This works pretty well for some companies. Facebook, for example, hit 100 million users in mid 2008, with “more than 600″ employees. Now they have 500 million users, and 1400+ employees. 400% growth in users; 130% growth in employees. That’s exactly the kind of math VCs like to see, and it’s why they were willing to fund Facebook generously in the early stages. Facebook will run into scalability barriers after a while. At some point, the limiting factor is not engineers (a scalable resource) but customer service reps and servers.

For many of the current crop of hot companies, the end of scalability is coming much faster.

Long-Tail = Labor-Intensive

Google wants to organize the world’s information, period. Demand Media wants to create every single piece of content for which there’s demand. Enumerated.

Google’s technique involves aggressive automation: spidering, creating indices, weeding out link farms and spam, and automatically analyzing content. When humans interact with that process, it’s generally at the margin: tweaking an algorithm here, fiddling with backend infrastructure there.

Demand Media requires consistent human interaction at every level. They do have an algorithm, but it spits out data that need digesting: title editors turn search query snippets into headlines, then content writers create them, then editors review them. If Demand Media wants to grow (and of course they do!), they need to crank up their inputs.

It’s the same for any other business that wants to hand-craft content for a niche audience. It takes continuous input to get continuous growth. And even increasing the growth rate is labor-intensive; Demand Media screens every applicant, and you can find plenty of stories of journalism majors getting rejected.

It might be a fantastic business, but it doesn’t scale the way the last generation did. No wonder they’ve raised $355 million. The real question is: why are they raising equity? They have immediate, predictable cash flow; they might as well replace their operating leverage with the old-fashioned kind.

Local Marketing = Telemarketing

If you’re going to talk about massive money raising, you’ll have to talk about Groupon. $173 million, including a big check from Digital Sky Technologies. They’re also in an established space, with lots of competition, including companies that have recently gone public. And why did Reach Local go public? So they could hire more sales reps!

A surprising fraction of my friends work for companies that do group buying or location-based marketing. And there’s a reason for that: once you have your platform and your userbase, the big obstacle is signing up new small business customers. And so far, nobody has found a better way to do that than hiring lots of salespeople and getting them on the phone.

Even Foursquare is growing into that situation. They’ve done some big, showy deals, but I bet the main value they’ll see from them is that they can call up the local coffee shop and say “Wouldn’t you like some of those customers who order the $5 Venti at Starbucks?”

The VC Overhang: Cause or Effect?

It can’t be a coincidence that VCs have raised too much money since the late 90’s, and there are now startup-looking businesses that can (and must) deploy huge amounts of capital.

It’s hard to say which is cause and which is effect, though. Groupon’s founders stumbled into their business—no cynical ploys there. I wouldn’t put it past Demand Media’s CEO, Richard Rosenblatt, to have planned this out (he knows how to sell high).

But my best guess is that it’s more complicated, because you can reframe the question: what these companies have in common is that the limiting factor for their growth isn’t technology, or brand recognition, or network effects. It’s capital. And for once, at least in part of the economy, capital is overabundant.

Google is the Big Default. If you want to find something, but you’re not precisely sure what, Google is where you start. For about eight years, that’s where I’ve started, too. But recently, two sites have started to replace Google. And what’s especially dangerous about them is that they’re both encroaching on Google, starting at opposite ends of the spectrum of services that Google Search provides.

DuckDuckGo: The Best New Search Engine Since Google

The first Google Threat I found is the DuckDuckGo search engine. It’s a one-person company, so it’s entitled to some quirks. But it’s also entitled to strong opinions on privacy, and that low overhead means they can be hostile to ads that are hostile to users.

DuckDuckGo’s founder has some complex ideas about what Google can’t copy, but the summary is simple: Google is at, or close to, a local maximum. Any change they make will, on average, make the typical user’s experience worse. If there’s a better way to search than Google, there are many worse ways to search between that and Google.

Which makes DuckDuckGo a great business: if they Get Search Wrong and only have a small core of loyal users, they can at least sell ads against those pageviews. But if they get it right, Google can’t afford not to buy them—why not marry Google’s Adwords team (and all their search data) to whatever search interface happens to work best?

What I’ve found is that for a specific set of queries, DuckDuckGo wins. Specifically, if you are sure that what you’re looking for exists, DDG will feature it more prominently. They hide ads, let you downgrade commercial sites, and highlight official sources. Basically, they’re a better user interface for a better Wikipedia.

Quora: The Longest Possible Long Tail

On the other end of the spectrum, there are some things you would not expect to exist online. For those, your best bet is Quora, a smart Q&A site. They were invite-only until literally the day after I sent a bunch of people invites, so their userbase consists of people who are a few degrees of separation away from the founders. And since Quora’s founders came straight out of Facebook, that’s a smart group.

Quora is full of people who can answer the questions Google can’t. Questions like:

• What are some behaviors that are accepted now but might be considered immoral in the future?

• How many times a year does an air conditioner fall out of a window in New York City and kill someone?

• For what purposes are fictitious social networking profiles created?

I wouldn’t bother asking Google. Quora has answers. Quora is targeting the longest possible long tail: pieces of content that at least one person can create, and that at least one person cares to read.

Quora doesn’t, however, have a business model (they have enough funding not to care). DuckDuckGo may or may not be profitable, but probably isn’t a huge business.

But they’ve both replaced Google as a default. And they did it for less than it would cost Google to take that default status back.

At 21X earnings, Google is not a short. There’s a lot they can do to diversify, and a lot they can do to get closer to DuckDuckGo and Quora. But all that will cost them something, so buying Google now is a tricky bet—that they’ll be able to change direction in time, before they end up being another Yahoo.

Take a look!

There’s a good reason most people choose to “Reply All”: all of the recipients of an email have to assume that, until they hear something about it, whatever the email says must be done still must be done. If you’ve ever replied directly to the sender of an email that was sent to ten people, you’ve gotten one of two responses: either ten minutes later you’re “Reply All”‘d on another email that makes yours redundant. At one minute per email times ten recipients, it’s easy to see how a simple task can take an hour or more total—and that’s ignoring the cost of disruptions.

I have a simple solution: “Reply All” should not allow you to compose an email reply; it should send a default answer like “It’s being taken care of.” To recipients who need to know more, you can elaborate; to everyone else, well, it’s being taken care of.

(In the meantime, you can start replying-all with that line. Hopefully it will catch on.)

• In an equity bubble, investors have limitless optimism about the future. They expect many of the companies they invest in to fail, but believe that the 95th- or 99th-percentile performers will more than make up for this.

• In a credit bubble, investors have limitless faith in the status quo. They expect volatility to decrease, and they believe they can estimate returns with increasing accuracy. If they want higher returns, they know they can use leverage—but for the most part, investors celebrate the middle of the bell curve, and expect the tails to cancel each other out.

The only thing these bubbles have in common is that they involve collectively bad decisions with money. The kinds of decisions are vastly different, and the consequences are, too.

Equity Bubbles Considered Not-So-Harmful

In an equity bubble, resources get distributed towards whatever investment is the most levered to optimistic outcomes. These don’t have to be the same outcomes—AOL’s walled-garden got a high valuation at the same time that Yahoo’s anything-goes approach did, for example.

Because of this, they attract capital (and talented people) to anything sufficiently unusual that fits into the bubble narrative. This entails lots of investments in bad ideas (Pets.com) and lots of investments in necessary ideas (online brokerages, which automated the most automatable part of investing).

It’s a huge subsidy for creative destruction, with an emphasis on the creativity. Unlike the usual economic process of local optimization (making a factory marginally more efficient, reducing inventories a little bit at a time, finding a new customers), it represents a massive change in the process (creating a completely new sales channel, revamping the entire inventory management process, creating a financing model that’s based on venture funding plus a negative cash cycle).

There’s a lot of malinvestment during these bubbles, but they also lead to lasting companies. They also create new infrastructure (bad telecom investments in the 90’s made Myspace and Youtube possible in the 00’s). And they help illustrate the ineffectiveness of older companies, though it’s often not until the bust that these companies go under.

Of all of the ways that the market can overshoot itself, equity bubbles appear to be the most beneficial. In the short term, they subsidize creativity; in the long term, they subsidize creativity tempered by sanity. And if “creativity tempered by sanity” doesn’t describe the best parts of the world economy since the industrial revolution, I don’t know what does.

Credit Bubbles: Doubling Down on the Status Quo

Credit bubbles are toxic. They rely on ignoring possibilities, rather than embracing them. They allocate human capital away from analyzing uncertainty, and towards creating artificial certainty. Credit bubbles are more self-perpetuating than other kinds of bubbles, and they leave behind an inflexible economy.

A credit bubble is a bet on the continuation of the status quo. Since lenders have limited upside and lots of downside, they don’t have any reason to care about best-case scenarios; instead, they look at average scenarios. That requires historical data, which can best be obtained from older and more static industries.

The most pernicious effect of credit bubbles is that they tend to be self-perpetuating. In the 00’s, the dominant investment thesis might be summed up as follows:

• Our economy is stable, financial markets are liquid, and information is freely available, so volatility should gradually decrease.
• This liquidity and information also means we won’t have huge economic dislocations; future change will be gradual.
• We can use historical data to model prices, and our models keep improving.
• Thus, the way to make money is to buy what you can most effectively model, treat it as an asset class rather than a claim on specific cash flows, and lever as much as your volatility permits—after all, you have historical data on exactly how markets will behave under any circumstances.

This results in smooth returns with low (and declining) volatility for people who buy into the thesis. And if they’re competing with other investors for funds, that means more money gets allocated to investors who buy into the bubble thesis—pushing prices further in the same direction.

All else being equal, skeptics get priced out. During the mortgage bubble, the skeptics who profited the most were the ones for whom all else was not equal—value investors who got into real estate as a sideline (like Michael Burry and John Paulson), or unusually talented traders who subsidized their negative bets with their market-making profits (like Greg Lippmann).

Meanwhile, the bubble believers see their ideas constantly confirmed. Everyone’s returns are in line with predictions—unlike equity bubbles, there aren’t any sudden gains. In a credit bubble, it’s possible to do what Bear Stearns’ internal hedge funds did, and show consistent returns of about 1% per month with no down months.

All this means more resources allocated towards precision, rather than accuracy: if prices converge on what the model says they should be, a more refined model will create more incremental profits than a different understanding of what’s being modeled. Over time, this simplification leaves room for the underlying assets to change: the capital for mortgages from 2006 was allocated based on the returns from years beforehand, which made that capital less sensitive to declining credit standards.

In the terminal phases of a credit bubble, investors are precisely wrong—whatever they’re most bullish on and most certain about is bound to be the asset declining in quality the fastest, and the one whose future pricing is thus the least predictable.

What to Do About a (Bad) Bubble

Investors in the 90’s were overconfident about the power of technology to change their lives in the near term. They were also overconfident about the power of financial models to predict sovereign debt prices and equity volatility—in the latter case, the collapse of LTCM scared them straight, while the Fed’s subsequent liquidity injections kept that collapse from flattening the broader economy.

This illustrates the fundamental problem: given enough liqudity, good and bad bubbles can last indefinitely. And identifying them can be tricky: a large component of the “tech” bubble was the “IT bubble”&madsh;a huge increase in the demand for people with otherwise obsolete skills, who could update systems ahead of Y2K.

You can ask yourself a simple question: “Is what these people are throwing money at, fundamentally, boring?” If it is, buy puts: you know they’ll be cheap.

If you’re a money manager, you’re out of luck: the more effectively you short the bubble, the worse your returns will look. And since credit bubbles appear quite conservative (they are, after all, based entirely on historical precedent), you’ll look bad and imprudent. Worst of all, if you bet on the bubble as a manager and short it (or even deride it) as a private investor, you’ll probably end up in court.

So your best bet is to quit your job and start a blog or something. (Then, buy puts.)

In the case of the US, India, or China, that tax rate is determined by all sorts of lobbying, voting, personalities, and compromises. In Facebook’s case, they can collect taxes by forcing companies to use Facebook Credits. It’s just a question of maximizing profits. And that means taxing companies that profit from Facebook at the peak of a slightly modified Laffer Curve.

The Laffer Curve normally describes government revenues compared to marginal tax rates. It’s a curve because, given a sufficiently high tax rate, the incentive to work, report income, or live in a particular country declines. This leads to the argument that lower taxes are net beneficial: if we’re past the peak, they’ll raise government revenue, but even if we’re not, they can produce economic growth.

Facebook doesn’t have to care about “economic growth.” Their goal is not to grow the companies that exist on their platform, just to profit as much as possible from them. It might seem that this implies taxing at the Laffer maximum, but that’s not quite true: Facebook can afford to maximize the net present value of their future income, and to set their tax rate accordingly.

In practice, that will mean low (or zero) taxes as long as a company using Facebook’s platform is still growing. But once their growth slows, it shifts the Laffer curve to the point that taxing them more produces extra income even if it slows down their growth (and discourages other companies from using Facebook’s platform).

Since Facebook can easily prevent tax evasion, and since corporations have a fiduciary duty not to be lazy, the only mechanism by which the Laffer Curve can operate is emigration: at some point, Zynga could theoretically decide that Facebook isn’t worth it; they’ll take their bigger slice of a smaller pie elsewhere. I’m not sure what it costs Zynga to move one person from Facebook to a non-Facebook platform for the same game, but it’s probably a painfully high number when you multiply it by, say, the 82 million active users of Farmville. This might also explain why Facebook is okay with stickiness—it’s bad for business, but good for keeping existing business from going elsewhere.

Taxation or Nationalization?

Fred Wilson argues that Twitter can be free to ‘fill in the holes’ in their experience, but not to go after new verticals. In the Laffer context, the question is not which features a platform will duplicate and which it won’t, but which features it will tax and which it will expropriate instead.

Facebook, and more recently Twitter, have also done a form of “nationalization”: they turn someone else’s product into a feature of their own product. This seems to work best when the product works as a feature, and doesn’t have a clear monetary value: the classic example being Internet Explorer and Netscape Navigator; soon after IE came out, selling a computer and charging for the browser would have made as much sense as selling a car and charging for the steering wheel.

The “features they should have had” versus “value-added extras” dichotomy is false. The real question is which is worth more: taxing a platform user at the Laffer maximum, or subsuming them in order to shift the Laffer curve in a more profitable direction. At first, this sounds like an academic distinction—but it implies that the more people make money with Facebook apps, the more desirable it is to nationalize rather than tax other apps: Zynga’s $300 million in revenue is worth taxing; but if Zynga produced $1 billion in revenue, it could easily be worth giving up the chance to tax other companies, in order to make it easier to tax that billion dollars at a higher rate.

Twitter isn’t monetizing in the same way, but they do face the same equation. In their case, they’ve nationalized more, but it’s easy to see where they could start taxing instead. If you’ve looked at many financial sites that monetize through ad networks, you’ve seen who can bid the most for finance-related ad space: penny-stock promoters. That’s why Stocktwits has been so successful: it culls the spam. If Twitter sells ad space to the highest bidder, Stocktwits will get spam, and it’ll be official spam, too. A nasty outcome, but possible (though Stocktwits has mitigated this risk by building their own non-Twitter income sources, and their own independent platform; more than anyone else, they’ve figured out how to launch from someone’s platform, without being anchored to it.)

Why To Stay Bullish

Thanks to the power of Metcalfe’s law, squared, platforms have an incentive to encourage new applications, and to make them rewarding. Like a country that encourages people to start small businesses, these platforms will get more activity without having to try very hard.

So for small startups, this is irrelevant: they don’t have enough of an income for it to be worth Facebook’s time to determine the optimal tax rate, and they’ll produce more taxable income if they grow fast. Once a company hits the saturation point, though, there’s little reason for Facebook to let them earn excess profits. Sure, it will discourage VCs from funding some companies on Facebook’s platform, since they won’t be able to participate in quite so giant an IPO. On the other hand, the independent programmers who put together a simple app over a couple weekends won’t be too discouraged; Facebook is likely to tax only when it’s already fantastically profitable.

And even companies like Zynga won’t be left behind. There’s still no cheaper source for new users. Converting a small fraction of them from one platform to another is still easier than trying to get them to start out on the Zynga platform itself. Meanwhile, it makes a $25 billion market cap sound a bit more believable.

So I tend to pay attention to them.

That Actrade story spoiled me, though. There was a lot of conjecture about the company’s fast growth and low cash flow, which I’d heard before. What was new was that company executives had bought their auditor a fancy Rolex; that’s what drove the stock down. Since then, I’ve paid much closer attention to the incentives people have to tell a story that doesn’t quite correspond with reality. And that’s why the recent Barrons article suggesting that the Washington Post Co. is 50% undervalued made me do a double-take.

The meat of the analysis is this: Yes, the newspaper itself is a bad business and getting worse. But the company’s other assets more than make up for it. In fact, their education division, Kaplan, is worth as much as the whole company!

That’s good news for Washington Post shareholders, but it’s great news for Kaplan executives:

The Post uses phantom Kaplan stock to compensate the division’s top executives. Based on the phantom stock price, Kaplan was valued at $2.8 billion at year end, below our $5 billion estimate. The Post’s value of Kaplan likely is understated, partly because the company has no incentive to assess Kaplan at a market price; that would force it to pay more to top Kaplan executives, who get the cash value of the phantom stock.

I can imagine a very simple explanation for this article: the senior people at Kaplan feel underpaid. They get fake stock at a low multiple, instead of real stock at a high multiple. Their division is keeping the company alive, but its growth is masked by the growing losses in Newsweek and the newspaper. They’re in the unlucky position of having stock in a growing company in a hot sector that could collapse at any moment—and not being able to sell because there isn’t a real market for their shares.

An article like this helps their case enormously. It gives them a reason to justify a spinoff, at best, and to expect a higher valuation in their internal stock, at worst. I could only find one executive, CFO Hal Jones, with Kaplan phantom stock. But even with the Post’s fairly low executive compensation, there are executives with million-dollar restricted stock grants. If just one Kaplan executive got such a bonus in Kaplan stock, and this article caused that stock to be valued correctly, it’s a multi million-dollar windfall for the lucky Kaplan executives. All this from Barron’s recommending a stock that doesn’t exist!

Certainly, money has been made from advertising—Rupert Murdoch and Mark Zuckerberg both made their billions from running ads, and well-marketed products like Nike, Windows, and Walmart have produced their share of rich people.

But it’s been a while since anyone started, joined, or bought an ad agency expecting to make a phenomenal amount of money. That wasn’t always the case, though. Albert Lasker was able to throw around many millions of dollars undoing the damage some of his ads did; his employee Claude Hopkins ended up making a salary close to $5 million (inflation-adjusted) for writing copy; David Ogilvy went into advertising because he knew it would make him rich; and the CEO of Ted Bates got a $100 million payday when the firm was bought out in 1986, at a time when that was still serious money.

There’s a good reason these people got Wall Street-sized compensation:for decades, ad agencies charged their clients in a way very similar to how hedge funds do now—but, for reasons I’ll get into, the agencies themselves were even more profitable.

“A royalty on the growth of others…”

Warren Buffett describes the ideal business as one that, among other things, earns its profits as “a royalty on the growth of others,” requiring little extra investment. He also uses the “tollbooth” metaphor: once you’re there, you keep collecting revenue without spending much. The math works amazingly well for an ad agency following the traditional model. Let’s assume that in Year One of our study, the agency handles ten million dollars in ad business. That gives it revenues of $1.5 million. Assume that, at this level, the company’s net profit margin is 5%.

What happens five years later? Their revenue probably grows as fast as that of their clients—say, 7% per year. But their expenses might only rise at the rate of inflation. Call that 3%. After five years, revenues are $2.1 million. Their expenses are $1.65 million. That leaves about $450K in profits, for an annual growth rate of 43%! What a tollbooth!

That’s good for a small business. It’s great for a business that didn’t have to make any major decisions, go after any new clients, or do anything it wasn’t doing five years earlier. No wonder Buffett liked these companies.

It gets better, though. Forget looking at a small agency: what about a big, successful one? Let’s assume they’re very good at what they do: they attract faster-growing clients (+1% growth), they do a good job growing their clients’ sales (+1% growth), and they can convince their clients to spend more money (+1% growth). Not only that, but their success attracts new clients—let’s call that 5% more growth. Now, those new clients will require someone to actually do the work, but those people will be working for a big, secure, growing company; it won’t be hard to attract that right people, at a reasonable price. So expenses can grow 4% faster than in the small company example. Since we’ve already established that past growth leads to high profits, let’s start this company with a $100 million in billings, $15 million in revenue, and a 20% profit margin.

What happens after five years? Their revenues double to $30 million. Expenses rise to $16.8 million. But that leaves $13 million for profits—growth of 32% per year. It gets better: with such high profit margins, this kind of company can better survive a recession. A 10% drop in revenue will hurt their profits, but it will wipe out smaller agencies. So the big agency can also grow by scooping up competitors. Buffett was serious about buying this kind of stock (in the 70’s, tollbooth-style ad agencies started showing up in his portfolio. Along with stock in an actual toll road company, Ogilvy & Mather was a big Buffett holding in the 70’s and 80’s.

What Happened?

Clients got sick of it and started asking for hourly rates. It’s a bit more complicated than that (the big money played a role; clients eventually realized that they were subsidizing three martini lunches; and once the cartel-lite pricing behavior of the big agencies weakened, there was no good reason to be part of the cartel).

And that completely changed the economics of the business. It’s not a royalty on the growth of others: it’s hour-arbitrage: buy forty-hour weeks from writers, designers, etc., and sell those hours to clients. If you can sell all forty (or fifty, or sixty), you will do very well, indeed. If you can only sell thirty, you’ll break even. And if you can only sell twenty-five, you’ll lose money.

But this also makes it insanely easy to scale up or scale down. Got more clients? Buy more hours. And you can subcontract, too: sell hours to a big client, buy some of your hours from a smaller, more specialized company.

Instead of a series of high-margin, high growth, low-risk streams of cash, the business has basically turned into a way to aggregate the work of free agents.

So Are Hedge Funds the New Business Business in the World?

If you want a royalty on the growth of others, running a hedge fund seems to be the way to go. Under the normal compensation structure, you can earn 2% of assets and 20% of profits. On a very mediocre 10% return, that means 4% of assets go to the managers each year. And if that 4% of assets can buy good analysts, savvy traders, and the like, one could expect even higher returns on even more capital.

But it’s not that easy, precisely because it is so easy. In finance, people with quantifiable value tend to get paid extremely well. So if your analyst has a knack for picking good energy stocks, he’ll get a great job offer from the biggest energy investor who hears about him; if your trader has an awesome talent for dealing with distressed debt, he’ll get hired by anyone with a big portfolio of the stuff. The only way to reduce turnover is to pay such vast amounts that you don’t risk losing our people.

Advertising doesn’t quite suffer from the same problem. It takes lots of creative people to put together a single campaign, and it’s very hard to say that the copywriter contributed X% of the profits, while the art director was responsible for Y. Direct response is different, of course, but it scales even worse for companies, since anyone getting paid the salary they’re worth is someone who could be making far more money as a freelancer.

While the top hedge fund guys are making a lot of money, they aren’t making money from the business advantages of the hedge fund structure; they’re making money because the measurable results allow them to take a significant fraction of the money they earn for their firms. This is why the richest hedge fund owners have privately-held companies, and the publicly traded hedge funds have been such a disaster. They’re good to work for, but only good to own in the sense that you can work for them.

What’s the Best Business In the World Now?

If advertising agencies are no longer the best business in the world, and hedge funds never will be, what is the best business in the world?

It’s Facebook. Moore’s Law means that their costs approach zero. Metcalfe’s Law means that their revenues approach infinity. Everything else is building and operating the Buffett-style “tollbooths” to collect the money.

It could have been Google, but Google has trouble earning a marginal profit on the data they collect outside of search. Google’s search/Adwords business is great, but not if its returns are being invested in the rest of Google, which is basically the world’s biggest VC fund.

I believe that this is entirely wrong. A company becomes too big to fail when it’s a leveraged bet on a universally agreed-upon belief that happens to be false.

In the mid-2000’s could look at the data on housing and find reasons to be optimistic: house prices always went up year-over-year, housing was a tax-advantaged investment, there was an explicit government policy in favor of raising home ownership, and an increasingly liquid market for mortgage-backed financial products meant that it would always be easy to borrow.

These reasons, of course, were also the reasons that the housing market collapsed. It was easy to make inductive judgments based on the immediate past, without reaching to make the deductive judgment that circumstances had changed, largely due to an overreliance on their staying the same. (You can never have a true bubble until the bubble itself is part of the story: you had to buy Internet stocks, because they were going up so fast; a house was a safe investment, because housing prices had never seriously dropped.)

Back to Bear and AIG: both companies were, among other things, highly leveraged bets on that same real estate status quo. Letting them unwind would mean further damaging the housing investment thesis, which itself would lead to further failures, more doubts about the future of housing, etc.

It’s a major distinction: the current doctrine is that a company is too big to fail if it will make prices lower than they should be; in practice, a company is too big to fail if its failure means that prices will get closer to where they should be—and we’ll get closer to rethinking the way we’ve been pricing things in general.

This is a little more clear when looking at an asset class that started having trouble at the same time that subprime mortgages did: equity statistical arbitrage. The basic idea behind stat arb was that you could determine the expected correlations between different stocks, and bet that anomalies would revert. So if steel stocks are up 1% today, and one steel stock is up .5%, it’s a buy. Multiply the process many thousands of times over, and add a whole lot more complexity, and you have a highly profitable strategy—but it’s a strategy contingent on the idea that past trades and current trades provide information about future prices beyond the profits captured by those traders. (If someone buys a stock, and it rises, the information that they bought may indicate that it should rise—but does that information indicate it should rise past the point at which they bought it?)

There wasn’t a single stat arb firm. But, as it turned out, they were all using roughly the same strategies. When some firms started selling what they’d been buying and buying what they’d been selling, it signaled to the other firms that they should do the same, leading to the classic rush for the exits that characterizes a panic.

Many hundreds of billions of dollars had been invested in variants on this strategy. No one company dominated the market. No one failure would have made a difference. But the market dislocation did lead to a collective realization: that when everyone ran the same statistical tests over the same data, returns would be good whether or not there was any validity to the results, simply because they’d all make the same trades and push prices in the same direction. The funds that didn’t go under have a much healthier attitude, now.

As more assets get ‘financialized’, it’s a lot easier to construct a temporarily profitable consensus. In fact, as more assets get marked-to-market, it becomes easier to temporarily lose money by being right. The credit default swap is, among other things, a way to guarantee that you’ll lose money and everyone will think you’re wrong, continuously, until you end up right. Or bankrupt.

Fortunately, this financialization offers a solution to the restated too-big-to-fail program. You can find a way to bet on anything, whether it’s overpopulation, demographic decline, peak oil, the Singularity, China as the next superpower, China as the next Japan, etc. It’s easier than ever to articulate a divergent opinion by making the appropriate bet.

This gives you a very simple obligation: you need to seriously consider at least a few things that society holds sacred, and start actively disbelieving in them (and investing like you do). It’s probably safest to take a belief that could get you excluded from polite company, and look for less harmful beliefs that correlate with it. (People on the extreme left and extreme right were talking about the real estate bubble long before it popped.)

It’s your civic duty: do your part to make sure mainstream beliefs aren’t Too Big to Fail.

The Internet is an efficient marketing: any source of cheap, high-quality traffic won’t stay cheap or high-quality for long. When I started doing SEO, one of the cheapest ways to get traffic worked like this: First, come up with a list of keywords that people search, but that competitors don’t use in their sites; next, build pages that speak to the audience that searches for these keywords; and finally, use article directories to promote those pages.

A Different Plan: They Own Content, You Rent Visitors

The content factories have a different plan in mind: you can create all the landing pages you want, but they don’t intend for you to rank well for any of those target keywords: they’ll create their own junk content (for less than those article-directory articles cost), and then sell visitors one at a time through ads.

This is a terrible idea. It outsources a customer’s first encounter with a product to a company with a vested interest in making that interaction frustrating, but not infuriating (it bas to be frustrating because, as Patrick MacKenzie points out, the content must be less useful than the ads. If it’s infuriating, visitors will just leave. But that’s a low standard.)

A Word on Pricing SEO Services (and How People Get SEO Jobs)

This doesn’t just make the web a worse place, though: it also destroys the business model of small, independent SEO companies—and it makes it harder for new people to break into the industry.

The way I started doing SEO was simple: I answered an ad on Craigslist. The ad was looking for someone who could write simple articles, fast. And I can do that.

The good news about learning SEO this way is that I got to start with the very basic stuff: a refresher course on HTML, some practice writing useful information on pretty much any topic, an understanding of where people started their searches (and what steps they took next), and a peek into how keyword lists were generated.

I wouldn’t have gotten into this business if that opportunity hadn’t been available, but I can do the math: even as a part-time, off-site intern, my cost was at least 50% higher than Demand Media. And that’s not counting the value of the experience, which is obviously far higher.

Under the Demand Media model there’s no need to learn about SEO. Why bother, when the articles can be churned out so cheaply? They have their own algorithms to determine which keywords are useful, and their own formulae for crafting the right headline.

I’m not the only person who got a job that way, and I don’t work for the only company that started SEO as a sideline before it became a major production. For these companies—web designers or web developers who use SEO as a value-added service—it won’t be feasible to compete with content factories. The end result is not just less income for those designers and developers, but that it won’t make sense for them to optimize their customers’ sites.

What Google Can Do About Content Factories

The only thing Google can do here is apply a selective site-by-site penalty for junk content. This will hit article directories just as hard as these other sites, and it will cut into Google’s revenue (since these sites often use Google Adsense to make money).

The heuristic is not difficult, here: if a site has many links, but few links per page, and people tend to click on an ad once they get to the site, it’s clearly there just to take organic Google traffic and turn it into paid Google traffic. That might be nice for Google’s revenues, but it’s bad for their customers. (If Google doesn’t penalize them, maybe Bing will.)

Two Alternatives: Content Factories, but Benign; Or…

If we do need to live with content factories, I can see two ways it might be okay. First, content factories that handle writing articles based on someone else’s keyword list and specifications: these would offer tiered pricing based on quality and keyword lists, and would send organic traffic rather than ad traffic. The great thing about this model is that they could keep track of individual contributors, and forward the promising ones on to the companies that paid for their articles. It adds another kink to the SEO recruiting pipeline, but keeps it intact.

Second, we can get used to the idea that there’s a lot of junk content out there—more very day. Instead of creating lots of lower-quality content, SEOs can make a smaller number of very worthwhile pages, and pay for traffic to them. At the same time, searchers will learn to use broad terms, and then navigate from the site they land on (i.e. searching for “401K” instead of How to Determine if Your 401k is Safe).

In the latter case, we may see a bigger premium for more experienced copywriters with an SEO background. After all, they’ll be writing the landing pages that everyone sees, instead of pages seen only by people who search for a very narrow term. And when every visitor costs money, every improvement in copy translates directly into a higher return on a big investment.

So even the end of “free traffic” from long-tail terms could be good news.

SEO Hater’s P.S: If you think I’m alone on this, please note that programmers are doing it, too. It’s only a matter of time before Demand Media for apps appears. In fact, back in April I talked to a VC about something that boils down to “Demand Media for Apps.” Fortunately, we both had better things to do than to make that happen.