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Growth Systems

Viral Coefficient (K)

How many new users each existing user brings in — and whether your loop compounds or fizzles.

Your numbers

invites
%
users

Results

Viral coefficient K
0.6
New users generated per existing user; 1.0 is the self-sustaining threshold
Second-generation signups
600 users
Users your starting cohort recruits in one viral cycle
Eventual cohort size (if K < 1)
2,500 users
Cohort ÷ (1 − K): total users after the loop fizzles out. Shows 0 when K ≥ 1 — growth compounds indefinitely instead of converging

How it works

K = invites sent per user × invite conversion rate.

K is the branching factor of your referral loop. At K = 1 each user replaces themselves and the loop self-sustains; above 1 growth compounds without paid spend; below 1 each generation shrinks, and virality is an amplifier on your other channels rather than an engine.

The classic mistake is chasing K > 1 as the only goal. Almost no product sustains it — and a K of 0.6 is still hugely valuable: every 1,000 acquired users ultimately becomes 2,500 (1 ÷ (1 − K)), cutting your effective CAC by 60%. The second mistake: ignoring cycle time. A K of 0.9 that cycles in 2 days beats a K of 1.1 that cycles in 3 months.

Worked example

Each of 1,000 new users sends 3 invites and 20% convert: K = 3 × 0.20 = 0.6. The cohort recruits 600 second-generation users, they recruit 360, and so on — converging on 1,000 ÷ (1 − 0.6) = 2,500 total users. Sub-viral, but it cut the effective cost of that cohort by 60%.