the current level of adoption and their expectations for future adoption. If they think others are going to jump on board, the perceived value of the service increases, and they become more likely to adopt it.

This technique is reflected in one of the most influential business books of all time, Geoffrey Moore’s Crossing the Chasm. Moore argues that technology companies often run into problems when they try to transition from a market of early adopters to the mainstream—the proverbial “chasm.” He recommends that companies focus on niche beachhead markets, from which the company can expand outward using a “bowling pin” strategy in which these markets help to open up adjacent markets. This strategy is even more important for network effects businesses.

A company can also reshape the demand curve by designing the product to be valuable to the individual user regardless of network adoption. At LinkedIn, for example, we discovered that public LinkedIn profiles had some value independent of the user’s network, since they served as an online professional identity. This gave people a reason to join LinkedIn even if their friends and colleagues hadn’t done so yet.

Connectivity Enables Network Effects Businesses

In addition to supporting network effects, the high connectivity of the world we live in today also makes it easier to reach the tipping point where network effects kick in, and to sustain those network effects and the market dominance they produce.

First, the Internet has driven the cost of discovery for products and services lower than ever. Unlike in the past, when companies needed to offer goods in retail stores or broadcast advertising in order to be visible to customers, today buyers can find whatever they’re looking for on Amazon or other online marketplaces like Alibaba, in app stores, or, when all else fails, by Googling. Because products and services that are already popular will almost always come up first in search results, companies with a competitive advantage can quickly grow to the point where the increasing returns of network effects produce a winner-take-most or winner-take-all market. This also explains why the growth factor of distribution is as or more important to company success as the product itself—without distribution, it is difficult to reach the tipping point.

After network effects take hold, the efficiencies enabled by the Networked Age make it easier to sustain the pace of rapid growth. In the past, rapid customer growth inevitably led to rapid organizational growth and to dramatic increases in the overhead required to coordinate a large number of employees and teams. Today’s networks allow companies to sidestep these traditional growth limiters, such as when Apple used Foxconn to get around the potential limitation of its manufacturing infrastructure (more on this in the next section). The more you can remove those limiters, the more dominant a network effects–driven business can grow. This is why companies like Google that have surpassed the $100 billion mark in annual revenues are still growing at over 20 percent per year.

Finally, the remarkable profitability of these companies gives them the financial resources to expand into new fields and invest in the future. The S-curve of innovation argues that the rate of adoption of every innovation eventually slows as the market saturates. However, companies like Apple have mastered the strategy of investing in new products that let them hop onto additional S-curves. Apple hopped from music players to smartphones to tablets, and it is no doubt spending some of its vast profits chasing the next S-curve. The premium that the public markets grant these companies also helps them use mergers and acquisitions (M&A) to jump these curves, much as Facebook did with Instagram, WhatsApp, and Oculus, and Google did with DeepMind.

Of course, network effects don’t apply to every company or market, even if they are superficially similar—as many companies and their investors discovered to their chagrin during the dot-com bust, the Great Recession, and the funding slowdown of 2016. This is why the best entrepreneurs try to design innovative business models that leverage network effects. One of the reasons that Google is Google and Yahoo! is now part of AOL (which in turn is owned by Verizon) is that Google focused on AdWords (a marketplace with strong network effects) while Yahoo! tried to become a media company (a traditional model based on economies of scale).

Much of Silicon Valley’s historical success in building giant companies can be traced to its cultural emphasis on business model innovation, which results in the creation of network effects–driven businesses. The irony is that many people in Silicon Valley couldn’t define a network effect or what caused it if asked. Yet simply because so many entrepreneurs are trying so many different business models, they can end up stumbling into powerful network effects. Craig Newmark simply started e-mailing his friends about local events in 1995; almost twenty-two years later, network effects have kept Craigslist a dominant player in online classifieds despite operating with a skeleton crew and making seemingly no changes to the website design during that entire period!

This is where an emphasis on speed also plays an important role. Because Silicon Valley’s entrepreneurs focus on designing business models that can get big fast, they are more likely to incorporate network effects. And because the fierce local competition forces start-ups to grow so aggressively (i.e., blitzscale), Silicon Valley start-ups are more likely to reach the tipping point of network effects before start-ups from less aggressive geographies.

One of the motivations for this book is to help entrepreneurs from around the world emulate these successes by teaching them how to systematically design their businesses for blitzscaling. When you design your business model to leverage network effects, you can succeed anywhere.

DESIGNING TO MAXIMIZE GROWTH: THE TWO GROWTH LIMITERS

Building key growth factors into your innovative business model is only half the battle. It is fiendishly difficult to grow an amazing business, in part because it is fiendishly easy to run smack into obstacles that limit your growth. A key component of business model innovation is designing around these growth limiters.

GROWTH LIMITER #1: LACK OF PRODUCT/MARKET FIT

Product/market fit enables rapid growth, while the lack of it makes growth expensive and difficult. The concept of product/market fit originates in Marc Andreessen’s seminal blog post “The Only Thing That Matters.” In his essay, Andreessen argues that the most important factor in successful start-ups is the combination of market and product.

His definition couldn’t be simpler: “Product/market fit means being in a good market with a product that can satisfy that market.”

Without product/market fit, it’s impossible to grow a start-up into a successful business. As Andreessen notes,

You see a surprising number of really well-run start-ups that have all aspects of operations completely buttoned down, HR policies in place, great sales model, thoroughly thought-through marketing plan, great interview processes, outstanding catered food, 30″ monitors for all the programmers, top tier VCs on the board—heading straight off a cliff due to not ever finding product/market fit.

Unfortunately, it’s far easier to define product/market fit than it is to establish it!

When you start a new company, the key product/market fit question you need to answer is whether you have discovered a nonobvious market opportunity where you have a unique advantage or approach, and one that competing players won’t see until you’ve had a chance to build a healthy lead. It’s usually difficult to find such an opportunity in a “hot” space; if an opportunity is obvious to everyone, the chance that you’ll be the one who succeeds is exceedingly low.