User Acquisition: Cycle Time Matters

This is an extension to my original three post series on user acquisition.

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.

The Game Has Changed. Design for Passion.

One of the most exciting developments in software has been a resurgence in the focus and priority on design.  With the growing dominance of social platforms and mobile applications, more and more people are growing comfortable productively discussing and utilizing insights about human emotion in their work.

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? I don’t really like to talk about health mmainly becase I’ve had some bad experiences with hospitals, last month I had to report some hospital negligence claims, I went to the docotr and I was treated whihc so much disrespect I was humiliated so I prefer to leave health out of this.

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.

User Acquisition: Mobile Applications and the Mobile Web

This is the third post in a three post series on user acquisition.

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.

User Acquisition: Viral Factor Basics

This is the second post in a three post series on user acquisition.

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.

Lot-of-Rabbits

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.

User Acquisition: The Five Sources of Traffic

This is the first post in a three post series on user acquisition.

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.

Product Leaders: User Acquisition Series

I can be pedantic about user acquisition.  The truth is that consumer web and mobile applications are under increasing pressure to demonstrate explosive exponential traction.  Building a great product is no longer sufficient, lest you be left with the best product in the world that no one has discovered.

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:

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

Top 10 Product Leadership Lessons

On Sunday, I was fortunate enough to give a talk at the 9th annual Harvard Business School Entrepreneurship Conference.  I’m trying to be better about posting the slides from these talks as they happen.

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

Great Product Leaders Win Games

Being a great product leader is hard. Every organization and process is different, and in many cases you are responsible for the outcome without having the authority to enforce decisions. My recent blog post on Being a Great Product Leader was an attempt to capture the specifics of how to lead a great, cross-functional software team.

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.

Be a Great Product Leader

People who know me professionally know that I’m passionate about Product Management.  I truly believe that, done properly, a strong product leader acts as a force multiplier that can help a cross-functional team of great technologies and designers do their best work.

Unfortunately, the job description of a product manager tends to either be overly vague (you are responsible for the product) or overly specific (you write product specifications).  Neither, as it turns out, is it effective in helping people become great product managers.

I’ve spent a lot of time trying to figure out a way to communicate the value of a product manager in a way that both transparently tells cross-functional partners what they should expect (or demand) from their product leaders, and also communicates to new product managers what the actual expectations of their job are.  Over the years, I reduced that communication to just three sets of responsibilities: Strategy, Prioritization & Execution.

Responsibility #1: Product Strategy

They teach entire courses on strategy at top tier business schools.  I doubt, however, that you’ll hear Product Strategy discussed in this way in any of them.

Quite simply, it’s the product manager’s job to articulate two simple things:

  • What game are we playing?
  • How do we keep score?

Do these two things right, and all of a sudden a collection of brilliant individual contributors with talents in engineering, operations, quality, design and marketing will start running in the same direction.  Without it, no amount of prioritization or execution management will save you.  Building great software requires a variety of talents, and key innovative ideas can come from anywhere.  Clearly describing the game your playing and the metrics you use to judge success allows the team, independent of the product manager, to sort through different ideas and decide which ones are worth acting on.

Clearly defining what game you are playing includes your vision for the product, the value you provide your customer, and your differentiated advantage over competitors.  More importantly, however, is that it clearly articulates the way that your team is going to win in the market.  Assuming you pick your metrics appropriately, everyone on the team should have a clear idea of what winning means.

You should be able to ask any product manager who has been on the job for two weeks these questions, and get not just a crisp, but a compelling answer to these two questions.

The result: aligned effort, better motivation, innovative ideas, and products that move the needle.

Responsibility #2: Prioritization

Once the team knows what game they are playing and how to keep score, it tends to make prioritization much easier.  This is the second set of responsibilities for a product manager – ensuring that their initial work on their strategy and metrics is carried through to the phasing of projects / features to work on.

At any company with great talent, there will be a surplus of good ideas.  This actually doesn’t get better with scale, because as you add more people to a company they tend to bring even more ideas about what is and isn’t possible.  As a result, brutal prioritization is a fact of life.

The question isn’t what is the best list of ideas you can come up with for the business – the question is what are the next three things the team is going to execute on and nail.

Phasing is a crucial part of any entrepreneurial endeavor – most products and companies fail not for lack of great ideas, but based on mistaking which ones are critical to execute on first, and which can wait until later.

Personally, I don’t believe linear prioritization is effective in the long term.  I’ve written a separate post on product prioritization called The Three Buckets that explains the process that I advocate.

You should be able to ask any product manager who has been on the job for two weeks for a prioritized list of the projects their team is working on, with a clear rationale for prioritization that the entire team understands and supports.

Responsibility #3: Execution

Product managers, in practice, actually do hundreds of different things.

In the end, product managers ship, and that means that product managers cover whatever gaps in the process that need to be covered.  Sometimes they author content.  Sometimes they cover holes in design.  Sometimes they are QA.  Sometimes they do PR.  Anything that needs to be done to make the product successful they do, within the limits of human capability.

However, there are parts of execution that are massively important to the team, and without them, execution becomes extremely inefficient:

  • Product specification – the necessary level of detail to ensure clarity about what the team is building.
  • Edge case decisions – very often, unexpected and complicated edge cases come up.  Typically, the product manager is on the line to quickly triage those decisions for potentially ramifications to other parts of the product.
  • Project management – there are always expectations for time / benefit trade-offs with any feature.  A lot of these calls end up being forced during a production cycle, and the product manager has to be a couple steps ahead of potential issues to ensure that the final product strikes the right balance of time to market and success in the market.
  • Analytics – in the end, the team largely depends on the product manager to have run the numbers, and have the detail on what pieces of the feature are critical to hitting the goals for the feature.  They also expect the product manager to have a deep understanding of the performance of existing features (and competitor features), if any.

Make Things Happen

In the end, great product managers make things happen.  Reliably, and without fail, you can always tell when you’ve added a great product manager to a team versus a mediocre one, because very quickly things start happening.  Bug fixes and feature fixes start shipping.  Crisp analysis of the data appears.  Projects are re-prioritized.  And within short order, the key numbers start moving up and to the right.

Be a great product leader.

This work is licensed under a Creative Commons Attribution 3.0 Unported License.

Trend Micro Keynote: Innovation & Inspiration

I had the opportunity yesterday to kick off the 2011 Trend Micro Engineering Summit with a keynote on Innovation & Inspiration.  It’s a topic I’m passionate about, and I appreciated the chance to put some key learnings together and present them to a great technology team.

The talk is broken into three sections:

  • Lessons from Distributed Computing about how to think about Distributed Organizations
  • Three types of Risk
  • Hackdays and Cultures of Innovation

I would definitely consider the slides “draft” quality, but worth sharing nonetheless.

Those of you who attended by “Ten Things I Learned About Product at LinkedIn” talk will recognize the Optimus Prime quotes.  What can I say?  I’m a sucker for the Transformers. (I will get those slides posted up here soon.)

Enjoy.

 

Steve Jobs, BMW & eBay

There have been so many articles posted on Steve Jobs in the past week, I really thought I wasn’t going to add one here on my blog.

However, yesterday, John Lilly wrote a great piece on Steve Jobs yesterday, and I realized I might have a story worth telling after all.  I find myself fortunate, in retrospect, to have joined Apple in 1996 as an intern, and then full time in 1997 just weeks before Steve Jobs took the helm as interim CEO.

A Tale of Two Meetings

As an outgoing intern of the Advanced Technology Group, I actually did attend the meeting that John describes in his blog post.  However, as a full time engineer on WebObjects, I also had the opportunity to attend a different all hands that Steve Jobs called for the entire Rhapsody team (the codename of the project that became Mac OS X).

If you haven’t read John’s post, it’s definitely worth reading in tandem with this one.  He does a great job capturing the insights from the ATG meeting.  Instead, let me add to the story with my recollection of the Rhapsody meeting that happened the same week.

(Note: It has been over fourteen years since the meeting, so don’t take this as a literal play-by-play.  I have no notes, so all quotes are from memory.  But this is how I remember it.)

The “Michael Dell” Meeting

The mood of the Rhapsody team meeting was energetic, but mixed.  More than any other group at Apple, the Rhapsody team required a combination of talent from both long time Apple engineers and newly merged NeXT engineers.  There was a palpable sense of excitement in the room, as particularly the NeXT team had a huge amount of respect for the “incoming administration”.  At the same time, there was an element of discontent around suddenly finding themselves part of a large company, and even some skepticism that Apple was salvageable.

Steve got on stage at the front of the room in Infinite Loop 4, and put a huge, larger than life picture of Michael Dell on the wall.  He repeated the news fodder that Michael Dell had been asked recently what he would do if he was running Apple Computer.  (At the time, Dell was the ultimate success story in the PC industry.)  Dell said that he would liquidate the company and return the cash to shareholders.

A few gasps, a few jeers and some general murmuring in the audience.  But I don’t think they expected what he said next.

And you know what? He’s right.

The world doesn’t need another Dell or HP.  It doesn’t need another manufacturer of plain, beige, boring PCs.  If that’s all we’re going to do, then we should really pack up now.

But we’re lucky, because Apple has a purpose.  Unlike anyone in the industry, people want us to make products that they love.  In fact, more than love.  Our job is to make products that people lust for.  That’s what Apple is meant to be.

What’s BMW’s market share of the auto market?  Does anyone know?  Well, it’s less than 2%, but no one cares.  Why?  Because either you drive a BMW or you stare at the new one driving by.  If we do our job, we’ll make products that people lust after, and no one will care about our market share.

Apple is a start-up.  Granted, it’s a startup with $6B in revenue, but that can and will go in an instant.  If you are here for a cushy 9-to-5 job, then that’s OK, but you should go.  We’re going to make sure everyone has stock options, and that they are oriented towards the long term.  If you need a big salary and bonus, then that’s OK, but you should go.  This isn’t going to be that place.  There are plenty of companies like that in the Valley.  This is going to be hard work, possibly the hardest you’ve ever done.  But if we do it right, it’s going to be worth it.

He then clicked through to a giant bullseye overlayed on Michael Dell’s face.

I don’t care what Michael Dell thinks.  If we do our job, he’ll be wrong.  Let’s prove him wrong.

All I can remember is thinking: “Wow. Now that’s how you regroup, refocus and set a company in motion.”  I had seen speeches by Gil Amelio in 1996, and there was nothing comparable.  Please remember, at this point in time it wasn’t at all obvious that Steve or Apple would actually succeed. But I felt like I’d witnessed a little piece of history.

Fast Forward: eBay 2006

That meeting left a huge impression on me that extended well beyond Apple.  Steve’s actions and words at Apple in 1997 represented the absolute best in leadership for a turnaround situation.

It wasn’t until 2006, however, that I found myself at another large technology company looking to rediscover itself.  In the summer of 2006, I was one of a relatively small number of product leaders to tour a draft of a new initiative at eBay called “eBay 3.0”.  Led by the marketing team, a small, strong team had done a lot of research on what made eBay different, and what people wanted from the eBay brand.  The answer was that eBay was fun, full of serendipity, emotion, thrill.  The competition of auctions, the surprise at discovering something you didn’t know existed.  This reduced into a strong pitch for eBay as “colorful commerce”.

I was excited about the research and the work, because it echoed some of the things I remembered about Steve & Apple, and the simple vision he had for a company that made products that people lusted for.  But I also remember voicing a strong concern to several members of the team.  I told them about Steve’s speech to the Rhapsody team, and asked: “Does eBay want BMW market share, or Toyota market share?”  At the time, eBay was more than 20% of all e-commerce, and all plans oriented towards growing that market share.

Unfortunately, eBay tried to do both with the same product.

It’s not typical for a large, successful public company to basically say market share doesn’t matter, and to drive a company purely around a simple focus and vision.  When things are the toughest, unfortunately, that’s when leadership and vision matter the most.

Final Thoughts

Who would have imagined that Apple would have the largest market capitalization in the world?  Who would have thought that in the year 2011 that Apple – not Microsoft, not Dell, not Sony – would be defining the market for so many digital devices and services?

Most importantly, who would have thought that a leadership mandate that eschewed market share would achieve such dramatic gains?

Apple so easily could have gone the way of SGI, the way of Sun.  Instead, it literally shapes the future of the industry.  All because in 1997 Steve was able to offer a simple and compelling reason for Apple to exist.  A purpose.  And it’s a purpose that managed to aggregate some of the most talented people in the world to do some of their best work.  Again and again.

So I will add here a simple thank you to Steve Jobs for that meeting, and for changing the way that I think about every company’s purpose – their reason to exist.  Rest in Peace, Steve.

Joining Greylock

Today, John Lilly put up a really nice note on the Greylock Partners blog officially welcoming me to the firm.  Needless to say, I’m both honored and excited to be joining such a great team.

We’re fortunate to be witnessing the explosive growth of not one but two incredible new platforms for consumer products and services: social and mobile.  Both are literally changing the fundamental ways that consumers interact with devices, and are rapidly changing the dynamics for building successful new products and services.  After spending the past four years helping to build out social and mobile platforms, I can’t wait to partner with entrepreneurs to help them build out the next generation of products and companies over them.

Over the past few years, I’ve shared a number of insights here on this blog about building great products and companies.  Here are a few that are worth reading if you are curious about how I think:

And of course, the most appropriate for this announcement:

For now, I just want to say thank you to Reid, David, John and the entire Greylock team.  I can’t wait to get started.

Why T-Shirts Matter

During my tenure at LinkedIn, I’ve held a wide variety of roles and responsibilities within the company.  Some are fairly public (as described on my LinkedIn profile).  Others are the the type that you’d never find formally discussed, and yet would be no less true if you asked anyone who worked at the company.

In a rare combination of serendipity, passion, and empowerment, I personally ended up with one of those unspoken roles: the most prodigious producer of LinkedIn t-shirts.

2010 LinkedIn for Breast Cancer Awareness Shirt

At the recent Silicon Valley Comes to the UK trip, I had the chance to have a great conversation with Dave Hornik on why making t-shirts matter to high tech start-ups.   Believe it or not, I felt that this was a subject important enough to capture in a blog post.  (My friends from The Clothing People and I will write a separate blog post on how to make truly great high tech t-shirts, which is a field of expertise unto itself.)

Why T-Shirts Matter

At a high level, understanding the typical culture at a high tech startup can be difficult for those who haven’t worked for one.  The best analogy I can think of is to put yourself back in time, to when you were between 8 – 12 years old.  Now, think carefully about the things that 8 – 12 year old boys like (at least, the geeky ones).  Video games.  Caffeine.  e-scooter from this excellent guide.  Toys.  Computers. Bean bag chairs.  Junk food.  This should help orient you, and brings you to the right frame of mind about t-shirts.

T-shirts are a part of that culture.  In part, t-shirts represent the ultimate middle finger to those unnamed sources of authority who wanted software engineers to dress like “Thomas Anderson” in the Matrix.  Software engineers want to be Neo, not John Anderson.

This leads us to the reasons why t-shirts matter:

Empowerment.  In some ways, engineers delight in having found a profession where their intellect and passion for technology have enabled them to earn a great living and work at a company where – yes, you guessed it – they can wear t-shirts to work.  Giving out t-shirts tells your employees, implicitly, that you get it.  You hire only the best, and the best can wear whatever they want.  It says you know that you value merit over appearance; a working prototype over an MBA.

Incentives.  Over the past decade, behavioral finance has taught us that people don’t value money rationally – it varies depending on form and context.  You can bring a $20 bottle of wine to your girlfriend’s parents’ house and be thought a gentleman.  Handing her Mom a $20 at the door isn’t looked on the same way.   Let me just tell you, free t-shirts evoke some sort of primal response at a high tech company.  I’ve often said that I would see less interest at a high tech company handing out $100 bills than handing out free t-shirts.  High tech companies are filled with benefits that cost hundreds of thousands of dollars per year, benefit a minority of employees, and are generally under-appreciated financially.  You’d be shocked at what a $200 per person per year budget for t-shirts will do for employee morale comparatively.

Tribal Cohesion. There are a lot of reasons why many institutions require employees to wear uniforms.  Common appearance can be a reminder that the person represents the company.  More importantly, common dress signals who is “part of the tribe” and belongs to the corporate family.  Uniforms are incompatible with the “empowerment” aspect of how people want to dress, but t-shirts can represent a form of “voluntary uniform” if produced in sufficient variety and quantity.   This effect can be had at a team level, when a t-shirt is made just to celebrate a new product, or at the company level.  It has a profound effect on new hires, as well, who desperately want “a shirt” so they can fit in.  It may sound subversive, but t-shirts can provide many of the same benefits of camaraderie and tribal cohesion that uniforms did, without the top-down oppression.

Tenure Based Seniority. High tech companies are largely meritocratic, and as they grow they tend to define roles based on skills & experience rather than “time at the company”.  However, there are positive aspects to rewarding those who have “bled for the company” over the years, and put their hearts and souls into building the business.  T-Shirts, in an innocuous way, implicitly do this by almost always becoming “limited editions”.  Want the t-shirt from the 2007 company picnic?  You had to be there to get one.  How about the shirt from the first intern program?   The launch of a game-changing new product?  Even shirts that are given out to the whole company will become rare at a company that’s growing rapidly.  In a socially acceptable way, t-shirts subtlely communicate a form of tenure that is warm, and yet structured.

Branding.  As discussed under “Tribal Cohesion”, people want to wear the brand of their tribe.  They will wear them out everywhere if you let them.  Let them.  While being careful not to interfere with the uniqueness of shirts given to employees, make shirts for your developers, your fans, your early adopters.  Long before they become vocal advocates for your brand, they will gladly showcase it if you let them.  This tends to work best in relatively inter-connected, dense, techy cultures like Silicon Valley, but you’d be surprised how far your reach might be.  Of course, this assumes that you make shirts that don’t suck, but we’ll cover that in the next blog post.

So How Do I Make Great Shirts?

It turns out that this is a lot harder than it appears.  Mario always tells me my blog posts are too long, so I’m going to save this topic for the next post…

Rethinking IT as an HR Benefit

This has been something that I’ve been thinking about heavily for the past few years.  There is a trend in Silicon Valley that has been under-appreciated in the press, but nonetheless has rapidly swept through technology companies in the Bay Area. It may not be buzzword-enabled (yet), but it nonetheless may be a truly transformative event for our industry.

More and more companies seem to be thinking of IT as a human resources benefit.

(If your eyes just rolled back in your head, stay with me for a second.  This is a big deal.)

Historically, IT has been positioned as one of two things in the enterprise:

  1. Cost Center. In this model, IT technology and services are a required cost of doing business and being competitive, but don’t add any differentiation versus your competitors.  As a result, IT is managed by cost, and the goal is to provide “sufficient” productivity compared to other comparable companies at the lowest possible cost.  In this frame, every software purchase, every hardware purchase, every investment in training or personnel is evaluated based on price.
  2. Productivity. In this model, IT technology and services are seen as productivity enhancements, and potential differentiators.  Here, investments are made based on an Return on Investment (ROI) justification, where the benefits can include saving time and/or people, or potentially boosting output or revenue.  In this frame, there is a heavy bias towards technology that allows people to get more things done, more quickly, and with fewer errors.

Both of these models tend to heavily favor technology that is cheap.  What they don’t favor is technology that is enjoyable to use.   This has led to many decades of enterprise technology that is sold to decision makers at the top of the organization, and rolled out to reluctant employees who bear the brunt of the cost savings and/or potential productivity gains.

I had never considered that there might be a third model until a blog post about IT at Google surfaced in 2006.  [Note: I hope someone can find this URL for me – I’ve tried with no luck tonight].  This post wrote about how Google set up stations on every floor, with surplus batteries and machines to make swapping out faulty equipment a breeze.  It talked about giving employees a choice of platform to work on.  Most importantly, it talked about thinking about IT as an HR benefit.

IT as an HR Benefit

When you think about benefits in a human resources context, there is a very different frame of reference.  In business school, students who take incentives classes learn about different forms of compensation and their impact on psychology.  In theory, benefits need to justify their existence in some way beyond straight cash compensation.  Sometimes benefits are required because competitors offer them.  Sometimes benefits are offered because it’s cheaper, due to taxes or bulk purchasing power, for the company to buy them than the employee.  Benefits can be long term, or reward certain types of behavior.  In some cases, benefits are offered because people actually appreciate them more than the equivalent of cash.

In most companies, while benefits are in the end a cost center, they are factored into the general budget and philosophy around compensation of employees.  As a result, more often than not, benefits tend to compete with each other.  Given a compensation budget, what percentage of dollars will be spent on salaries vs. bonus vs. benefits?  Would employees prefer a 401k match or transportation vouchers?  Charitable contribution matches or gym discounts?  Who benefits from each program, and how much?  Will the benefit help with recruiting new employees, or with employee satisfaction and retention?

When framed as an HR benefit, IT comes under a whole different light.  Consider:

  • What percentage of your employees time is spent in front of a computer?
  • What is the relative cost of newer, more enjoyable technology over the “base model”?
  • How much would an employee appreciate dollars spent on IT technology vs. other benefits?
  • How does your technology affect your internal corporate culture?

These are very different questions than the ones that tend to drive historical cost-driven IT decision making.

In this model, you might get everyone a 24″ flat panel monitor instead of a 20″ monitor.   Why?  Because as a benefit, this might only cost $50 per employee per year, and they would appreciate it far more than the dollars themselves.   And they would appreciate it for hours every single day.  In fact, they might want to stay at work longer to use it compared to the machine they have at home.

In this model, you might give everyone the choice of mobile device (Blackberry, iPhone, Android, etc).  Of course, it would cost more in software support and development, but allowing employees to use the device of their choice might be appreciated every single day.  It also might make them a little more reluctant to consider working in an environment where they are forced to use a less-preferred platform.

LinkedIn

At LinkedIn, our IT department provides a wide range of choices, which we actually advertise on job postings:

  • Choice between Mac or Windows environment
  • Choice between laptop or workstation
  • Choice between two 24″ displays or a single 30″ display
  • Choice between iPhone or Blackberry

Do these technologies boost productivity?  Absolutely.  Do these technologies cost more than a homogenous, lowest-cost environment?  Absolutely.

But when you look at this list, it’s hard not to see them as benefits.  I see new employees every day, almost giddy when they first get their first laptop and 30″ display, or a tower with 24GB of RAM.  I hear people with guests at lunch brag about how LinkedIn lets you have an iPhone or a Blackberry.

Many of these employees spend anywhere from 4 to 10 hours with this equipment every day – is it any wonder that they perceive these as benefits?

Thoughts for the Industry

The question I have is, how pervasive is this trend?   For most office workers, any computer offers sufficient speed and available software.  In the consumer market, with the resurgence of design-based thinking, we’re seeing more products and profits driven by quality of the experience rather than quantitative metrics or feature checklists.  Will it spread to the enterprise?   Will employees demand it?

Many great professionals that I know in IT long to provide better products and services to their fellow employees.  Maybe this is the opportunity for IT & HR professionals to work together to reframe the way we justify technology at work.