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K-Factor

Metric
Customer

Definition

This measures exponential growth, specifically how many new users each existing user brings in.

K=invitations per user×conversion rate of invitationsK = \text{invitations per user} \times \text{conversion rate of invitations}

For example, if each user invites 5 people and 20% of those invites convert, your K-Factor is:

K = 5 \times 0.2 = 1.0

What the number means

  • K > 1 – Viral growth. Each user brings in more than one new user, creating exponential growth. This is rare and usually unsustainable long term.
  • K = 1 – Stable. Each user replaces themself with one new user. Growth flatlines without other acquisition channels.
  • K < 1 – Decaying virality. You need other acquisition methods to grow. This is where most products sit.

    • Why it matters

    K-Factor helps you understand whether your product has organic viral mechanics.

    Even a K-Factor of 0.5 is valuable, because each acquired user brings in half a user for free, making your paid acquisition effectively 50% more efficient.

    How to improve K-Factor

  • Reduce friction in the invite or share process
  • Make sharing feel natural or rewarding
  • Improve the experience for invited users so they are more likely to convert
  • Add viral loops into the core product experience
    • Example: collaborative features
    • Example: inherently shareable content

    • Limitations

  • K-Factor typically declines over time as networks saturate
  • It does not account for churn
  • High K-Factor with poor retention can still lead to failure

    • Real-world example

    For Lovable, "Powered by Lovable" badges on user-created apps are a viral loop. You would calculate the K-Factor of that badge by measuring:

  • Average number of visitors or sign-ups generated per existing user via the badge
  • Conversion rate from badge impressions to sign-ups

    • Then plug those into the K-Factor formula above.