Product-Led Growth (PLG) & Viral Loops Lab

Viral Coefficient & K-Factor Lab

Calculate viral coefficient (K-factor), viral cycle time, organic amplification multipliers, and compounding user growth in a free product-led growth lab.

Virality Engine Cycle Compounding Table PLG Theory FAQ

Growth Loop Presets

Load benchmark viral product loops.

Step 1: Configure Viral Loop & Cycle Parameters

Viral Growth Inputs

Acquired seed user cohort.
Average referrals sent per active user.
Percent of invitees who accept and convert.
Time taken for an invite to convert into a new inviter.
Paid marketing cost per top-of-funnel user.
Viral Coefficient
K = 1.30
True Exponential Virality (Runaway Compounding)
Organic Multiplier
Exponential (Runaway)
No upper theoretical ceiling
Total Users (10 Cycles)
46,953 Users
+45,953 organic viral invites (30 days)
Effective Blended CAC
$5.10
Direct Paid CAC: $25.00 (-79.6%)

Cycle-by-Cycle Viral Compounding & User Progression

Viral Cycle Elapsed Timeline New Cycle Additions Cumulative Active Users Organic Share

Growth Mechanics & Product-Led Growth

The Science of Viral Loops

Product-led growth transforms users into organic acquisition channels:

  • The K-Factor Threshold: $K = 1.0$ is the mathematical boundary. Below 1.0, growth decays but multiplies paid marketing. Above 1.0, user growth becomes exponential without additional marketing spend.
  • Cycle Time Compounding: Halving viral cycle time (e.g. from 14 days to 7 days) doubles the speed of exponential compounding over any fixed calendar quarter.
  • CAC Dilution: Even a sub-viral loop ($K = 0.60$) yields a $2.5 imes$ amplification multiplier ($1 / (1 - 0.60) = 2.5$), effectively reducing paid CAC by 60%.
  • Retention Synergy: Virality without strong product retention causes high leaky-bucket churn; sustainable loops require high Day-30 retention.

Measure payback in the CAC Payback Lab.

Mathematical Virality Formulas

Growth loop formulas

Viral Coefficient (K) = Invites × Conversion Rate %

Amplification Multiplier (M) = 1 ÷ (1 - K) [for K < 1.0]

Users at Cycle t = U_0 × K^t

Cumulative Users = U_0 × [ (1 - K^(t+1)) ÷ (1 - K) ]

Effective CAC = Paid CAC ÷ Multiplier

Calculate customer value in the CLV & Retention Lab.

FAQ

Viral coefficient & growth loop questions

What is a viral coefficient (K-factor)?

The viral coefficient (K-factor) measures the number of new users generated by each existing user through referrals, shares, or collaborative loops: K = Invites per User * Referral Conversion Rate.

What happens when K is greater than 1.0 vs less than 1.0?

When K > 1.0, each cohort produces a larger subsequent cohort, leading to exponential viral compounding without paid ad spend. When K < 1.0, virality decays, but acts as an organic amplification multiplier reducing effective CAC.

Why is viral cycle time critical to growth compounding?

Viral cycle time is the time required for a user to invite friends and for those friends to convert. Shorter cycle times accelerate the frequency of compounding, producing dramatically faster user growth.

How does a viral loop reduce Customer Acquisition Cost (CAC)?

Organic referrals dilute paid advertising spend across a larger total user base: Effective Blended CAC = Paid CAC / Viral Amplification Multiplier.

What strategies increase the viral coefficient?

Increasing invite prompts (frictionless sharing, double-sided incentives), improving recipient onboarding conversion, and embedding inherent product collaboration.

Can I export the viral compounding model to CSV?

Yes. You can export complete cycle-by-cycle new users, cumulative growth, organic shares, and effective CAC figures as a UTF-8 CSV spreadsheet with formula defense.

Continue Exploring Marketing & Demand Tools

Explore our Marketing & Demand Hub, optimize conversion steps in Conversion Funnel Lab, calculate payback velocity in CAC Payback Lab, measure customer equity in CLV & Retention Lab, or evaluate attribution credit in Attribution Lab.