K-Factor
A measure of viral growth equal to the average number of invitations each user sends multiplied by the share of those invitations that turn into new users.
Definition
K-factor, borrowed from epidemiology, measures how many new users each existing user brings in through invitations, shares and referrals. It is calculated as the average number of invites sent per user (i) multiplied by the conversion rate of those invites (c). A K-factor above 1 means each user brings in more than one new user, so growth compounds on its own. Most apps have a K-factor well below 1, where virality adds a boost on top of other channels rather than driving growth alone.
Why It Matters
Every user who joins through an invite costs nothing to acquire, often activates faster because a friend is already there, and retains better. Even a K-factor of 0.3 means 100 paid installs become about 143 users once the invite chains play out, which lowers your effective acquisition cost. Measuring K-factor shows whether referral programs, sharing features and invite flows are working and which part of the loop, sending or converting, needs work.
How It Works
Track how many invites or shares users send over a set period and how many of the recipients sign up. Multiply invites per user by the conversion rate to get K. Viral cycle time, how long it takes from a user joining to their invitees joining, matters as much as K: a short cycle compounds faster. Because a share or invite can arrive through many paths, apps attach referral codes or deferred deep links so new users are credited to the person who invited them.
Example
A shared shopping-list app measures one month of invites:
- 20,000 new users sent 30,000 invites: i = 1.5
- 6,000 invitees installed and created an account: c = 20%
- K-factor = 1.5 x 0.2 = 0.3
After adding a prompt to invite a partner right after the first list is created, invites per user rise to 2.1 and K rises to 0.42.
Best Practices
- 1Place invite prompts right after users get value, not during signup
- 2Make inviting part of the product, for example sharing a list or a team workspace
- 3Use deferred deep links so invitees land on the shared content after installing
- 4Track invites sent and invite conversion separately to know which to improve
- 5Reward both the inviter and the invitee, and follow up with a reminder to people who were invited but have not joined
K-Factor Scenarios
| Invites per user | Invite conversion | K-factor | What it means |
|---|---|---|---|
| 1 | 10% | 0.1 | Small boost to other channels |
| 2 | 20% | 0.4 | Meaningful lift, lower blended acquisition cost |
| 5 | 25% | 1.25 | Self-sustaining viral growth |