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Viral Marketing Math Projections

Let’s kick off our section on Viral Marketing Projections with a basic formula. Because while predicting the impact your viral campaigns have over time can be a challenge, don’t worry, I’m going to break it down to its simplest forms. By the end, you’ll hopefully have a strong understanding of how by taking a peek into the future, you can better help drive the value of your business.

But before we get ahead of ourselves, let’s take a quick detour into the past.

Looking for a Formula for Viral Growth?

 

In previous chapters, I’ve given you the basic formula for calculating K, which is your most basic measure of potential viral magnitude. We’ve also gone over how to use K to calculate your amplification factor and improve your branching factor. As well as examined how architecting your product specifically for virality is the one true way to succeed.

We’ve also talked about viral cycle time, and how the amount of time necessary to complete your viral loop is the single biggest factor in determining your growth over time.

Now that we’ve gone through some of these more advanced fundamentals – let me give you the most basic equation that will allow you to project the impact of virality over a fixed period of time as it pertains to your user base.

In other words, I’m about to give you a secret formula for looking into your viral future. But don’t go running off to your local bookie quite yet.

This won’t be the full formula for calculating viral growth over time. We’re building towards that. Stay with me and we’ll get there.

This may seem complex. But if you take a few minutes to understand things, and drop the formula I’m about to give you into a spreadsheet to make for more practical use, you’ll make your life a heck of a lot easier as we move forward.

Are you ready?

Get your math pants on boys and girls.

A Basic Projection Formula for Viral Growth Over Time

 

Viral Growth Formula - Viral Hero Marketing

Let’s start by defining a few variables. Some you already know, and some we haven’t yet used:

  • The fixed period of time you’re analyzing = t
  • Your user growth over a define period of time = u(t)
  • The users you start the process with, or the first users you seed into a new viral engine = u(0)
  • The number of invites users send out over a fixed period = i
  • The awareness-to-action conversion rate on the invites users send out = conv%
  • The most basic measure of viral magnitude is your viral factor, and it comes from multiplying i by conv%. This will = K
  • The amount of time that elapses from the moment a prospective user becomes aware of your product until the moment they send their first invite, measured in days as a decimal = ct

Here’s the formula for projecting viral user growth over a fixed period of time:

u(t) = u(0) * (K^(t/ct + 1) – 1) / (K – 1)

This may appear a bit complex at first, but you do NOT need to commit this formula to memory. You only need to know it long enough to create a formula in a spreadsheet tool or write a function in a programming language so you can simply drop in your variable values as measured by your analytics tools.

Then you’re good to go.

Tap Into Your Full Exponential Potential

 

Something important to keep in mind that we talked about in a prior chapter:

  • Since K is raised to the power of t/ct, reducing ct has a FAR more profound effect on viral growth over time than increasing K will.

When viral cycle time is shorter, growth becomes more explosive.

This is one of the many reasons that companies who pay very little attention to their viral loops have had their growth trajectory held hostage by how much exposure they can buy through non-viral marketing efforts.

It’s also why YouTube exploded at a faster rate than any other company anyone had ever seen before. They wanted to create a service that allowed users to easily stream and share videos without the headache of downloading or sending files. Thus they built virality deep into the bones of their product offering. (If you’re interested in learning exactly how YouTube did this, I go more in-depth in a prior chapter.)

With this focus, YouTube built their product in such a way that their cycle time was a little over 2 minutes on average. This gave users the mathematical capacity to complete over 650 viral loops in a single day. While this would never realistically happen for a single user, with each viral loop that DID occur, more and more people were exposed to the product and sent invites of their own.

I’ll save you the obligatory “focus on cycle time, then optimize K” soap box for now. You’ve heard it before.

Besides, now that you’ve gotten the basic formula from above AND you’ve dropped it into a spreadsheet to help you project your own viral growth over time (you HAVE dropped this into a spreadsheet already, right?), I don’t think you’ll forget this advice any time soon.

What’s Next

 

In this chapter I only gave you the formula for VIRAL growth. We haven’t factored in non-viral marketing channels yet, so this still isn’t a projection formula for ALL growth.

We’ll get there. But first let’s factor in saturation, decay, and all the other peaks and valleys that come with a realistic upward trajectory.

 

Are You Taking Into Account All the Variations of Virality?

While we’re heading in the right direction, our formula is nowhere close to being a complete representation of the real world effects of virality. That is unless you live in a bubble. In which case go home Bubbly Boy, because we’ve got important business to take care of in our next chapter.

 

Travis Steffen
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Travis Steffen

Travis Steffen is a Silicon Valley growth engineer, data scientist, and serial entrepreneur with multiple exits. He currently serves as Head of Growth at AutoLotto. He's also a crazy adrenaline junkie, is obsessed with fantasy football, and can grill a mean rack of ribs.
Travis Steffen
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