K-Factor and Viral Coefficient

Overview

K = i × c, where i = average invites per existing user, c = conversion rate into new activated users. K > 1 → exponential growth; K < 1 → finite ceiling; K = 1 → linear. Most "viral" products have K in the 0.1-0.6 range — social transmission, not a growth engine.

Codified by Steve Jurvetson (DFJ) via the Hotmail case (1996); formalized by Andrew Chen, David Skok, and early Facebook/LinkedIn growth teams.

Composes with aarrr-pirate-metrics (K sits in Referral), network-effects (value vs. user count — different things), mvp (smoke tests cannot establish K), feedback-loops (K > 1 is a specific reinforcing-loop condition).

When to Use

• A product is described as "viral" without an explicit K calculation
• Growth plateauing despite "viral elements" (share buttons, referral programs, invite flows)
• A growth team debating which lever to pull without the K = i × c decomposition
• An investor or founder using "viral" to justify a growth forecast
• Not when: B2B enterprise; focus is engagement/retention; pre-PMF product

Coaching Novices (Adaptive Front Door)