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Calculate Viral Factor Coefficient

If you’re as big a fan of the latest and greatest tech talks as I am, or you do any combination of reading books and blogs, attending growth and marketing conferences, talking to other founders and growth engineers, and hanging out with anthropomorphic panda bears who occasionally wear capes, you’ve probably heard the buzzword “viral coefficient.

However, most people who throw this term around never actually bother explaining:

  • What is a Viral Coefficient
  • How do you calculate a Viral Coefficient, or
  • What kind of an impact can a Viral Coefficient have

Lucky for you, this big “secret” is about to be revealed.

Granted, no one in the history of words has ever enjoyed hearing the word “coefficient.” In fact, its mere utterance is usually enough to send people running in the other direction, or instantly fall asleep. Which is probably why viral coefficient is just as commonly referred to as the “viral factor.”

You have to admit that sounds way cooler, and could very easily be the name of a popular TV game show hosted by Wayne Brady.

Do you have . . . the VIRAL FACTOR! Let’s play to find out!

Basic Viral Marketing Math

 

Your viral factor tells you to what degree your users will power your growth by inviting others to try your product.

While it would be a bit more intuitive to name this variable V (which I almost did – as you can see in our jazzy little panda art above), since the majority of existing resources label this variable as K, let’s adopt K as our variable here so other past or future resources make sense to you.

Your viral factor = K

(See, I told you this would be basic math. But wait, I think I can make it a little more confusing for all you viral nerds out there.)

To elaborate more, K is needed to calculate the average number of new prospective users each existing user will successfully bring back to your site or app to enter your viral loop. In other words, K is a measure of the magnitude of virality your site or app possesses on a per-user basis.

Not quite getting it yet? Hang in there.

No Sharks Here

Let’s say K = 0.5.

This means for every user you recruit via non-viral means, that user will bring 0.5 prospective users into your viral loop for you.

Wait . . . a half a user? I still don’t get it. That makes no sense. Did the other half get eaten by a shark or something?

No Sharks Allowed Sign - Viral Factor Marketing

Nope, no sharks here.

Let’s try a different way of explaining this. When K = 0.5, it means for every TWO users you recruit via non-viral means, they’ll collectively bring ONE prospective user into your viral loop for you.

Make sense? Now instead of 0.5, what if K = 2.0?

This means those SAME two users you acquired via non-viral means will now bring you FOUR prospective users into your viral loop.

And that’s where sh*t gets crazy.

How to Calculate Your Viral Factor (aka K)

 

K is made up of two smaller KPIs:

  • The total number of invites sent out per user on average during one cycle of a viral loop. Let’s call this i.
  • The conversion rate on those invites (or the percentage of those invites sent that result in a new prospective user coming to your site and starting a new viral loop). Let’s call this conv%.

K = i * conv%

Viral Factor Coefficient Equation - Conversion Marketing

As you start to think about this, you’ll inevitably want to factor in time. So it’s worth noting that K is typically calculated over a fixed time period, such as one month. Don’t use an average i value from the last 90 days with an average conv% of the last 2 weeks. That’s just silly.

As you optimize, conv% should eventually become relatively stable (unless you experience heavy seasonality). This will be great for the projections we’ll begin doing shortly. However, i will vary heavily over the life of each user, so measuring for month one is a good starting point.

(Note: If your loop has been rocking and rolling for a while and you’ve got enough data to try and measure K over the life of a user, we’ll use a different variable. Which we’ll call K’ . . . but more on that later on.)

Pretty exciting stuff so far, right? YAY MATH!

What’s Next?

 

You’ve likely just run to a calculator or a spreadsheet to see what sort of an impact a K > 1.0 would have on your product, and you’re currently flipping out.

If that’s you – take a deep breath.

I hate to be the bearer of bad news, because even if you hit K > 1.0 (the holy grail of K’s), this cannot last for long. As you’ll soon see as we move forward, if it DID last for very long you’d end up with more users than currently inhabit the entire planet. While that might sound awesome to your bottom, unfortunately it’s impossible. (Unless your product goes viral on Mars, too.)

But fear not, you can still harness the incredibly profound power of. . . but believe it or not, K is not the most powerful viral KPI we’ve got at our disposal.

 

What's the Best Way to Amp Up Your Growth?

Viral Factor sounds cool and all, but it actually own’t be the primary metric driving your products virality. That honor goes to the “amplification factor.” Ever hear of it? You’re about to 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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