Category Archives: Social software

Viral Loop notes

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I just stumbled across a great site, Books Noted, which in it’s words provides “quotations, notes and takeaways on interesting books. These books further our knowledge in a variety of topics from psychology, entrepreneurship, philosophy, business and more. Since they tend to be hundreds of pages in length, these short notes and takeaways will get to the essence of the book for time strapped readers.” Below are the notes from Viral Loop, with my particular interest on the growth curve behind Hotmail and the story of how one mother got out of Chernobyl just in time – intuition is powerful:

* Products that require a customer education are best suited to direct selling… if you are unloading blue jeans, direct selling probably isn’t for you, since everyone knows what jeans are and what they are used for [what about cosmetics? Avon?]
* Jim Clark contacted Marc Andreesen after using the Mosaic browser for the first time
* Warren Buffett says “Get greedy when others are fearful and fearful when others are greedy.”
* Network effect: the more connections you have, the more nodes, the more people, the more valuable it will be
* “double viral loop” – every network creator is a user and every user is a potential network creator
* Successful viral expansion loop companies share these characteristics:
o Web-based: suited to the frictionless world of the Internet
o Free: users consume product at not charge
o Organizational technology: no content is created, users create it. Companies just organize the content
o Simple concept: easy and intuitive to use
o Built-in virality: users spread the product out of their own self-interest
o Extremely fast adoption, exponential growth, virality index, predictable growth rates, network effects, stackability, point of nondisplacement and ultimate saturation
* Fanout: Jurvetson noted a “mathematical elegance” to Hotmail’s “smooth exponential growth curves” in the company’s early days: Cumulative users = (1 + fanout) cycles Where “cumulative users” related to the number of Hotmail registered subscribers, “fanout” was the rate by which the product spread and “cycles” was the number of times the product was used in the time period since launch (or frequency multiplied by time). At the beginning, each Hotmail user, on average, brought in two new users each month. (In other words, the fanout equaled 2.)
* Controlled growth at Gmail: Paul Buchheit, the brains behind Gmail, purposely controlled the rate of adoption by instituting an invitation-only sign-up procedure. Because Gmail offered 1,000 megabytes of storage while others gave users only 4 megabytes, Buchheit chose to drag down Gmail’s growth rate so Google could keep the application operational without risking sluggish download times, outages, data loss, or any other performance problem that often emerges with rapid scaling.
* How Max Levchin survived Chernobyl: Fleeing the crumbling Soviet empire most likely saved their lives. When Levchin was eleven, his mother, a physicist who worked as a government research assistant, overheard news of a leak at the Chernobyl nuclear reactor, which was on the verge of a meltdown. Acid rain misted down as the family quietly vacated their home and rushed to the train station in Kiev. After they were onboard, news of the disaster became public, and hours later, as they chugged into Crimea, Soviet guards ordered them to turn back, fearful of contamination. Following an animated discussion, Levchin’s mother convinced them to check for radiation. All were clean, except Max, whose right foot sent the Geiger counter into spasms. The guard said the boy’s bone marrow was contaminated; his leg might have to be amputated. His mother told Max to take off his shoe and he was tested again. This time he passed and they were let through, sans shoe. The culprit was a radioactive rose thorn that had lodged in his sole as they escaped Kiev.
* What early PayPal was looking for: Because Thiel’s ultimate plan was to create a Web-based currency to undermine government tax structures, which would require taking on powerful interests like commercial banking, the cofounders sought people a lot like them: hypercompetitive, well-read, multilingual workaholics who had, above all, a proficiency in math and an aversion to authority.
o Thiel subscribed to a theory of human behavior known as “mimetic desire,” propounded by French historian and philosopher René Girard, who believed that people were essentially sheep who, without much reflection, borrowed their desires from others. This theory has been applied to describe financial bubbles and panics, when investors blindly act as a flock and follow what others are doing even if it flies in the face of economic logic, and to war and violence, which arise when two individuals vie for the same possession, leading to antagonism and strife. Pretty soon the object of desire is forgotten and all you’re left with is the antipathy.
o PayPal Mafia: The day that eBay took over, Thiel, Levchin, and Hoffman, who collectively took in more than $100 million, walked away from the viral company they had started just a few years earlier. But PayPal was simply the beginning for these former employees, and the lessons they learned at PayPal would spread virally to other viral concerns. Thiel founded his own hedge fund, Clarium Capital Management LLC, invested $750,000 in Facebook, and joined the board. Levchin created Slide, a widget maker that counts hundreds of millions of installs of its photo slideshow and other applications across social networks. Hoffman is the CEO of LinkedIn, a networking tool for business that counts almost 40 million members and, since it has multiple revenue streams, boasts that it is profitable. Roelof Botha, PayPal’s CFO, moved over to the venture capital side and became a partner at Sequoia Capital. One of his first investments was in YouTube, which was started by former PayPal alums Chad Hurley and Steve Chen.
* Michael Birch, founder of Bebo’s daily life: While Bebo grew at a fantastic rate overseas, Birch’s family life in San Francisco remained downright normal. He woke up at 6:30 a.m. to help his children get ready for school; then, after dropping them off, he and his wife would arrive at the office at 8:00 a.m., and Birch would spend half the day programming. The few meetings he held were with suppliers and prospective partners or advertisers. With Bebo adding ten thousand new members a week, either he or his head programmer was always on call, since they were the only ones who knew the site’s architecture. Since his co-coder got his kicks from skydiving, Birch would stress whenever he took to the sky. Then he would leave around 7:00 p.m. to see his kids for an hour before they went to bed. A few times a week he attended networking events, for instance, a website launch, and he traveled to England, where he and his wife would combine business with pleasure.
* Summary of online viral loop companies:
o Web-based: Better suited to the Internet
o Free: Users consume the product at no charge
o Organizational technology: They don’t create content, their users do
o Simple concept: Easy and intuitive to use
o Built-in virality: Users spread the product out of own self-interest
o Exponential growth: That is, the virality index is above 1.0, which creates predictable growth rates
o Network effects: The more who join, the more who have an incentive to join
o Stackability: A viral network can be laid over the top of another, helping both grow
o Point of nondisplacement: Becomes virtually impregnable
o Ultimate saturation: A point of maturity when growth slow

Who are the influencers?

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Moving back to valuing social networks, and who are influencers following listening to a Telligent webinar which included discussion on tracking ‘influencers’, I found the following quote from a recent GoViral report ‘The social metropolis’ (pdf) pretty interesting – it’s that passion, not position is what distinguishes an influencer.

Duncan J. Watts, a network-theory scientist from
Columbia University, has recently challenged the
theory of the influencer and the idea of viral marketing
as concept. Originally inspired by epidemiology,
the idea of viral marketing is that a few agents
can ignite and eventually drive a massive spread.
After analyzing e-mail patterns and setting up
computer simulated tests, Watts and his colleagues
found that even highly connected people are not really
the social hubs we expected them to be.

Watts created computer simulated societies to test this
theory, and they actually managed to create trends.
“The problem, I think, is that we have been defining
influentials incorrectly. They are not a particular class
of people like college grads or news junkies. Instead, the
title of influential migrates from one person to the next
depending on the topic of interest. One person is an
influential for computers, another is an influential for
wine. It’s a function of passion, not position.”

The main conclusion is that for the vast majority
of cases that spread, it was just as much a result
of average people – the ones that didn’t seem particularly
influential – as of those who were. In fact,
even when influentials had forty times the reach of
a normal person, you couldn’t be sure they could
kick-start a trend.

Indeed Dr Watts, interviewed over two years ago in FastCopmany, argued that just targetting ‘influencers’ was a big waste of marketing spend. But he also suggested a way that did work, which while not viral exactly ‘doubled’ the effect and used a bit of basic viral looping (if I may inelegantly call it that). It also rings true for anyone experienced in grassroots political campaiging for example, and no doubt is supported by Obama’s campaigning strategy:

In their hunt for a practical way to create maximum exposure for any given ad, Watts and Peretti developed a way to marry the benefits of old-school mass marketing with clever six-degrees effects. Their first test case came when the Brady Campaign, the gun-control group, asked for help with an online petition.

Watts and Peretti set up a regular mass-market ad buy, running banner ads on several prominent blogs and news sites. Like many ads these days, they added a button on the ad that allows people to forward the ad to a friend–a way of collecting eyeballs for free. Typically, people ignore this “share with your friends” pitch. But Watts and Peretti included technology called ForwardTrack, which displays the route the ad travels once you’ve forwarded it. This turned ad forwarding into a piece of social cartography. People would pass the ad specifically to those friends most likely to keep it moving. It became a Facebook-like contest to sign up the most friends.

The technique marries Watts’s two main epiphanies: Cascades require word-of-mouth effects, so you need to build a six-degrees effect into an ad campaign; but since you can never know which person is going to spark the fire, you should aim the ad at as broad a market as possible–and not waste money chasing “important” people. And it worked. The pass-around effect doubled the number of people who saw the Brady Campaign’s ad. They paid for 22,582 hits and received an additional 31,590 for free. Another campaign they ran for the Oxygen network quadrupled the audience size, adding 23,544 hits to the initial 7,064.

Neither was, technically, a viral hit. Neither passed the disease threshold, where the meme spreads exponentially and engulfs the mainstream. “But you can double your impact, which is still pretty good,” Watts says.

The ultimate irony of Watts’s research is that, if you really buy it, the most effective way to pitch your idea is … mass marketing. And that is precisely what the wizards of Madison Avenue, presiding over our zillion-channel microniche market, have rejected as obsolete. “But that’s the thing about magic,” says Watts. “If it sounds too good to be true, it probably is.”