K-factor is the virality coefficient: the average number of new users each existing user generates through product-driven sharing or invites.

How it works

A simple framing: if each user sends invites that convert to 0.4 new users on average, K = 0.4. Growth from virality alone shrinks unless something else — paid ads, sales, SEO — adds users. At K = 1, each cohort replaces itself through referrals; above 1, growth accelerates without proportional spend.

Real products rarely sustain K above 1 at scale. Early invite-only betas can look viral; mature networks usually settle below 1 as the easy audience is exhausted.

Why it matters

• Founders: Separate true viral loops (in-product sharing that completes a job) from one-time referral bonuses. Measure K by cohort and channel, not a single headline week.
• Investors: High K with poor retention is a red flag. The interesting case is K near 1 with strong payback on blended CAC when virality plus paid work together.

Measuring K-factor requires clean attribution. Invites opened from email campaigns are not the same as in-product sharing after a completed workflow. Split organic viral loops from incentivized referrals — paid bonuses inflate K temporarily.

Sustainable K often comes from product mechanics where sharing completes a job: collaboration invites, payment requests, or content co-creation. Investors ask whether K holds as you move from early adopters to mainstream users.

Common mistake

Counting all signups from a referral link as permanent virality without measuring whether invited users stay and invite others.

Related ideas

• Viral loop and referral program design
• CAC and payback period
• Product-led growth metrics