You need more than hope and good intentions if your startup relies on viral growth. You need data and metrics to drive decision making.
Going viral isn’t an exact science, but data plays an important role in gauging how successful your customer acquisition efforts will be. Focus on the virality coefficient before all other metrics. It shows the impact of each product choice on growth. The formula, developed by David Skok, illustrates how each new feature impacts your customer base.
Virality-dependent businesses need to craft their strategy, and every decision they make, around the virality coefficient to be successful..
Otherwise, you’ll sound like these businesses.
(Not) Finding Growth
A number of companies have pitched me by saying they will “go viral” and attract users when it’s obvious that they have no believable plans to make it a reality. Many don’t even have share buttons on their apps!
One company made it so difficult to share their app with others that I never used it again. That’s a virality coefficient of -1. Clearly, their focus wandered.
Let me explain what that means.
The Virality Coefficient Explained
There are four variables used to determine the virality coefficient:
- Initial customers (custs)
- Number of invites sent out (i)
- The Conversation rate of customers (conv%)
- The number of days it takes to complete a full Viral Cycle (ct)
Combine these factors to calculate it using this spreadsheet.
Virality in Action
Let’s say you have ten users and send them ten invites each (100 total invites). With a 20% conversion rate, you’ll finish with a total of 30 customers after the first campaign. Using the sheet I linked to previously, that gives you a virality coefficient of two. Invites * the conversion rate or rather 100 * .2 = 2.
For the next campaign, send out 10 invites to the 20 new users (200 total invites). Assuming there’s no churn or change in the virality coefficient, a 20% conversion rate will bring in 40 new users for a total of 70 users.
Look at the below chart to see just how much of impact each campaign can have. Due to its compounding effects, even small changes in your virality coefficient will have massive impacts on your business.
| Cycle 1 | Cycle 2 | Cycle 3 | Cycle 4 | Cycle 5 | Cycle 6 | Cycle 7 | Cycle 8 | Cycle 9 | Cycle 10 | |
| Starting Customers | 10 | 30 | 70 | 150 | 310 | 630 | 1,270 | 2,550 | 5,110 | 10,230 |
| Invites Sent | 100 | 200 | 400 | 800 | 1,600 | 3,200 | 6,400 | 12,800 | 25,600 | 51,200 |
| Conversions to New Customers | 20 | 40 | 80 | 160 | 320 | 640 | 1,280 | 2,560 | 5,120 | 10,240 |
| Total Customers | 30 | 70 | 150 | 310 | 630 | 1,270 | 2,550 | 5,110 | 10,230 | 20,470 |
There needs to be a coefficient of at least one for there to be growth. Anything less means you’re churning customers.
Crafting a Plan
To determine which feature to develop in your product backlog, sort the features based on the predicted increase in the virality coefficient. The backlog should look something like this chart.
| Feature | Increase of Virality |
| Share Button | 2 |
| Social Login | 1.8 |
| Cool Feature | 1.5 |
| Photo Sharing | 1.4 |
| Logout | 1 |
You need a virality business plan to map out exactly how you’re going to acquire new customers. The plan should determine what features to prioritize, what incentives there are for users to share, and what level of engagement you want to focus on. Don’t forget to determine which promotion channels to use too.
Determining what makes user acquisition work might seem like an art, but using the virality coefficient can change that. Use your data to drive the decision-making process. Even a small increase could mean (hundreds of) thousands of new customers over time.