Viral Loop (4/4) - Viral Growth

This is 4th and final installment on our 4-part series talking about Viral Loop, written about by Adam Penenberg. Have you got your copy yet?

We started the series by talking about What's a Viral Loop? and saw examples of successful viral loops. Then, we went on to explain How it Works in the most basic form of a viral loop. Last post, we talked about how to calculate the Viral Coefficient - the measure of performance in a viral loop.

In this final post, we are going to show you how the viral loop relates to user growth rates. Ideally, you want viral growth!

Viral Growth

Remember the formula to calculate your viral coefficient?

v = x * y
where
x = average number of invites
y = new users / average invites

Here's a table to match different viral coefficient values to their corresponding growth patterns.

Viral Coefficient	Growth
v = 0	no growth
v < 1	some growth
v = 1	linear growth
v > 1	VIRAL growth

Where does your viral coefficient fit?

Let's go back and visit our example in the last post. We had v = 1 or we had 1 new user for each existing user - linear Most people would be quite happy with linear growth. I mean, it is free advertising through word-of-mouth testimony after all. But is that good enough? Is that true viral growth? Is there more growth available?

Let's show it a different way, by observing a graphical comparison of different growth rates. To do, this we'll start with 10 users and extrapolate over a series of time periods the different viral coefficient growth rates.

If you had your pick, which one of these three lines would it be? (I hope you picked the green one).

time period	v = 0.9	v = 1.0	v = 1.1
0	10	10	10
1	19	20	21
2	27	30	33
3	34	40	46
4	41	50	61
5	47	60	77
6	52	70	95
7	57	80	114
8	61	90	136
9	65	100	159
10	69	110	185
11	72	120	214
12	75	130	245
13	77	140	280
14	79	150	318
15	81	160	359
16	83	170	405
17	85	180	456
18	86	190	512
19	88	200	573
20	89	210	640

This graph shows a much clearer perspective of what true viral growth looks like - v > 1!. A viral coefficient greater than 1 provides an accelerated growth rate, that any social community should aspire to have.

Going back to our example, since we're already at v = 1, small, incremental changes to either one or both of our two metrics with push the needle into viral growth territory.

1. Increase the number of average invites (x)
   x = 10 + 1 = 11
   v = 11 x 10% = 1.1


2. Increase the acceptance rate of new users coming from the invites (y)
   y = 10% + 1% = 11%
   v = 10 x 11% = 1.1

It's that simple!

I hope you enjoyed this series on Viral Loop. Our goal at CloudSponge.com is to enable your social community for viral growth. Talk to us today, and see how we can help you to GO VIRAL!