Month: April 2012

Goodbye, Newton

/ Adam Nash / 5 Comments

Today, we had to say goodbye to a very special member of our family, Newton Nash.

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.

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User Acquisition: Mobile Applications and the Mobile Web

/ Adam Nash / 8 Comments

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

/ Adam Nash / 18 Comments

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.