ConverterHub

Viral Coefficient Calculator

Enter invites sent per user and the invite conversion rate to find the viral coefficient.

How it is calculated

The viral coefficient, or k-factor, is k = i × c / 100. Here i is the average number of invitations each user sends and c is the percentage of those invitations that turn into a new user. The tool shows k with two decimals and a status: above 1 is "Viral growth", below 1 is "Sub-viral", and exactly 1 is "At unity". The new-users figure it shows is the same number as k, because each user is counted as bringing k new users. The invites figure must be zero or more and the conversion rate must be between 0 and 100. The status uses the exact value, not the rounded one. The tool does not include time between invitations.

Worked example

Each user sends 6 invites on average, and 15% of those invites become new users. k = 6 × 15 / 100 = 0.90. Every user therefore brings in 0.90 new users, and the tool shows the status "Sub-viral (k < 1)". Starting from 1,000 users, referrals would add about 900 users, then 810, and so on, so the loop fades out without other acquisition channels. Raising the conversion rate to 20% would make k = 1.20 and sustain growth.

Try this example →

Common mistakes

  • Entering the conversion rate as a fraction (0.15) instead of a percentage (15). The tool would read it as 0.15% and show k near 0.01.
  • Using total invites sent by the whole user base instead of invites per user. The first field is an average per user.
  • Counting people who clicked an invite as converted. Conversion should be completed sign-ups from invites, otherwise k is overstated.
  • Reading 1.00 as proof of break-even. The label "At unity" appears only when the unrounded product is exactly 1; for example 3 invites at 33.3% shows 1.00 yet is Sub-viral.
  • Ignoring time. A k of 1.2 with a cycle of several months grows far slower than the same k with a cycle of days, and this tool does not measure that cycle time.

About this calculator

The viral coefficient — often called the k-factor — measures how many new users each existing user brings in on average, calculated as invites sent per user × invite-to-signup conversion rate. If a user sends 5 invites and 20% convert, k = 1.0.

A k-factor above 1.0 means every user brings in more than one new user on average, so the product can theoretically grow through word-of-mouth alone without any paid acquisition — true viral, compounding growth. A k-factor below 1.0 means the viral loop still helps but can’t sustain growth by itself and needs to be paired with other acquisition channels. Growth marketers and product managers at consumer and B2B products with sharing or referral features — the pattern popularized by early Dropbox and PayPal — calculate this figure to see whether their invite mechanics are actually compounding.

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