A lot of people think (or hope) that one of their ideas or marketing materials will somehow “go viral,” but most people don’t put much time into thinking about what actually causes something to spread virally.  Without doing too much math, here’s the basics of how something spreads virally: You start with your initial userbase (let’s say it’s 100 users).  A percentage of your userbase (for easy math, let’s say 10%) will invite 10 people to check out your idea or product. Of those 10 invites they send out, let’s assume 10% accept the invitation and become new users.  You add these new users to your original userbase.  But you also should assume (for easy math) that your attrition rate is 10%, so you subtract 10% from your initial userbase.  This represents one wave of viral growth that will then repeat itself to continue the trend.  (In this example, of course, you’re losing the same number of users that you’re gaining.)

But here’s how it gets tricky: you can assume that your viral growth will get worse over time, because in the second, third, and fourth waves of growth, you can expect more and more invitations to go out to the same people, which means your conversion rate (which started out at 10%) may plummet as invitations reach people who are already users, or who have already rejected invitations.  So people begin adopting it at a lower rate, while your attrition rate is likely to stay the same.  This means that each wave of growth is smaller, until eventually it stops.  As Andrew Chen explains it, each “new batch of users needs to exceed the previous batch in order to “go viral.”

What can you do with this information?  Well, the most important thing you can do is set measurable goals for viral activity to guide your decisions and planning to avoid wasting time and resources.  If you know what you’re looking for (adoption rate; conversion rate of new users; attrition rate of your base over time; the size of the universe of users), you can actually measure the factors that have the greatest impact on your success and you can learn how to improve results over time.  Like most useful things, viral activity isn’t guided by one enormous X-factor that either is present or absent.  If you know the rules, you can make it happen.

PS – If you want to go deeper into viral models, follow this link to read Andrew Chen’s stuff.  I will return to this topic periodically, and I hope my posts are helpful on this subject, but if there’s a better place than Chen’s blog to go for an in depth, technical analysis of viral products and marketing, I’m unaware of it.

Will Marlow co-founded AlumniFidelity to help his clients reposition their fundraising to benefit from Web 2.0 technology and marketing techniques. He’s working with clients such as UVA, the College of William & Mary, the University of Oklahoma, Bowling Green State University, Randolph Macon College, and he loves nothing better than a thorny marketing challenge.  Email him at will@alumnifidelity.com