# K-factor

K-factor is the average number of new users each existing user brings in through referrals, calculated as the share of users who refer (i) multiplied by the average number of successful referrals per referrer (c). A K-factor of 1.0 or more means growth sustains itself.

Canonical page: https://getlaunchlist.com/glossary/k-factor. Updated 2026-10-15.

## The formula

**K = i × c**

- **i** is the share of your signups who refer at least one person who goes on to join.
- **c** is the average number of successful referrals each of those referrers brings in.

There is a shortcut hiding in the formula. Because i × c is (referrers ÷ signups) × (referred signups ÷ referrers), the referrers cancel out, and K-factor is simply referred signups divided by all signups in the same period. Both versions give the same number. The split version is the useful one when you want to improve it, because it tells you which half is weak: too few people sharing, or sharers who bring in too few friends.

## A worked example

Say 1,000 people join your waitlist in its first two weeks. 150 of them refer at least one friend who signs up, so i = 0.15. Between them, those 150 bring in 400 signups, so c is about 2.67.

K = 0.15 × 2.67 = 0.40. Every 100 signups you find yourself produce about 40 more.

Those 400 referred signups can refer too. At a K-factor of 0.4, each generation is 40% the size of the one before it: 1,000, then 400, then 160, then 64, and so on. Added up, the list ends at about 1,000 ÷ (1 − 0.4), roughly 1,670 people. That is the real meaning of a K-factor below 1: it does not make the list grow on its own, but it multiplies everything you put in.

| K-factor | Final list size for every 100 signups you bring in |
| --- | --- |
| 0.2 | About 125 |
| 0.4 | About 167 |
| 0.6 | About 250 |
| 0.8 | About 500 |
| 1.0 or more | Keeps growing while the loop holds |

The table is arithmetic, not a benchmark: it assumes every generation refers at the same rate, which real lists only roughly do.

## Measuring it honestly

- **Count successful referrals only.** People who joined, not links shared or clicked.
- **Use a fixed window or cohort.** Late referrals from old signups otherwise inflate this week's number.
- **Leave out fraud.** A self-referral or a burst of fake signups raises K-factor and fills your list with people who will never buy. A number you padded is a number you can't plan with.
- **Watch the cycle time too.** Two lists with the same K-factor grow at different speeds if one turns a signup into a referral in a day and the other takes a month.

## What moves K-factor

To raise **i**, ask at the moment people care most, right after they sign up, make sharing a single tap, and give them a reason to do it: a place in line that improves ([queue jumping](https://getlaunchlist.com/glossary/queue-jumping)) or a reward at the next step ([milestone rewards](https://getlaunchlist.com/glossary/milestone-rewards)).

To raise **c**, give sharers a reason to keep going after the first friend. A ladder of rewards and a visible [referral leaderboard](https://getlaunchlist.com/glossary/referral-leaderboard) both do this. Be careful with big prizes: they raise the number by drawing in people who want to win, not people who want the product.

## K-factor in LaunchList

Every signup gets a personal [referral](https://getlaunchlist.com/features/referrals) link, and a referral is credited once the friend confirms their email (or at signup on a form without confirmation). Self-referrals, repeated referrals from one IP address and bursts that come in too fast are refused before they count, so the figure is not padded.

The Referrals tab in [Analytics](https://getlaunchlist.com/features/analytics) shows both halves of the formula: the people who referred and the referrals per referrer. Below them it writes the result as a sentence, how many of every 100 confirmed signups arrived through a referral, which is the same K-factor calculated against confirmed signups.

The ripple effect behind K-factor is what makes a [viral loop](https://getlaunchlist.com/glossary/viral-loop) worth building, and [viral coefficient](https://getlaunchlist.com/glossary/viral-coefficient) is the other name you will see it under.

Further reading: [the K-factor and viral coefficient guide](https://getlaunchlist.com/blog/viral-coefficient-k-factor-guide).

## Frequently asked questions

### What's a good K-factor for a waitlist?

At or above 1.0, the list keeps growing from referrals alone, which is hard to reach and usually needs a product people genuinely want to show their friends. Below 1.0 is still worth having: a K-factor of 0.5 means the list ends up about twice the size of the traffic you brought in yourself. Compare your K-factor with your own earlier weeks rather than with somebody else's launch.

### What's the difference between K-factor and viral coefficient?

There is no practical difference. Both names describe the same measure, the number of new users each existing user brings in, and both are calculated the same way. K-factor is the more common label among growth teams.

### How do I calculate K-factor from my waitlist numbers?

Take one period or cohort and divide the signups that came through a referral by all signups in it. That gives the same answer as multiplying the share of people who referred (i) by the average number of successful referrals per referrer (c).

### Should K-factor count clicks, shares or signups?

Signups. A shared link or a click that never turns into a signup adds nothing to your list, so counting it makes K-factor look better than your growth really is. Counting only confirmed signups is stricter still, and closer to the people you can actually reach.

### Can K-factor stay above 1 forever?

No. Every audience is finite, so as referrals start reaching people who are already on the list or not interested, both the share who refer and the referrals per referrer fall. A K-factor above 1 tends to come in bursts, which is why it is worth tracking week by week.

## Related terms

- [Viral coefficient](https://getlaunchlist.com/glossary/viral-coefficient.md)
- [Viral loop](https://getlaunchlist.com/glossary/viral-loop.md)
- [Referral leaderboard](https://getlaunchlist.com/glossary/referral-leaderboard.md)
- [Queue jumping](https://getlaunchlist.com/glossary/queue-jumping.md)