“Bubbles are beautiful, fun and fascinating, but do you know what they are and how they work? Here’s a look at the science behind bubbles.” – About.com Chemistry, “Bubble Science”

“Double, double toil and trouble
Fire burn, and cauldron bubble.” – Macbeth, Act 4, Scene 1

Given the incredible volatility we’ve seen lately in the Bitcoin and gold markets, there has been a resurgence in discussion about bubbles. This topic is always top of mind in Silicon Valley, especially given that the two favorite local topics of conversation are technology companies and housing.

Defining a market bubble is actually a bit trickier than it might first appear. After all, what differentiates the inevitable booms and busts involved in almost any business and industry from a “bubble”?

The most common definition of a speculative or market bubble is when a broad-based, surging euphoria or wave of optimism carries asset prices well beyond supportable value. The canonical bubble was the tulip mania of the 1630s, but it extends across history and countries all the way up to the Internet bubble of the late 1990s and the housing bubbles in the past decade.

WHAT DO BUBBLES LOOK LIKE?

Not surprisingly, there are a number of great frameworks for thinking about this problem.

In 2011, Steve Blank and Ben Horowitz debated in The Economist whether or not technology was in a new bubble. In those posts, Steve cited the research of Jean-Paul Rodrigue denoting four phases of a bubble: stealth, awareness, mania and blow-off.

(Source: Wikipedia)

HOW DO BUBBLES HAPPEN?

In 2000, Edward Chancellor published an excellent history and analysis of market bubbles over four centuries and a wide variety of countries called “Devil Take the Hindmost: A History of Financial Speculation.” In his book, he finds at least two consistent ingredients.

• Uncertainty. In almost every bubble, there seems to be some form of innovation or insight that forces people to rapidly debate the creation of new economic value. (Yes, even tulip bulbs were once an innovation, and the product was incredibly unpredictable.) This uncertainty is typically compounded by some form of lottery effect, exacerbating early pay-offs for the first actors. Think back to stories about buying a condo in Las Vegas and flipping it in months for amazing gains. This creates the inevitable upside/downside imbalance that Henry Blodget recently framed as: “If you lose your bet, you lose 100%. If you win your bet, you make 1000%.” Inevitably, this innovation always leads to a shockingly large assessment of how much value could be created by this market.
• Leverage/Liquidity. In every bubble, there is some form of financial innovation that broadly increases both leverage and liquidity. This is critical, because the expansion of leverage not only provides massive liquidity to fund the expansion of the bubble, but the leverage also sets up the covenants that inevitably unwind when the bubble turns aggressively to the downside. In some ways, it’s also inevitable. When a large number of people believe they’ve found a sure thing, logic dictates they should borrow cheap money to maximize their returns. In fact, the belief it may be a bubble can make them even greedier to lever up their investment so they can “cash out” the most before the inevitable break.

BEHAVIORAL FINANCE LESSONS IN BUBBLES

Bubbles clearly have an emotional component, and to paraphrase Dan Ariely, humans may be irrational, but they are predictably irrational.

There are five obvious attributes of components of bubble psychology that play into market manias:

1. Anchoring. We hear a number, and when asked a value-based question, even unrelated to the number, they gravitate to the value that was suggested. We hear gold at $1,500, and immediately in the aggregate we start thinking that $1,000 is cheap and $2,000 might be expensive.
2. Hindsight Bias. We overestimate our ability to predict the future based on the recent past. We tend to over-emphasize recent performance in our thinking. We see a short-term trend in Bitcoin, and we extend that forward in the future with higher confidence than the data would mathematically support.
3. Confirmation Bias. We selectively seek information that supports existing theories, and we ignore/dispute information that disproves those theories. (This also tends to explain most political issue blogs and comment threads.)
4. Herd Behavior. We are biologically wired to mimic the actions of the larger group. While this behavior allows us to quickly absorb and react based on the intelligence of others around us, it also can lead to self-reinforcing cycles of aggregate behavior.
5. Overconfidence. We tend to over-estimate our intelligence and capabilities relative to others. Seventy-four percent of professional fund managers in the 2006 study “Behaving Badly”believed they had delivered above-average job performance.

The greater fool theory posits that rational people will buy into valuations that they don’t necessarily believe, as long as they believe there is someone else more foolish who will buy it for an even higher value. The human tendencies described above lead to a fairly predictable outcome: After an innovation is introduced and a market is formed, people believe both that they are among the few who have spotted the trend early, and that they will be smart enough to pull out at the right time.

Ironically, the combination of these traits predictably leads to these four words: “It’s different this time.”

IT’S DIFFERENT THIS TIME

After two massive bubbles in the U.S. in less than a decade, many people question spotting bubbles ahead of time is so difficult. In every bubble, a number of people do correctly identify the bubble. As in the story of the boy who cried wolf, however, the truth is apt to be disbelieved. The problem is that in every market, there are always people claiming that prices are too high. That’s what makes a market. As a result, the cry of “bubble” is far more often proven wrong than right.

Every potential bubble, however, provides an incredibly valuable frame for deepening and debating the role of human psychology in financial markets. Honestly and thoughtfully examining your own behavior through a bubble, and comparing it to the insights provided by behavioral finance, can be one of the most valuable tools an investor has to learning about themselves.

Basic Assumptions

Since there are an incredible number of technology and service choices that can affect a home media solution, it’s best I put some of the basic decisions that my household currently has made around media technology:

Comcast HD is our HD television service
• iTunes HD is our standard movie purchase format
• Netflix is used for movie rental
• Tivo is our DVR of choice

Of all of these choices, the ones that are most material are the choice of Comcast HD / Tivo, as Comcast is the best HD service for modern Tivo DVRs, and the standardization on iTunes HD, not Blu-Ray, for HD movie purchases.

Office Configuration

Our home media solution is grounded in the home office, but really has become fairly distributed between the cloud and local devices. In fact, at this point, the home office solution is really used more for backup and legacy purposes.

The key elements of the configuration are as follows:

• The iMac is really the “source of truth” for the media library in the house
• The media library is large (each HD movie is about 4GB), so it sits on its own 4TB USB HD
• The iMac backups up to the Synology box via Time Machine
• Wireless devices (laptops, iPads, iPhones) connect via 802.11N
• The Gigabit Ethernet switch is connected to the central home network

Living Room Configuration

The consumption solution in any room with a television is largely the same.  Here is a diagram of it’s fundamental components:

The key elements of the configuration are as follows:

• The Gigabit Ethernet switch connects all the devices to the central home network
• The AppleTV is used to watch purchased HD movies from iTunes, Netflix for streaming, and access the home media library on the iMac
• The Tivo is used to watch live / recorded television (from Comcast)
• The Blu-Ray is there theoretically if we wanted to watch a Blu Ray, which almost never happens

A Few Caveats

This solution currently has the notable sub-optimal elements:

• I didn’t include an A/V receiver or surround sound solution in the above description, because that actually varies room to room.  In some rooms we have an AV receiver, in others we utilize a surround sound bar or just use TV audio.

Input switching.  We almost never use the Blu-Ray, but this solution does require switching inputs between AppleTV & Tivo, which is a bit annoying since the Tivo remote can’t control the AppleTV and vice-versa.

While I’m sure this solution will not impress any cinephile out there, hopefully it will be useful to a few of you thinking through how to setup or reconfigure your home media solution.

I’ll try to do a follow up post with what I’m hoping to see in 2013 to make this even better.

Todays’ news is filled with discussion and analysis of Elon Musk’s aggressive response to the negative review of the Model S sedan in the New York Times.

• Stalled Out on Tesla’s Electric Highway (New York Times, 2/8/2013)
• A Most Peculiar Test Drive (Tesla Blog, 02/14/2013)

What makes Tesla’s response so ground breaking is that it involves releasing data, and lots of it.  There is some debate about the efficacy of Tesla’s response, and even more interest in the level of data collection that Tesla employs.

However, what I find most fascinating is the position Tesla is taking, in general, around data privacy for it’s users.

When is it OK to share user data?

Most modern websites and social networks have clear, articulated terms around the privacy protection they provide their users.  In general, these are encoded in both the user agreement that customers accept when they join the site, and the privacy policy that is provided for the site.

Tesla has, to my knowledge, staked out a new and interesting position around user data privacy:

After a negative experience several years ago with Top Gear, a popular automotive show, where they pretended that our car ran out of energy and had to be pushed back to the garage, we always carefully data log media drives.

The Tesla Privacy Policy has this to say about information sharing:

…we may share such information in any of the following circumstances:

* We have your consent.

* We provide such information to trusted businesses or persons for the sole purpose of processing personally identifying information on our behalf. When this is done, it is subject to agreements that oblige those parties to process such information only on our instructions and in compliance with this Privacy Policy and appropriate confidentiality and security measures.

* We conclude that we are required by law or have a good faith belief that access, preservation or disclosure of such information is reasonably necessary to protect the rights, property or safety of Tesla Motors, its users or the public.

So the question to be asked here, is which term is being used to justify the sharing of the journalist’s driving data?  I’m not a lawyer, but my guess is that Tesla would argue the third term covers this as necessary to protect Tesla Motors.

The Tesla Clause

Typically, the more specific and transparent a privacy policy is, the better.  Elon Musk is on the record as stating:

“While the vast majority of journalists are honest, some believe the facts shouldn’t get in the way of a salacious story.”

So the next question is, should web services reserve this right more generally?  Should it be explicit that the company reserves the right to reveal user data if deemed necessary to directly refute claims published publicly about the user’s experience with the product?

Will other web services implement the equivalent of a “Tesla Clause” in their privacy policies?

Keep Journalists Honest, Dampen Critique, or both?

If justified, this would dramatically increase the risk that journalists would take when publishing a product review of a web service.  For example:

• How aggressive would you be reviewing Google vs. Bing if you knew either company could reveal how your past browsing history affected your results?
• Would you critique Facebook’s new photo features aggressively if there was a risk that your photos might be included in a public response?
• Is it fair game to respond to a review criticizing the battery life of the iPhone 4 by publishing the the specific apps and services that journalist had running?

Alternatively, the “Tesla Clause” could prove extremely valuable:

• Forces journalists to more thoughtfully consider how their own usage patterns affected their results, and report that openly and honestly when applicable.
• Prevent journalists from cherry picking data and screenshots to support a pre-determined conclusion (or more likely, headline).
• Sets a marginally higher bar for web services to justify their rebuttals to negative product reviews.

Blackberry is on an impossible mission.

Why Blackberry?

I used a Blackberry for over seven years.  In fact, I didn’t move to the iPhone until the 3G came out with the native application platform.  Like many, I was addicted to the perceived and actual productivity of messaging on the Blackberry and the physical keyboard.

Like most people who make the switch, it took me a few weeks to get to be “good enough” to type and message effectively on the iPhone.  The millions who are still on the Blackberry tend to focus on exactly one issue: the Blackberry is an amazing messaging device, thanks to the keyboard & software optimization.

The Victory of the Touch Screen

I remember, in 2009, making a Blackberry my temporary “full time” mobile device for a few days.  It was amazing – in just a year, I had completely lost all the muscle memory that made me so productive on the Blackberry.  The iPhone had won.

The reason is simple: a fast, modern device that offers the full richness of the modern web, combined with a vibrant and high quality native application market dominates the marginal efficiency in messaging.  Whether you use iOS or Android, minor productivity improvements in SMS & Email are swamped by access to applications, games, web services, cloud platforms and a myriad of other capabilities.  The smartphone itself has now evolved into a variety of form factors and niches, with phablets and tablets eating an increasing share of our attention and computing.

Blackberry’s Impossible Mission

Right now, it seems like Blackberry has no viable path as a third platform.

Yes, the ardent users of the platform can buy the new devices for their hardware keyboards.  But there aren’t enough of them (h/t to Daring Fireball), and it’s hard to imagine that this market won’t get eaten by the flexibility provided by the Android platform in time.

Yes, there are IT departments that continue to have their companies locked down on the Blackberry, but it’s unlikely the the new operating system won’t create sufficient migration issues that they won’t move to either iOS, Android or both as supported platforms.

The real problem is that their touchscreen product cannot possibly provide enough unique functionality to justify the choice over the iPhone or Android at the medium to high end.  At the low end, they cannot possibly underprice the Android ecosystem.

Damned if they do, Damned if they don’t

In other words, if they abandon their customer-defined differentiator (keyboard), they’ll lose all differentiation in the market.  If they don’t, they are left with an eroding, minority share of a market that is likely insufficient in size and economics to fund their continued development and support of a competitive mobile ecosystem.  As a developer, spending precious resources on this, at best, stagnant minority pool of potential users is tough to justify.

Microsoft can play this game, for a while, because they (still) have relatively unlimited free cash flow and a desktop platform that still boasts hundreds of millions of users.  Blackberry doesn’t.

As many long time readers know, personal finance has always been a passion of mine.  However, now that I’m moving from this being a personal passion to a professional role, there are some important disclosures that have to be made.

First, it needs to be stated that Psychohistory is my personal blog and is not written in my capacity as COO of Wealthfront Inc.  Nothing on this blog should be construed as, nor is it intended to be, personal investment advice.  The content of this blog represents my own views and/or opinions and does not represent the views and/or opinions of Wealthfront Inc.

Second, I’ve added a Disclosure tab to this blog, to ensure that at any time, any new visitor will have quick access to this information.

Third, none of the historical content of this blog is being modified from its original.  Those articles were written for purely personal reasons, and are appropriate for the time they were published.  That being said, going forward, I’m only going to publish content related to personal finance and investing through the official Wealthfront blog.  Wealthfront has published a fantastic series of articles on a wide range of topics, and I feel privileged to be added as one of the contributing authors there.

I will continue to blog here about personal topics of interest, including product management, design, software development, Silicon Valley, startups, tech tips, science, and of course coins.

Can’t wait to get started tomorrow.

Here’s an excerpt:

About 55,000 tourists visit Liechtenstein every year. This blog was viewed about 310,000 times in 2012. If it were Liechtenstein, it would take about 6 years for that many people to see it. Your blog had more visits than a small country in Europe!

Click here to see the complete report.

Last night, I tweeted out my joy at finding out that Apple did, in fact, provide a menu item to re-enable the side navigation in iTunes 11.  Now, while I’m not a huge fan of the complexity and modality of the older iTunes interface, there is no doubt that after using iTunes 11 for a week, you wish for the halcyon days of the left navigation bar.

Surprisingly, enough people tweeted and commented in gratitude that I realized I should probably summarize in a blog post.

iTunes 11 – Default

This is the iTunes 11 default interface. (Try to ignore my taste in movies for a second)

iTunes 11 – Sidebar

This is iTunes 11 with the sidebar enabled.

All of a sudden, the shockingly horrid modality of the iTunes 11 default interface is resolved.  You can easily select which sub-category of content in your iTunes library you want to browse, and viewing connected devices and playlists has once again become trivial.  It turns out, you still end up with the horrid choices for navigation views within a “domain”, but at least we’re 80% of the way back to the (limited) usability of the previous iTunes interface.

Wait, How Did You Do It?

It’s hidden under the View menu, “Show Sidebar”

Simple does not mean Easy to Use

Just as cuffs, collars and neckties are subject to the whims of fashion, so also do memes in design tend to come and go in software.  I think iTunes 11 represents a bit of a teachable moment on a couple concepts that have been overplayed recently, and what happens when you take them too far.

1. Consistency does not always lead to ease of use.  Having a more consistent interface between the iPhone, iPad, AppleTV and Mac OS renditions of iTunes may seem like an “obvious” goal, but the fact is all of these devices vary in terms of input mechanisms and use cases.  The truth is, many users sit down at a desktop for different tasks than they sit down at a TV for, and the interface of the desktop is optimized for those tasks with large, high resolution screens and a keyboard.My best guess here is that Apple optimized the interface for laptops, not desktops, and for consumption, not curation. However, Apple would have been well served to provide a “first launch” experience with packaged pre-sets of these minor configurable options, to let users who are upgrading easily identify their primary mode of operation.I would love Apple to take a more proactive stance on how to build applications and services that provide elements of commonality across the multitude of devices that users increasing use to author, curate and consume content with, without blind adherence to making everything look & behave “the same”.
2. Simple does not mean easy to use.   On the heals of Steve Jobs mania, it has become ultra-fashionable to talk about simplicity as the end-all, be-all of product design.  The fact is, there is often a trade off between reducing the number of controls that an application (or device) has, and introducing increased modality for commonly used functions.  The one button mouse was, in fact, simpler than the two button mouse.  However, it came at the expense of pushing a significant amount of functionality into a combination of selection and menu modality.Look at the poor “single button” on the iPhone.  Simple, but now stacked with modality based on the number and timing of presses.Designers would do well to consider the balance of simplicity, accessibility and the difficult decision of which functions are so key to an application that they require “zero click” comprehension of availability.  For iTunes 11, the hidden modality of managing the devices synched to your iTunes library is unforgivable. (The likely sin here is being too forward looking. As we move to iCloud for everything, the need for devices to be tethered to iTunes goes away.  But we’re not there yet with video.)

I hope this helps at least one person out there have a better experience with iTunes 11.

From Human Capital to Financial Capital

One way to imagine your professional life is overlay of two types of capital: the building and growing of your human capital, and the transformation of that human capital into financial capital.

It feels like just yesterday that I was writing a blog post here about my first day at LinkedIn. At its heart, LinkedIn is building, growing & leveraging human capital throughout your career.  Wealthfront provides an answer to the second part of that equation – how to grow and leverage the financial capital that you accumulate throughout your career.

As Marc Andreessen put it, software is eating the world, and it is providing us a platform to bring the features and sophistication previously only available to the ultra-rich, and making it available to anyone who wants to protect & grow their savings.

Too many good, hard-working individuals today lack access to many of the basic advantages accorded to people with extremely high net worth.  With software, Wealthfront can bring features and capabilities normally available only to those with multi-million dollar accounts to everyone, and at a fraction of the cost.

Personal Finance as a Passion

For regular readers of this blog, the fact that personal finance has been a long standing passion of mine comes as no surprise.  What many don’t know is that this passion dates all the way to back to my time at Stanford, where despite one of the best formal educations in the world, there was really no fundamental instruction on personal finance.

In fact, upon graduation, I joined with about a dozen friends from Stanford (mostly from engineering backgrounds) to form an investment club to help learn about equity markets and investing together.  (In retrospect, the members of that club have been incredibly successful, including technology leaders like Mike Schroepfer, Amy Chang, Mike Hanson and Scott Kleper among others.)

A Theme of Empowerment

As I look across the products and services that I’ve dedicated my professional life to building, I’m starting to realize how important empowerment is to me.  At eBay, I drew continued inspiration from the fact that millions of people worldwide were earning income or even a living selling on eBay.  At LinkedIn, it was the idea of empowering millions of professionals with the ability to build their professional reputations & relationships.

With Wealthfront, I find myself genuinely excited about the prospect of helping millions of people protect and grow the product of their life’s work.

We’ve learned a lot in the past thirty years about what drives both good and bad behaviors around investing, and we’ve also learned a lot about how to design software that engages and even delights its customers.  The time is right to build a service that marries the two and helps people with one of the most important (and challenging) areas of their adult lives.

A Special Thank You

I want to take a moment here to voice my utmost thanks to the team at Greylock Partners.  My year at the firm has given me the opportunity to learn deeply from some of the best entrepreneurs, technology leaders and venture capitalists in the world.  The quality of the entrepreneurs and investors at Greylock forces you to think bigger about what is possible.  Fortunately, Greylock is also a partnership of operators, so they understand the never-ending itch to go build great products and great companies.

… And Lastly, A Couple of Requests

Since this is a personal blog, I don’t mind making a couple of simple requests.  First, if you have a long term investment account, whether taxable or for retirement, I would encourage you to take a look at Wealthfront.  I’d appreciate hearing what you think about the service and how we can make it better.

Second, and perhaps most importantly, we are hiring.  So let me know if you are interested in joining the team.

Family Man

My grandfather met my grandmother in a surprisingly familiar story. At 15, his mother asked a neighbor if their daughter, aged 13, could help tutor their son in French and Math. Smitten with his tutor, five years later they were married. Sixty nine years later, they had four children, seventeen grandchildren and six great-grandchildren.

Work with your hands

Douglas Churnin was always a man who worked with his hands. Though educated at NYU, he was always more comfortable and confident with any project or activity that involved working with physical material. Generous and selfless, his favorite expression was to respond to a request with “no problem”.

He was a big man, with old fashioned strength. Interestingly, he would never admit to being six feet tall. He would always insist he was just “five eleven and three quarters”.

When I think of my grandfather, and all of the projects he helped me with over the years, I can’t help but reflect on the parables and expressions that were his favorites:

• Measure twice, cut once
• With the right tools, any job is easy

I ended up being an engineer myself, and although I spend the dominant share of my time working with ethereal, virtual software, those who know me know that I find incredible comfort in working on projects in the physical world. It’s one of the reasons I make far too many trips to Home Depot, and why I’m always eager to not just read about how things work, but actually take the time to build them.

Measure twice, cut once

They say it’s impossible to really know your parents as people, and thus imagine the difficulty trying to really understand the life of someone born two generations before yourself. But while I may have only had the opportunity to really know a sliver of my grandfather’s life, I find myself shaped significantly by him.

When I’m rushing through designs and organizations in the incredibly fast paced technology world, it’s useful to remember that some changes can’t be undone. For those, you should truly measure twice and cut once.

When I’m struggling with a problem, based on some sort of ridiculous, MacGuyver-inspired, “fix it with paperclips and bubblegum” solution, it’s worth remembering that investing in the right tools can make any job easy.

When I’m thinking about how I want to live my life, it’s worth remembering that Douglas Churnin married the woman he loved, built a life together for sixty nine years, and passed away surrounded by the large, vibrant family he helped build.

It’s wonderful to know that it can and does happen, even in 2012.

I was driving home on Sunday, listening to the radio, and it occurred to me how different the financial news would be if Apple ($AAPL) was in the Dow Jones Industrial Average (^DJI).

Of course, being who I am, I went home and built a spreadsheet to recalculate what would have happened if Dow Jones had decided to add Apple to the index instead of Cisco back in 2009.  Imagine my surprise to see that the Dow be over 2000 points higher.

Update: AAPL at $700

With the launch of the iPhone 5, we find ourselves roughly 7 months later.  For fun, I re-ran the spreadsheet that calculated what the DJIA would be at if they had added AAPL to the index in 2009 instead of CSCO. (To date, I’ve never seen an explanation on why Cisco was selected to represent computer hardware instead of Apple.)

Result: Dow 16,600

As of September 17, 2012, AAPL closed at 699.781/share.  As it turns out, if Dow Jones had added Apple instead of Cisco in 2009, the index would now be at 16,617.82.  Hard to think that hitting all new highs wouldn’t be material for market psychology and the election.

Anyone up for Dow 20,000?

Over the past few months I been fortunate enough to give over a dozen talks at various events and companies about user acquisition, virality and mobile distribution.  One of the best parts of the experience is that, without fail, every talk yields a new set of questions and insights that help me learn and refine my own thinking on distribution & growth.

One of the most common questions I get is around the difference between my definition of “viral factor” and the semi-standard definition of “K Factor” that has been floating around for a few years.

What’s a K Factor?

Wikipedia offers a fairly concise definition of a K factor, a term borrowed from epidemiology.

i = number of invites sent by each customer
c = percent conversion of each invite
k = i * c

As the wikipedia article explains:

This usage is borrowed from the medical field of epidemiology in which a virus having a k-factor of 1 is in a “steady” state of neither growth nor decline, while a k-factor greater than 1 indicates exponential growth and a k-factor less than 1 indicates exponential decline. The k-factor in this context is itself a product of the rates of distribution and infection for an app (or virus). “Distribution” measures how many people, on average, a host will make contact with while still infectious and “infection” measures how likely a person is, on average, to also become infected after contact with a viral host.

What’s a Z Factor?

This blog post from Mixpanel in 2009 does a great job of walking through the standard definition of Z factor.  Hat tip to Dave McClure for his slide, which is included in the post.

Based on this framework, the Z factor is literally the percentage of users who accept a viral invitation that they receive.

The Problem with K & Z Factors

I meet with a startup that told me proudly that they had measured the viral factor of their new service, and that it was over 2.  My first question, of course, was:

“over what time period?”

In my blog post on viral factor basics, I define a viral factor as follows:

“Given that I get a new customer today, how many new customers will they bring in over the next N days?”

The key to understanding viral math is to remember a basic truth about rabbits.  Rabbits don’t have a lot of rabbits  because they have big litters.  Rabbits have a lot of rabbits because they breed frequently.

You’ll notice that, unlike the other popularized definitions, I focus on a new variable, “N”, the number of days it takes for your viral cycle to complete.  I do this for a simple reason: cycle time matters.   The path to success is typically the combination of a high branching factor combined with a fast cycle time. If you don’t think deeply about the channels you are using for viral distribution, you risk prioritizing the wrong features.

How Do You Pick the Right Cycle Time?

Once a growth team digs into the numbers, they quickly realize that there is no one “cycle time”.  So what number do you pick for analysis?

There is no right answer, but in general, you tend to find in the data that there is a breakpoint in the data where a vast majority of all viral events that are going to complete are going to complete.  For example, maybe with a viral email you’d see most responses happen in 24 hours, with 90% of total responses happening within 3 days.  If that’s the case, picking 3 days might be the right cycle time for your feature.  Once you pick a cycle time, the conversion rate gets built into your projections.

Cycle Time Matters

If you are already focused on the new user experience, distribution and virality, well then kudos to you and team.  Too many consumer products to this day spend too little time focused on these problems.

But if you want to see clear, demonstrable progress from your growth team, make sure you include cycle time in your thinking about what viral features will be most effective for your product.

Now go out and make a lot of rabbits.

To frame the discussion, I chose to walk through the following structure:

• Web 1.0 vs. Web 2.0
• Social Networking as a disruptive platform
• LinkedIn as an example of a social platform
• Mobile as a disruptive accelerator for social platforms
• Thoughts on future disruptions

On a personal note, I hadn’t actually been back to visit NASA Ames Research Center since my internship during my senior year in high school (21 years ago).  Back then, I was helping develop simulation software for fluid dynamics simulations in Fortran.  Thankfully, no one asked me to code in Fortran during the Q&A.

The team at Singularity U was incredibly gracious, and I appreciated the opportunity to talk to the class.

Google: The Era of Utility

The progress of the last five to seven years is really a significant breakout from the previous generations of software design.

For decades, software engineers and designers focused on utility:  value, productivity, speed, features or cost.

If it could be quantified, we optimized it.  But at a higher level, with few exceptions, we framed every problem around utility.  Even the field of human-computer interaction was obsesses with “ease of use.”  Very linear, with clear ranking.  How many clicks? How long does a task take?  What is the error rate?

In some ways, Google (circa 2005) represented the peak of this definition of progress.  Massive data.  Massive scalability. Incredibly utility.  Every decision defined by quantifying and maximizing utility by various names.

But let’s face it, only computer scientists can really get passionate about the world’s biggest database.

Social: The Era of Emotion

Like any ecosystem, consumer technology is massively competitive.  Can you be faster, cheaper, bigger or more useful than Google?  It turns out, there is a more interesting question.

Social networks helped bring the language of emotion into software.  A focus on people starts with highly quantifiable attributes, but moves quickly into action and engagement.

What do people like? What do they hate? What do they love? What do they want?

In parallel, there have been several developments that reflect similar insights on the web, in behavioral finance, and the explosion in interest in game mechanics.

Human beings are not rational, but (to borrow from Dan Ariely) they are predictably irrational.  And now, thanks to scaling social platforms to over a billion people, we have literally petabytes of data to help us understand their behavior.

Passion Matters

Once you accept that you are designing and selling a product for humans, it seems obvious that passion matters.

We don’t evaluate the food we eat based on metrics (although we’d likely be healthier if we did).  Do I want it? Do I love it? How does it make me feel?

The PayPal mafia often joke that great social software triggers at least one of the seven deadly sins. (For the record, LinkedIn has two: vanity & greed).  Human beings haven’t changed that much in the past few thousand years, and the truth is the seven deadly sins are just a proxy for a deeper insight.  We are still driven by strong emotions & desires.

In my reflection on Steve Jobs, he talks about Apple making products that people “lust” for.  Not the “the best products”, “the cheapest products”, “the most useful products” or “the easiest to use products.”

Metrics oriented product managers, engineers & designers quickly discover that designs that trigger passion outperform those based on utility by wide margins.

The Game Has Changed

One of the reasons a number of earlier web giants are struggling to compete now is that the game has changed.  Utility, as measured by functionality, time spent, ease-of-use are important, but they are no longer sufficient to be competitive. Today, you also have to build products that trigger real emotion.  Products that people will like, will want, will love.

Mobile has greatly accelerated this change.  Smartphones are personal devices.  We touch them, they buzz for us. We keep them within three feet of us at all times.

Too often in product & design we focus on utility instead of passion.  To break out today, you need to move your efforts to the next level.  The questions you need to ask yourself are softer:

• How do I feel when I use this?
• Do I want that feeling again?
• What powerful emotions surround this product?

Go beyond utility.  Design for passion.

The Wrong Model: Linear

When a couple decides to have a second child, you are quickly inundated with advice on how to manage the complexity.  The most common refrain you hear is: “Don’t worry, you can still field man-on-man coverage.”  Another popular version of this advice is: “At least you’re not outnumbered.”

The implication here is that managing the family is fundamentally a relationship between parents & kids, like this:

Parental Ratio = # of Parents / # of Kids

With the implication that somehow, as long as the parental ratio is greater than or equal to one, you’ll be able to manage.

Unfortunately, I’ve found that this description of complexity dramatically understates the drama of real family life.

The Right Model: Combinatorics

Instead 0f focusing specifically on the number and types of nodes in the family graph, I think it’s more useful to think about the nature of emotional entanglements (aka “drama”) and understand that they tend to require at least two people, but can easily involve more.  As a result, the complexity of family life can be more accurately modeled as the number of two-party relationships in a family that can engage in drama.

Initially, a couple has exactly one potential pair:

• Adult 1 <-> Adult 2

However, once you add a single child to the mix, you immediately add two more vectors of potential drama:

• Adult 1 <-> Child 1
• Adult 2 <-> Child 1

It’s worth noting that it’s sometimes unclear whether a three-party argument is truly a single argument or actually a combination of two or three two-party arguments, but let’s just roll with the simplified assumption for now that all drama can be decomposed to pair-based drama.

Pascal’s Triangle actually makes calculating this number for any size family trivial.  This means that:

• Two family members (0 kids): 1 drama pair
• Three family members (1 kids): 3 drama pairs
• Four family members (2 kids): 6 drama pairs
• Five family members (3 kids): 10 drama pairs
• Six family members (4 kids): 15 drama pairs

It’s combinatoric, specifically in the form of:

family complexity  = # of family members  choose 2

Which is a fancy way of saying each new child adds a new relationship to the mix for every existing family member.  This sequence is also known as the triangular numbers.

For those of you who have or come from large families, let me know if this lightweight graph theory matches your experience.

Julia Elizabeth Nash
Born 10.0 lbs, 21 inches
Single handedly increased Nash family complexity by 50%

Our Nintendo Wii gave up the ghost a couple of weeks ago.  After ordering a replacement on eBay, and then returning it due to this issue, I was shocked to get a second Wii with the same problem.  Realizing it must be a configuration issue, I was able to diagnose and correct for it.  I’m posting the solution here to help any other unfortunate souls with the same problem.

Symptoms

Your Nintendo Wii displays a blank, solid green screen.  Sound works fine, but nothing but green on the TV.

Likely Cause

You have a new Nintendo Wii and have used a component cable (Green-Blue – Red + Red-White) to connect it to an HD television.

By default, the Nintendo Wii comes configured to display 480i signals.  The problem is, newer high definition TVs don’t handle a 4:3 480i signal properly from component cables, and the Nintendo Wii doesn’t self-configure for 480p when you plug in component cables.

What makes this devilishly complicated is that if you try to configure the Wii using the standard RCA cable (Yellow-Red-White), the option to change the display to 480p is greyed out.  Catch-22.

Solution

Here are the steps to properly configure your Nintendo Wii for component display:

• Hook up your Nintendo Wii using the component cable.
• Instead of plugging the Green-Blue-Red cables into your display using the component ports, instead plug the green cable into the “Yellow” port of the RCA ports on your display.
• You will now get a greyscale rendering of your Nintendo Wii interface, but totally usable.
• Navigate through the configuration screens.  When complete, go to settings, and then select “Display”.  You’ll find that the 480p option is now selectable.  Choose it.  Also make sure to set the display to 16:9 if you have an HD display.
• Shut off the Wii, and hook up your component cables to the component jacks on your display.

That’s it.  Fairly simple, but I had to dig through a number of bad google results to figure it out.

Hope this helps someone out there, and saves you from returning a perfectly good Nintendo Wii.

Greylock Blog: User Acquisition, Virality & Mobile – Notes from Our Session with Adam Nash

Last week, I also had the opportunity to give a similar talk at 500 Startups.  As promised for those who couldn’t attend, here is a short list of relevant blog posts from the past two years that provide more depth to the topic:

Product Leadership

• Be a Great Product Leader
  
• Great Product Leaders Win Games
• Top 10 Product Leadership Lessons

Design Led Product

• Designers: Getting the Most Out of Your Product Manager
• Want Engagement? Find the Heat.

User Acquisition & Virality

• User Acquisition: The Five Sources of Traffic
• User Acquisition: Viral Factor Basics
• User Acquisition: Mobile Applications and the Mobile Web
• New User Experience, Engagement & Virality

Product Prioritization

• Product Prioritization: Three Feature Buckets
• Embrace the Minimum Necessary Change (MNC)

You only get one chance to make a first impression

Probably the biggest mistake you can make with your new user experience is to think of it as “registration”.  Registration is a bureaucratic, painful process that everyone hates in real life.  Your “new user experience” is your first and likely only shot at engaging your potential customer.  More importantly, if you are successful at user acquisition and grow rapidly, your new user experience is likely the most prominent representation of your product to the world.  Effectively, your new user experience is your brand.

Plant the seeds for future engagement

When people think of registration flows, they think of optimization.  Click through rates.  Conversion percentages.  This leads people to cut their sign up process down to a bare minimum.

Don’t get me wrong – you should be critical of every obstacle you put in a new user’s path.  If you lose that user on their first visit, odds are you’ll never engage them again.  That being said, you do need to ask for sufficient information to ensure that your product will not only successfully engage the user on their first visit, but plant the seeds of their next visit to your site.  (Zynga, bless their hearts, did this almost literally with Farmville.)

Most modern, social products end up minimizing their new user experience to three critical types of information:

• Identity: getting enough about you to provide some level of personalization and relevance, so you can begin to care about your identity on the site.
• Relationships: assuming the product has been designed to be intrinsically social, it should get better the more people you know who are using it.
• Communication: some mechanism (email, Facebook, LinkedIn, Twitter) to facilitate future communication with you, and between you and other users.

Their first visit is likely your most powerful viral opportunity

This may be counter-intuitive, but your new user experience is likely also fundamentally important to virality and growth.

Remember, as discussed in my previous post on viral factor basics, there are a couple of simple facts about viral growth:

• Growth only happens when a user somehow shares content with a non-member through your service.
• Cycle time matters.  The faster your cycle time, the quicker your service will grow in any given time period.

Literally by definition, a user’s first experience with your product and service is the first time you can help them start a new viral cycle.  So if you want a short viral cycle, you need to include the opportunity for users to connect with non-users in their very first experience.

This effect is compounded by the fact that there are quite a few users you may never see again on your site.   As a result, the new user experience may not only be your best shot at getting them to invite others, it may be your only shot.

T-Shirts Matter

In 2008, we officially said goodbye to registration at LinkedIn, and kicked of the New User Experience team.  In the spirit of my original diatribe on why t-shirts matter, it’s worth noting that this was one of the most popular and sought after t-shirts in LinkedIn history.

Now go make your new user experience great.

On December 2, 2002, I came home to find my wife waiting for me in the parking lot of our apartment complex.  I was immediately whisked away to pick up a surprise gift, a new beagle puppy.  There were a few puppies left in the litter, but I chose the one who peed when he saw us.  He was about eight weeks old at the time.

We picked a beagle because we lived in a small apartment at the time, but didn’t want to get a “toy” dog.  At the time, Star Trek Enterprise was still on TV, and I had asked Carolyn what type of dog Captain Archer had.  After meeting a few beagles at the local Starbucks, we were sold.

Newton was named based on an arcane naming convention matching three criteria: had to be a scientist, had to be an apple product or codename, had to end in “N” to go with Nash.

Newton was the first addition to our little family, which eventually added a second beagle (“Darwin”), and three children.  He was a 13″ beagle who grew up to be nearly 17″ at the shoulder.  He didn’t have a huge tolerance for party tricks, but could sit, stay, lie down, roll over and on a good day, do a military crawl.  Despite a somewhat extreme fondness for licking ears, he was incredibly gentle and playful with friends and strangers alike.

We knew our time with him was short, but didn’t realize it would be this short.  He will be missed.  I’ve posted a selection of photos from the last nine years below.  Many thanks to Eric Cheng, who took a few of the best shots over the years on his regular visits to suburban madness.

In the first two posts in this series, we covered the basics of the five sources of traffic to a web-based product and the fundamentals of viral factors.  This final post covers applying these insights to the current edge of product innovation: mobile applications and the mobile web.

Bar Fight: Native Apps vs. Mobile Web

For the last few years, the debate between building native applications vs. mobile web sites has raged.  (In Silicon Valley, bar fights break out over things like this.) Developers love the web as a platform.  As a community, we have spent the last fifteen years on standards, technologies, environments and processes to produce great web-based software.  A vast majority of developers don’t want to go back to the days of desktop application development.

Makes you wonder why we have more than a million native applications out there across platforms.

Native Apps Work

If you are religious about the web as a platform, the most upsetting thing about native applications is that they work.  The fact is, in almost every case, the product manager who pushes to launch a native application is rewarded with metrics that go up and to the right.  As long as that fact is true, we’re going to continue to see a growing number of native applications.

But why do they work?

There are actually quite a few aspects to the native application ecoystem that make it explosively more effective than the desktop application ecosystem of the 1990s.  Covering them all would be a blog post in itself.  But in the context of user acquisition, I’ll posit a dominant, simple insight:

Native applications generate organic traffic, at scale.

Yes, I know this sounds like a contradiction.  In my first blog post on the five sources of traffic, I wrote:

The problem with organic traffic is that no one really knows how to generate more of it.  Put a product manager in charge of “moving organic traffic up” and you’ll see the fear in their eyes.

That was true… until recently.  On the web, no one knows how to grow organic traffic in an effective, measurable way.  However, launch a native application, and suddenly you start seeing a large number of organic visits.  Organic traffic is often the most engaged traffic.  Organic traffic has strong intent.  On the web, they typed in your domain for a reason.  They want you to give them something to do.  They are open to suggestions.  They care about your service enough to engage voluntarily.  It’s not completely apples-to-apples, but from a metrics standpoint, the usage you get when someone taps your application icon behaves like organic traffic.

Giving a great product designer organic traffic on tap is like giving a hamster a little pedal that delivers pure bliss.  And the metrics don’t lie.

Revenge of the Web: Viral Distribution

OK. So despite fifteen years of innovation, we as a greater web community failed to deliver a mechanism that reliably generates the most engaged and valuable source of traffic to an application.  No need to despair and pack up quite yet, because the web community has delivered on something equally (if not more) valuable.

Viral distribution favors the web.

Web pages can be optimized across all screens – desktop, tablet, phone.  When there are viral loops that include the television, you can bet the web will work there too.

We describe content using URLs, and universally, when you open a URL they go to the web.  We know how to carry metadata in links, allowing experiences to be optimized based on the content, the mechanism that it was shared, who shared it, and who received it.  We can multivariate test it in ways that border on the supernatural.

To be honest, after years of conversations with different mobile platform providers, I’m still somewhat shocked that in 2012 the user experience for designing a seamless way for URLs to appropriately resolve to either the web or a native application are as poor as they are.  (Ironically, Apple solved this issue in 2007 for Youtube and Google Maps, and yet for some reason has failed to open up that registry of domains to the developer community.)  Facebook is taking the best crack at solving this problem today, but it’s limited to their channel.

The simple truth is that the people out there that you need to grow do not have your application.  They have the web.  That’s how you’re going to reach them at scale.

Focus on Experience, Not Technology

In the last blog post on viral factors, I pointed out that growth is based on features that let a user of your product reach out and connect with a non-user.

In the mobile world of 2012, that may largely look like highly engaged organic users (app) pushing content out that leads to a mobile web experience (links).

As a product designer, you need to think carefully about the end-to-end experience across your native application and the mobile web.  Most likely, a potential user’s first experience with your product or service will be a transactional web page, delivered through a viral channel.  They may open that URL on a desktop computer, a tablet, or a phone.  That will be your opportunity not only to convert them over to an engaged user, in many cases by encouraging them to download your native application.

You need to design a delightful and optimized experience across that entire flow if you want to see maximized self-distribution of your product and service.

Think carefully about how Instagram exploded in such a short time period, and you can see the power of even just one optimized experience that cuts across a native application and a web-based vector.

Now go build a billion dollar company.

In the first post in this series, we covered the basics of the five sources of traffic to a web-based product.  This next post covers one of the most important, albeit trendy, aspects of user acquisition: virality.

It’s About Users Touching Non-Users

Look at your product and ask yourself a simple question: which features actually let a user of your product reach out and connect with a non-user?   The answer might surprise you.

At LinkedIn, we did this simple evaluation and discovered that out of thousands of features on the site, only about a half-dozen would actually let a user create content that would reach a non-user. (In fact, only a couple of these were used in high volume.)

I continue to be surprised at how many sites and applications are launched without having given careful thought to this exactproblem.  Virality cannot easily be grafted onto a service – outsized results tend to be reserved for products that design it into the core of the experience.

Useful questions to ask, from a product & design perspective:

• How can a user create content that reaches another user?
• How does a users experience get better the more people they are connected to on it?
• How does a user benefit from reaching out to a non-user?

Understanding Viral Factors

One of the most useful types of metrics to come out of the last five years of social software is the viral factor.  Popularized by the boom of development on the Facebook platform in 2007, a viral factor is a number, typically between 0.0 and 1.0.  It describes a basic business problem that affects literally every business in the world:

“Given that I get a new customer today, how many new customers will they bring in over the next N days?”

“N” is a placeholder for a cycle time that makes sense for your business.  Some companies literally track this in hours, others 3 days, or even 30.  Let’s assume for now that 7 is a good number, since it tells you given a new customer today, how many new customers will they bring in over the next week.

Basic Viral Math

The good news is, once you identify the specific product flows that allow users to reach non-users, it’s fairly easy to instrument and calculate a viral factor for a feature or even a site.  But what does the number really mean?

Let’s assume a viral factor of 0.5, and an N of 7.  If I get a new user today, then my user acquisition will look like this over the next few weeks:

1 + 0.5 + 0.25 + 0.125 ….

It’s an infinite series that adds up to 2.  By getting a new user, the virality of this feature will generate a second user over time.

Two obvious epiphanies here:

• A viral factor is a multiplier for existing sources of user acquisition.  0.5 is a 2x, 0.66 is a 3x, etc.
• Anything below 0.5 looks like a percentage multiplier at best.

What about a viral factor of 1.1?

One of the memes that started to circulate broadly in 2008 was getting your viral factor to “1.1″.  This was just a proxy for saying that your product or service would explode.  If you do the math, you can easily see that any viral factor or 1.0 or higher will lead to exponential growth resulting in quickly having every human on the planet on your service.

I don’t want to get into a Warp 10 debate, but products can in fact have viral factors above 1.0 for short periods of time, particularly when coming off a small base.

Learning from Rabbits

The key to understanding viral math is to remember a basic truth about rabbits.  Rabbits don’t have a lot of rabbits  because they have big litters.  Rabbits have a lot of rabbits because they breed frequently.

When trying to “spread” to other users, most developers just focus on branching factor – how many people they can get invited into their new system.  However, cycle time can be much more important than branching factor.

Think of a basic exponential equation: X to the Y power.

• X is the branching factor, in each cycle how many new people do you spread to.
• Y is the number of cycles you can execute in a given time period.

If you have a cycle that spreads to 10 people, but takes 7 days to replicate, in 4 weeks you’ll have something that looks like 10^3.  However, if you have a cycle that takes a day to replicate, even with a branching factor of 3 you’ll have 3^27.  Which would you rather have?

In real life, there is decay of different viral messages.  Branching factors can drop below 1.  The path to success is typically the combination of a high branching factor combined with a fast cycle time.

As per the last blog post, different platforms and traffic channels have different engagement patterns and implicit cycle times.  The fact that people check email and social feeds multiple times per day makes them excellent vectors for viral messages.  Unfortunately, the channels with the fastest cycle times also tend to have the fastest decay rates.  Fast cycle times plus temporary viral factors above 1 are how sites and features explode out of no where.

Executing on Product Virality

To design virality into your product, there really is a three step process:

1. Clearly articulate and design out the features where members can touch non-members.  Wireframes and flows are sufficient.  Personally, I also recommend producing a simple mathematical model with some assumptions at each conversion point to sanity check that your product will produce a strong viral factor, layered over other traffic sources (the multiplier).
2. Instrument those flows with the detailed metrics necessary for each step of the viral cycle to match your model.
3. Develop, release, measure, iterate.  You may hit success your first time, but it’s not unusual to have to iterate 6-8 times to really get a strong viral factor under the best of conditions.  This is the place where the length of your product cycles matter.  Release an iteration every 2 days, and you might have success in 2 weeks.  Take 3-4 weeks per iteration, and it could be half a year before you nail your cycle.  Speed matters.

You don’t need hundreds of viral features to succeed.  In fact, most great social products only have a few that matter.

What about mobile?

Now that we’ve covered the five scalable sources of web traffic and the basics of viral factors, we’ll conclude next week with an analysis of what this framework implies for driving distribution for mobile web sites vs. native applications.

The topic of this blog post may seem simplistic to those of you who have been in the trenches, working hard to grow visits and visitors to your site or application.  As basic as it sounds, however, it’s always surprising to me how valuable it is to think critically about exactly how people will discover your product.

In fact, it’s really quite simple.  There are only really five ways that people will visit your site on the web.

The Five Sources of Traffic

With all due apologies to Michael Porter, knowing the five sources of traffic to your site will likely be more important to your survival than the traditional five forces.  They are:

1. Organic
2. Email
3. Search (SEO)
4. Ads / Partnerships (SEM)
5. Social (Feeds)

That’s  it.  If someone found your site, you can bet it happened in those five ways.

The fact that there are so few ways for traffic to reach your site at scale is both terrifying and exhilarating.  It’s terrifying because it makes you realize how few bullets there really are in your gun.  It’s exhilarating, however, because it can focus a small team on exactly which battles they need to win the war.

Organic Traffic

Organic traffic is generally the most valuable type of traffic you can acquire.  It is defined as visits that come straight to your site, with full intent.  Literally, people have bookmarked you or type your domain into their browser.  That full intent comes through in almost every produto metric.  They do more, click more, buy more, visit more, etc.  This traffic has the fewest dependencies on other sites or services?

The problem with organic traffic is that no one really knows how to generate more of it.  Put a product manager in charge of “moving organic traffic up” and you’ll see the fear in their eyes.  The truth is, organic traffic is a mix of brand, exposure, repetition, and precious space in the very limited space called “top of mind”.  I love word of mouth, and it’s amazing when it happens, but Don Draper has been convincing people that he knows how to generate it for half a century.

(I will note that native mobile applications have changed this dynamic, but will leave the detail for the third post in this series.)

Email Traffic

Everyone complains about the flood of email, but unfortunately, it seems unlikely to get better anytime soon.  Why?  Because it works.

One of the most scalable ways for traffic to find your site is through email.  Please note, I’m not talking about direct marketing emails.  I’m referring to product emails, email built into the interaction of a site.  A great example is the original “You’ve been outbid!” email that brought (and still brings) millions back to the eBay site every day.

Email scales, and it’s inherently personal in its best form.  It’s asynchronous, it can support rich content, and it can be rapidly A/B tested and optimized across an amazing number of dimensions.  The best product emails get excellent conversion rates, in fact, the social web has led to the discovery that person to person communication gets conversion person over 10x higher than traditional product emails.  The Year In Review email at LinkedIn actually received clickthroughs so high, it was better described as clicks-per-email!

The problem with email traffic generally is that it’s highly transactional, so converting that visit to something more than a one-action stop is significant. However, because you control the user experience of the origination the visit, you have a lot of opportunity to make it great.

Search Traffic

The realization that natural search can drive traffic to a website dates back to the 90s.  However, it really has been in the past decade in the shadow of Google that search engine optimization scaled to its massive current footprint.

Search clearly scales.  The problem really is that everyone figured this out a long time ago.  First, that means that you are competing with trillions of web pages across billions of queries.  You need to have unique, valuable content measured in the millions of pages to reach scale.  SEO has become a product and technical discipline all it’s own. Second, the platform you are optimizing for (Google, Microsoft) is unstable, as they constantly are in an arms race with the thousands of businesses trying to hijack that traffic. (I’m not even going to get into their own conflicts of interest.)

Search is big, and when you hit it, it will put an inflection point in your curve.  But there is rarely anysuch thing as “low hanging fruit” in this domain.

Advertising (SEM)

The fourth source of traffic is paid traffic, most commonly now ads purchased on Google or Facebook.  Companies spend billions every year on these ads, and those dollars drive billions of visits.  When I left eBay, they were spending nearly $250M a year on search advertising, so you can’t say it doesn’t scale.

The problem with advertising is really around two key economic negatives.  The first is cash flow.  In most cases, you’ll be forced to pay for your ads long before you realize the economic gains on your site.  Take something cash flow negative and scale it, and you will have problems.  Second, you have solid economics.  Most sites conjure a “lifetime value of a user” long before they have definitive proof of that value, let alone evidence that users acquired through advertising will behave the same way. It’s a hyper-competitive market, armed with weapons of mass destruction.  A dangerous cocktail, indeed.

While ads are generally the wrong way to source traffic for a modern social service, there are exceptions when the economics are solid and a certain volume of traffic is needed in a short time span to catalyze a network effect.  Zynga exemplified this thinking best when it used Facebook ads to turbocharge adoption and virality of their earlier games like FarmVille.

Social Traffic

The newest source of scalable traffic, social platforms like Facebook, LinkedIn and Twitter can be great way to reach users.  Each platform is different in content expectations, clickthrough and intent, but there is no question that social platforms are massively valuable as potential sources of traffic.

Social feeds have a number of elements in common with email, when done properly.  However, there are two key differences that make social still very difficult for most product teams to effectively use at scale.  The first is permission.  On social platforms, your application is always speaking through a user.  As a result, their intent, their voice, and their identity on the platform is incredibly important.  Unlike email, scaling social feed interactions means hitting a mixture of emotion and timing.  The second issue is one of conversion.  With email, you control an incredible number of variables: content, timing, frequency.  You also have a relatively high metrics around open rates, conversion, etc.  With social feeds, the dynamics around timing and graph density really matter, and in general it always feels harder to control.

The Power of Five

Eventually, at scale, your site will likely need to leverage all of the above traffic sources to hit its potential.  However, in the beginning, it’s often a thoughtful, deep success with just one of these that will represent your first inflection point.

The key to exponential, scalable distribution across these sources of traffic is often linked to virality, which is why that will be the topic of my next post.

As an engineer and designer by training, I didn’t always put this level of focus on traffic acquisition.  It wasn’t until we tried to build an entirely new site under the eBay brand (eBay Express) that I was forced to focus our team’s efforts on one large fundamental challenge: traffic acquisition.

Those struggles, some successful (and some not) led me to appreciate how profoundly the social web changed the metrics of distribution.  When we founded the growth team at LinkedIn in 2008, we were able to structure our thinking around user acquisition, measure it, and bend the curve significantly for the site. 

A special thanks to both Reid Hoffman and Elliot Shmukler, who both contributed significantly to my thinking on the subject.

History is Written by the Victors

History is written by the victors, and on the consumer web, victory is often defined by market distribution.  Growth does not just happen, it has to be designed into your product and service.

The following posts attempt to capture some of the fundamentals that I’ve personally found useful to structure thinking around social user acquisition, and extend those concepts from the web to mobile applications:

• The Five Sources of Traffic
• Viral Factor Basics
• Mobile Web vs. Mobile Application

Remember, Product Leaders win games.  Now let’s get started.

It may sound trivial, but making a great green beer is surprisingly delightful.  Throw in a leprechaun hat, some Irish whiskey, and a warm afternoon, and you’ve got yourself a party.

Step 1: The Beer

We tried quite a few varieties, but what you are really looking for is a bright, vibrant yellow color to start with.   Most people were happiest with Corona, although Beck’s was also popular.  Wheat beers tend to be too cloudy, and anything darker tends to look swampy.

(Listen, I know Corona doesn’t scream Irish, but we’re going for effect here.)

Step 2: Supplies

Before you can have your event, you need to assemble the following:

• Case(s) of beer.  Theoretically could get a keg, but our parties were never that big.
• Bottle openers.
• Clear, 16 ounce plastic cups.
• Green food coloring, liquid.

Step 3: The Process

The workflow is simple, but this detail is important.

1. Put two (not one, not three) drops of food coloring in the bottom of a cup
2. Open the beer
3. Pour liberally, to get good mixing and a bit of a head

That’s it.  The magic is that you get almost perfect color distribution pouring the beyou over the food coloring.  Adding the food coloring afterward, eve with stirring, is a giant fail.

The Results

Happy St. Patrick’s Day!

This is going to be a short post, but given the attention and page views that my posts on Quicken 2007 received, I thought this update worthwhile.

Previous Posts

• Proposed Solution: Quicken 2007 & Mac OS X Lion
• Final Solution: Quicken 2007 & Mac OS X Lion

Quicken 2007 for Mac OS X Lion Arrives

Last week, Intuit announced the availability of an anachronism: Quicken 2007 for Mac OS X Lion.  It sounds odd at first, given that we should really be talking about Quicken 2013 right about now, but it’s not a misprint.  This is Quicken 2007, magically enabled to actually load and run on Mac OS X Lion.  It’s like Intuit cloned a Wooly Mammoth, and put it in the New York Zoo.

The good news is that the software works as advertised.  I have a huge file, with data going back to 1994.  However, not only did it operate on the file seamlessly, the speed improvement over running it on a Mac Mini running Mac OS X Snow Leopard is significant.  Granted, my 8-core iMac likely explains that difference (and more), but the end result is the same.  Quicken.  Fast.  Functional.  Finally.

There are small bugs.  For example, some dialogs seems to have lost the ability to resize, or columns cannot be modified.  But very small issues.

Where is it, anyway?

If you go to the Intuit website, you’ll have a very hard time finding this product:

• It’s not listed on the homepage
• It’s not listed on the products page
• It’s not listed on the page for Quicken for Mac
• It’s not listed in the customer support documents (to my knowledge)
• It doesn’t come up in site search

However, if you want to pay $14.95 for this little piece of magic (and given the comments on my previous posts, quite a few people will), then you can find it here:

• Download Quicken 2007 for Mac OS X Lion

Goodbye, Mac Mini

I have it on good authority that Intuit is working on adding the relevant & required investment functionality to Quicken Essentials for Mac to make it a true personal finance solution.  There is a lot of energy on the Intuit consumer team these days thanks to the infusion of the Mint.com team, and I’m optimistic that we’ll see a true fully features personal finance client based on the Cocoa-native Quicken Essentials eventually.

Context & Caveats

This talk is based substantially on a lecture I gave at LinkedIn on August 31, 2011.  It’s heavily based on the unique product, strategy and organizational issues that you see currently in fast moving, hyper growth, consumer-focused software companies.

At the same time, many of the higher level business and management issues discussed are fairly universal, so hopefully there is something useful here for anyone who is passionate about building organizations that build great products.

So take a look, and I look forward to the comments.  FWIW The Optimus Prime quotes are from this excellent list of Optimus Prime quotes for the workplace.

Be A Great Product Leader

To scale a great team, however, you need more than just a list of roles and responsibilities. How you onboard new talent is as important for the long term health of your team as how you identify and hire them in the first place.

The Trials of Being a New Coach

When a sports team gets a new coach, there is some authority that comes with the role. You can immediately set standards for behavior & strategy – how the team is going to practice, what plays the team is going to run. That authority, however, tends to be short -lived. Before you know it, the team begins to focus on one thing: are we winning games?

Joining a new team as a product manager has the same dynamic. At most of the companies I’ve been a part of, there is this false sense of security that comes from process and organization. Sure, if you are technically fulfilling the role and responsibilities of a product manager, there is a certain amount of respect and authority initially. However, in the long term, teams want to win games, and in software that means products that people are proud of and products that move the needle.

So is there a pattern of behavior for new product managers that ensures long term success? I’ll argue yes, and for my new hires I boil it down to three phases:
2 weeks, 2 months, and 2 quarters.

Two Weeks

The first two weeks of a product manager are critical, because this is the window where a new leader can establish the most important aspect of the role: what game are we playing, and how do we keep score.

As a result, the first thing I lay out for new product manager is:

• The company culture and organizational philosophy of the team. Why the company matters. Product/engineering partnership. Results oriented performance.
• The current strategic frame for how their product fits into the overall strategy of the company.
• The current metrics and milestones for the product they are taking over.
• A set of frameworks for the roles & responsibilities of product managers. These include posts on being a great product leader, product prioritization, finding heat in design, etc.

In the first two weeks, a new product manager is expected to:

• Thoroughly challenge and finalize the strategic frame for the area. Does the existing frame make sense, or is there a better game to be playing?
• Thoroughly understand the existing product metrics, and identify new or different metrics needed to properly assess the success of the area (max: 3)
• Reprioritize all existing and future ideas & concepts based on the above, a.k.a. the product roadmap.

In addition, the first two weeks is the time when a new product manager can physically sit down and meet all the other key product and engineering leaders in overlapping areas, to help them both have context for their product and more importantly establish communication channels across the company with other key leaders. Great product managers very often serve as efficient people routers, and knowing who to talk to is often as important as knowing what to do.

Two Months

Like medicine, theoretical knowledge will only get you so far as a product manager. At some point, you learn by doing. A team will tolerate theoretical discussion for a short while, but in the end, a new product manager needs to get their hands dirty.

Two months is too short a time to significantly move the needle, but it is enough time to run through a few release cycles. In the first two months, it’s crucial for a product manager to actually be responsible for something released to users. In addition, the first two months is the typical time frame for a new product manager to flesh out the “best idea” from the team on how to win.

Two months is enough time to:

• Have identified key outstanding bugs or minor feature fixes that matter.
• Led the design / specification of solutions to those issues, and see them go live.
• Write their first product specification for a larger, more significant milestone for their area. This should be their highest priority project to “move the needle” as they’ve defined it for the team.

The first two months are crucial, because not only does it help the new team execute together and coalesce, but also put their stake in the ground on what their next big evolution will be. By leading the effort to place that bet, a product manager sets the team up for the type of success that hopefully will provide long term momentum for that product team.

Two Quarters

Six months is the window to get a cross-functional team into the positive, reinforcing cycle of ongoing success. At this point, the team has released both small and large features, and has meaningfully “moved the needle.”

This doesn’t mean, by the way, that the product manager led the launch of a single, monolithic all-or-nothing feature. In fact, what it most likely means is that the team launched a combination of iterative efforts to test out their theories and push through changes that in the aggregate validated the strategy and prioritization that had been put in place.

Great Product Leaders Win Games

Once teams have victories under their belt, in hyper-growth companies they gain both the desire to win again, and the confidence to execute on that desire. Creating that momentum is one of the hardest, and yet most valuable elements of cross-functional leadership.

This pattern has proven reliably consistent for my own product leadership efforts, as well as in differentiating the long term success of product managers I’ve hired and mentored.

In some ways, it’s really simple: great teams like winning, and great leaders reliably lead teams to great victories.

Now go out and win games.

The AppleTV 2 Blinking White Light of Death

Problem is simple: Your AppleTV 2 has a blinking white LED that never stops, and all it displays on the TV is an image instructing you to connect the device to iTunes.

Cause: Most likely, you interfered with a firmware update. In my case,  I had selected an option on my AppleTV 2 to update its firmware.  However, before it was complete, the power to the device was cut.

Mission: Find a Micro USB Cable

I didn’t realize it was possible to physically connect your AppleTV 2 to your computer.  This blog post was my first clue on what had caused my issue, and how to solve it.  Unfortunately, it sounded like he never was able to solve the problem directly.

It’s a bit strange that Apple decided to put a Micro USB port on the AppleTV 2.  However, after reading this support article on the Apple website, I was determined to try to fix it myself.

Finding a Micro USB cable turned out to be non-trivial.  To the casual observer, the Micro USB and the Mini USB look very similar.  The Mini USB is used by Blackerries, hard drives, and countless devices.  The Micro USB port is a bit smaller, flatter, and more oval.

Apple actually does not carry the cable in store, although you can get one online.  The trick was finding a device that uses the Micro USB.  In my case, I found them stocked next to the Sony eReader.

iTunes Saves the Day

I plugged the new Micro USB cable into a powered USB 2.0 hub.  Given some of the issues reported by others, I suspect that it’s possible that the power draw of the AppleTV might be a bit more than typical USB ports can handle.  In any case, the Apple TV showed up in iTunes 10.5.x.  I clicked the “Restore” button, and a couple of minutes later it was done.

No issues at all with the device – it was literally reset to a factory clean state.

Since an overwhelming number of support articles and comments I found online suggested that this didn’t or wouldn’t work, I thought I’d put this blog post out there.  Hopefully it will help someone in their hour of need.

Of course, being who I am, I went home and built a spreadsheet to recalculate what would have happened if Dow Jones had decided to add Apple to the index instead of Cisco back in 2009.  Imagine my surprise to see that the Dow be over 2000 points higher.

In real life, the Dow closed at 12,874.04 on Feb 13, 2012.  However, if they had added Apple instead of Cisco, the Dow Jones would be at 14,926.95.  That’s over 800 points higher than the all-time high of 14,164 previously set on 4/7/2008.

Can you imagine what the daily financial news of this country would be if every day the Dow Jones was hitting an all-time high?  How would it change the tone of our politics? Would we all be counting the moments to Dow 15,000?

Why Cisco vs. Apple?

This isn’t a foolhardy exercise.  The Dow Jones Industrial Average is changed very rarely, in order to promote stability and comparability in the index.  However, on June 8, 2009, they made two changes to the index:

• They replaced Citigroup with Travelers
• They replaced General Motors with Cisco

The question I explored was simple – what would have happened if they had replaced General Motors with Apple on June 8, 2009.  After all, Apple was up over 80% off its lows post-crash.  The company had a large, but not overwhelming market capitalization.  The index is already filled with “big iron” tech stocks, like Intel, HP & IBM.  Why add Cisco?  Why not add a consumer tech name instead?

In fact, there is no readily obvious justification for adding Cisco to the index in 2009 instead of Apple.

The Basics of the Dow Jones Industrial Average

Look, I’m just going to say it. The Dow Jones Industrial Average is ridiculous.

You may not realize this, but the Dow Jones Industrial Average, the “Dow” that everyone quotes as representative of the US stock market, and sometimes even a barometer of the US economy, is a mathematical farce.

Just thirty stocks, hand picked by committee by Dow Jones, with no rigorous requirements.  Worse, it’s a “price-weighted” index, which is mathematically nonsensical.  When calculating the Dow Jones Industrial Average, they take the actual stock prices of each stock, add them together, and divide them by a “Dow Divisor“.  They don’t take into account how many shares outstanding; they don’t assess the market capitalization of each company.  When a stock splits, they actually change the divisor for the whole index.  It’s completely unclear what this index is designed to measure, other than financial illiteracy.

In fact, there is only one justification for the Dow Jones Industrial Average being calculated this way.  Dow Jones explains it in this post on why Apple & Google are not included in the index.  To save you some time, I’ll summarize: they have always done it this way, and if they change it, then they won’t be able to compare today’s nonsensical index to the nonsensical index from the last 100+ years.

So what? Does it really matter?

It’s a fair critique.  Look, with 20/20 hindsight, there are limitless number of changes we could make to the index to change its value.  Imagine adding Microsoft and Intel to the index in 1991 instead of 1999?

I don’t think this exercise is that trivial in this case.  The Dow already decided to make a change in 2009.  They decided to replace a manufacturing company (GM) with a large hardware technology company (CSCO).  They could have easily picked Apple instead.

The end result?  People talk about the stock market still being “significantly off its highs” of 2008.  In truth, no one should be reporting the value of the Dow Jones Industrial Average.  But they do, and therefore it matters.  As a result, the choices of the Dow Jones committee matter, and unfortunately, there seems to be no accountability for those choices.

Appendix: The Numbers

I’ve provided below the actual tables used for my calculations.  Please note that all security prices are calculated as of market close on Monday, Feb 13, 2012.  The new Dow Divisor for the alternate reality with AAPL in the index was calculated by recalculating the appropriate Dow Divisor for the 6/8/2009 switch of AAPL for CSCO, and a recalculated adjustment for the VZ spinoff on 7/2/2010.

Calculating the “alternate divisor” requires getting the daily stock quotes for the days where the index changed, and recalculating to make sure that the new divisor with the new stocks gives the same price for the day. It’s a bit messy, and depends on public quote data, so please feel free to check my math if I made a mistake.

As I have a passion for finding a more human understanding for what drives engagement in real life and then mapping it to online behavior, I think the use of the term “expertise” here is misleading.  Instead, I believe what we are seeing is an explosion of activity around an incredibly powerful form of identity and reputation: the identity of taste.

Expertise is Empirical

If you go to LinkedIn, you see a site that is rich with the identity of expertise.  LinkedIn has rich structured data around sources of expertise: degrees, schools, companies, titles, patents, published content, skills.  They also have rich sources of unstructured content about job responsibilities, specialties, questions & answers, group participation, status updates and comments.  There are even implicit indications of expertise related to other online identities (like Twitter) and relationships to other people with expertise (connections).

This expertise can be tapped by using LinkedIn’s incredibly powerful search engine, either on site or via API, or by browsing the talent graph displayed in catalog form on LinkedIn Skills.  Github has created a powerful identity for developers based on their actual interests and contributions in code.  Blogs, Tumblr, Quora and Twitter have helped people create identities based on the content they create and share.

The power of identity based on expertise is that it is concretely demonstrated.  Education, experience, content and relationships are all very structured and concrete methods for measuring and assessing expertise.  However, in some ways, expertise is limited by it’s literal nature.  Factual. Demonstrable. Empirical.

Taste is Inspiring

Pinterest, however, has unlocked an incredibly powerful form of reputation and identity that exists in the offline world – an identity of taste.  People don’t care about the expertise of people who are assembling pinboards.  They care about how those combinations make them feel – the concept, the aggregation, the flow of additions.  The Pinboard graph begins for most people with their friends, but people quickly learn to hop based on sources to people they don’t know, finding beautiful, interesting, intriguing or inspiring collections of images.

This isn’t an identity based on expertise, really.  It’s not even clear how closely related it is to a graph of interests. Curation-based social platforms evoke a different phenomenon, and with it, some very powerful emotions and social behaviors.

Taste is different than expertise.  Taste does not imply that you are a good person or a deep well of expertise on the domain.  Taste is not universal, although there are certainly those with a predilection for influencing and/or predicting the changes in taste for many.  But when we as human beings find people whose taste inspires us, it’s a powerful relationship.  We map positive attributes to them, ranging from kindness to intelligence to even authority.  Fame & taste are often intertwined.

You Are What You Curate

Curation-based social platforms are based on the interaction of three key factors:

1. A rich, visual identity and reputation based on curated content
2. An asymmetric graph based on not only following people, but specific feeds of curated content
3. A rich, visual activity stream of curation activity

It’s the first item that I seem to see most under-appreciated.  Vanity, as one of the most common deadly sins in social software, drives an incredible amount of engagement and activity.  As people are inspired by those who create beautiful identities of curated content, they also become keenly aware of how their curated identity looks.  When people signal an appreciation for their taste, it triggers power social impulses, likely built up at an early age.

This, more than anything else, reflects the major step function in engagement of this generation of curation over previous attempts (anyone remember Amazon Lists?)

How Does Taste Factor into Your Experience?

I always like to translate these insights into actionable questions for product designers.  In this case, these are some good starting points:

• How does taste factor into your experience?
• Is the identity in your product better served by reputation based on taste or expertise?
• Are the relationships in your product between users based on taste or expertise?
• Are you creating an identity visually and emotionally powerful enough to trigger curation activity?
• Are you flowing curation activity through your experience in a way that stimulates discovery and the creation of an identity of taste?

Don’t underestimate the power of good taste.

Here’s an excerpt:

London Olympic Stadium holds 80,000 people. This blog was viewed about 460,000 times in 2011. If it were competing at London Olympic Stadium, it would take about 6 sold-out events for that many people to see it.

Click here to see the complete report.