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Viral coefficient (K-factor) calculator

Compute your product's viral coefficient from invites and conversion rate.

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Enter Invites sent per user, Invite conversion rate (%) and the Viral coefficient (K-factor) calculator works out Viral coefficient (K) straight away. For instance, with Invites sent per user = 5 and Invite conversion rate (%) = 20 it returns Viral coefficient (K) = 1.

How to use it

  1. Enter your values: Invites sent per user, Invite conversion rate (%).
  2. Read the result instantly: Viral coefficient (K).

Frequently asked questions

What does the Viral coefficient (K-factor) calculator actually compute?

It takes Invites sent per user and Invite conversion rate (%) and derives Viral coefficient (K) from them. The calculation is live as you type, so the result updates on every change.

What information do I need to provide?

2 values: Invites sent per user and Invite conversion rate (%). Nothing else is required — no account, no file upload.

Can you show a worked example?

With Invites sent per user = 5 and Invite conversion rate (%) = 20, the calculator returns Viral coefficient (K) = 1. Those figures come from running this exact tool, so you can reproduce them by entering the same values.

What happens if I enter larger values?

It moves a lot. Using Invites sent per user = 10 and Invite conversion rate (%) = 22 instead, Viral coefficient (K) goes from 1 to 2.2 — which is why it is worth testing a few scenarios rather than trusting a single figure.

What does it give for smaller values?

Scaled down to Invites sent per user = 2.5 and Invite conversion rate (%) = 18, Viral coefficient (K) comes out at 0.45. The relationship is worth checking at both ends before you rely on a single result.

When would I actually use this?

Before and after a campaign: turning a target into a daily budget, comparing two channels on the same basis, and deciding whether the return justifies continuing.

What is the most common mistake?

Judging ROAS without subtracting the cost of goods. A 3× return on ad spend is a loss whenever the margin is under a third — the ratio says nothing about profit on its own.

What is the difference between the Viral coefficient (K-factor) calculator and the ARPU calculator?

This one returns Viral coefficient (K); the ARPU calculator returns Average revenue per user. That is the whole difference — open the one whose figure you need.

Where do the figures come from, and how current are they?

The formulas are the industry-standard ones every ad platform uses; the inputs come from your own reporting. Platforms differ in attribution window and in what counts as a conversion, so figures rarely reconcile exactly between them.

Further reading

All guides →
ExplainerThe Viral Coefficient, and Why K Above 1 Almost Never HappensK is invitations per user times the conversion rate of an invitation — two small numbers multiplied. Below 1 the loop is a finite multiplier worth 1/(1−K), and cycle time decides which loop actually wins.ExplainerGrowing an Email List Is a Leaky BucketConstant additions against a proportional loss rate do not grow forever — they converge on a ceiling equal to additions divided by the loss rate. Here is that ceiling computed for six loss rates, why a list can grow while its engaged half shrinks, and the feedback loop that makes a bought list self-defeating.ExplainerReturn Rate: The Number That Decides Whether Your Ecommerce WorksA returned order is not a cancelled sale, it is a sale that cost you money. Here is the return rate at which returns eat the entire contribution of the orders that stayed sold, for three product profiles and five margin levels — plus what bracketing does to your order count.ExplainerCost per Lead, and the Funnel Arithmetic Behind ItCPL is spend divided by leads, and alone it means almost nothing, because a lead is whatever you decided to call one. Worked here: a channel with twice the CPL producing half the CAC, and the redefinition that moves CPL fivefold without moving CAC at all.ExplainerCart Abandonment: The Metric and the Money Behind ItAbandonment rate is one minus completed over created — and the figure quoted everywhere is an average across wildly different shops. The useful work is turning a percentage point of checkout completion into money, then discounting it for returns.ExplainerCPM, CPC and CPA Explained: Which Ad Metric Matters?Understand cost per mille, cost per click and cost per acquisition — how each is calculated, how they relate, and which one to optimize for at each stage of a campaign.