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Completing K to reveal virality

By now, you’ve gotten to know your viral factor (or K), and how good of a friend it can be to your growth (and your valuation) along your journey of starting a successful company. You’ve also learned how your amplification factor (or A) will be an even more practical measure when it comes to day to day growth.

That said, A – or even K for that matter – will NOT be the KPI that has the most profound impact on your viral growth.

Let me explain:

K is a key measure of the magnitude of your virality, or the overall growth potential your viral engine has IF time were not a factor. However – K by itself will NOT predict your actual viral growth over time.

Why? Because as it stands, it’s an incomplete equation. For example – if I asked you the question...

“If I get 10 new users today, how many new users will they bring back to me total?”

…you might have a shot at getting in the ballpark with K and A. However, if I asked you the question…

“If I get 10 new users today, how much will my total user count grow over the next 20 days?”

…you would have NO way of answering this yet.

This question can’t be answered with just K because K doesn’t factor in time in any way. To get projections like this, you must factor in two new KPIs:

  1. Viral Cycle Time (or ct)
  2. Time (or t)

Viral cycle time (ct), is the amount of time it takes for a user to become aware of your site or app, then go through all of the steps required for them to reach the point where they invite a friend or colleague.

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NOTE: Most ct equations we’ll be working with will be measured in days – but for practicality reasons we’ll convert things into minutes or weeks when necessary so they’re easier to understand.

For example, if you have a ct < 1 day, for our equations to work out, this has to be represented as a decimal-based fraction of 1.0 in order to get many of our higher-level equations (that we’ll go into shortly) to work as planned.

This means that a ct of 1 day = 1.0, while a ct of 12 hours would = 0.5 and so on.

Make sense? Okay – this chapter was a shortie, but an importantie (and yes Mom, I know that’s not a word.)

What’s Next?

This chapter was meant as a brief, but clear introduction to cycle time – which IS that end-all, be-all KPI I told you about in the last two chapters. On the surface, ct might seem a little…boring – but oh – how wrong you are.

In fact, as you’re about to see, reducing ct has far and above the biggest effect on viral growth over time. Get excited.

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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