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K-factor

The K-factor is a measure of viral growth: the average number of new users each existing user brings in through referrals or invites.

By Anders Lindqvist · CBDM Updated 6 September 2026
In brief

The K-factor is a measure of viral growth: the average number of new users each existing user brings in through referrals or invites. It is calculated as the number of invites sent per user multiplied by the conversion rate of those invites.

Definition

The K-factor is a measure of viral growth: the average number of new users each existing user brings in through referrals or invites. It is calculated as the number of invites sent per user multiplied by the conversion rate of those invites.

A K-factor above 1 means the user base grows on its own without paid acquisition, because each user recruits more than one replacement; below 1, referrals amplify other channels but do not sustain growth alone.

The term comes from epidemiology (the basic reproduction number) and applies cleanly to products with a built-in reason to invite others. Most consumer products, including iGaming operators, have a K-factor well below 1, so referral is a cost-reducing supplement to acquisition rather than a standalone engine, and the useful question is not "is K above 1" but "how much does referral lower our blended CAC".

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In context

For an iGaming operator, K-factor analysis breaks the referral programme into its two levers: how many players send at least one invite (participation), and how many of those invites convert to a funded player (invite conversion). Improving participation is a UX and incentive problem — making the invite prompt visible, timely and rewarding; improving invite conversion is a landing-page and offer problem for the invited user.

Multiplying the two gives the effective K contribution.

The metric also has to be read net of fraud and cannibalisation. Self-referral rings and circular invites inflate raw K without adding real users, so the calculation should use verified, retained referred players.

And some referred users would have signed up anyway through another channel, so the incremental K — the genuinely additional users — is lower than the attributed number. Operators use a realistic net K to decide how much to fund referral rewards: the reward can be as large as the CAC it displaces, minus a margin, as long as the referred cohort's LTV holds up.

Worked example

An operator finds 8% of players send an invite and 25% of invites convert, for a raw K of 0.02 per player. Small, but across a large base it displaces a few percent of paid acquisition.

Improving the invite prompt lifts participation to 14% and K to 0.035, and the referral reward is set just below the paid CAC it replaces.

Related terms

Frequently asked questions

How does K-factor work in practice?+
For an iGaming operator, K-factor analysis breaks the referral programme into its two levers: how many players send at least one invite (participation), and how many of those invites convert to a funded player (invite conversion).
Can you give an example of K-factor?+
An operator finds 8% of players send an invite and 25% of invites convert, for a raw K of 0.02 per player. Small, but across a large base it displaces a few percent of paid acquisition.
What terms are closely related to K-factor?+
The closest related terms are CAC (customer acquisition cost), Conversion rate, Lifetime value (LTV). Each is linked in the related-terms block below.
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