PLG viral / K-factor calculator
Calculate your viral K-factor and see how user growth compounds across cycles without any paid acquisition — and how sensitive growth is to small improvements in invite rate or conversion.
Enter your starting activated users, how many invites each sends, and what fraction of invites convert. The K-factor determines whether growth is self-sustaining — and the table shows exactly what happens over five cycles.
K-factor calculator inputs and results
K-factor benchmark bands
How the K-factor works
The K-factor is the product of two numbers: how many invitations each activated user sends per cycle, and what fraction of those invitations convert to a new sign-up. A K of 0.45 means each user generates 0.45 new users per cycle on average — the user base can only sustain itself with ongoing acquisition spending. A K above 1 means each cohort of users generates a larger cohort, producing self-sustaining exponential growth.
The compounding effect of K above 1 is dramatic. Starting from 1,000 users with K = 1.2, five cycles produce over 7,400 users — no paid acquisition required. But the same logic applies to small improvements below 1: raising K from 0.3 to 0.5 nearly doubles the contribution of the viral loop to your total growth, even without hitting virality.
In practice, not all activated users send invites in every cycle, and your effective inviter pool shrinks due to churn. The numbers above represent the upper bound assuming full participation. Use these as directional signals rather than exact forecasts.
About this tool
This tool calculates the viral K-factor for a product-led growth motion. Inputs: starting activated users, invites sent per activated user, invite-to-signup conversion rate %. Output: K-factor, viral growth label, and projected total users after 1–5 cycles. Formula: K = invites per user × (signup rate ÷ 100). A K above 1 means each cohort generates more than enough new users to replace itself, producing compounding growth.
Frequently asked questions
What is the viral K-factor?
The K-factor measures how many new users each existing user generates on average. It's the product of two numbers: how many people each user invites, and what fraction of those invitations convert to sign-ups. A K-factor above 1 means the user base is growing exponentially without paid acquisition — each cohort of users generates a larger cohort behind it. A K below 1 means growth slows without ongoing acquisition spend. A K of exactly 1 means you're sustaining the existing user base, no more.
What counts as a viral cycle?
A viral cycle is one round of the invite-signup loop: your existing activated users send invites, some convert to new users, those new users activate, and then they send their own invites in the next cycle. The duration of a cycle depends on your product — it could be a week (for a fast social product) or a month or more (for a B2B tool where invites happen at onboarding). The K-factor itself is independent of cycle duration, but cycle length determines how fast growth compounds.
What's a realistic K-factor for SaaS?
Most B2B SaaS products have a K-factor well below 1 — often between 0.1 and 0.4 — because the invite behaviour is lower and signup conversion is lower than consumer apps. Consumer social apps can exceed K = 1 during viral periods. For B2B PLG products like Slack or Figma, K-factors in the 0.3–0.8 range are strong; they offset sub-viral K with high activation and direct sign-up traffic. A K above 1 in B2B is exceptional and usually short-lived.
Does this model account for user churn?
No — this is a pure acquisition model. It shows how many users accumulate through viral cycles assuming no one leaves. In practice, your retained activated user base (the people still sending invites) will be smaller than the cumulative total because of churn. For a more conservative view, apply your monthly retention rate to the active inviter pool before multiplying by invites and conversion rate.