What is the K-factor in viral growth?

The K-factor, or Viral Coefficient, is a metric used to measure the number of new users generated by a single existing user through invitations and referrals.

Can I use this for B2B product-led growth?

Absolutely. It includes specific patterns for enterprise viral loops, such as teammate invitations and workspace collaboration triggers used by companies like Slack and Figma.

What is considered a good K-factor for a startup?

In consumer B2C, a K-factor of 0.15-0.25 is good, while 0.7 or higher is considered excellent. In B2B SaaS, 0.20 is a strong indicator of viral growth.

How do I calculate a viral coefficient using this skill?

The skill uses the formula K = i × c, where 'i' is the average number of invites sent per user and 'c' is the average conversion rate of those invites into new users.

Does this skill help with viral cycle time?

Yes, it provides frameworks to measure and reduce the time it takes for a new user to send their first invite, which is critical for exponential compounding.

Viral Coefficient & Growth Modeling

Name: Viral Coefficient & Growth Modeling
Author: lev-os

bylev-os

0•

营销自动化

Optimizes and models viral referral loops to evaluate and drive exponential user acquisition through mathematical K-factor analysis.

This skill implements the quantitative Viral Coefficient (K-factor) framework to help teams measure and optimize user-driven distribution. It provides a structured methodology for calculating invitation rates and conversion benchmarks, allowing users to model growth cycles, identify friction in sharing mechanics, and determine if viral growth can serve as a primary acquisition channel. By applying formulas popularized by growth experts like Andrew Chen, it assists in forecasting user acquisition trends and refining the 'Viral Cycle Time' for faster compounding growth in both B2C and B2B contexts.

主要功能

01Viral cycle time optimization and compounding analysis

02Multi-channel referral loop tracking (Email, SMS, In-app)

03Friction identification in user invitation and onboarding flows

04K-factor calculation and mathematical growth modeling

05Industry-specific benchmarks for SaaS, Marketplaces, and Consumer apps

060 GitHub stars

使用场景

01Evaluating the viability of referral programs as a primary acquisition channel

02Optimizing sharing triggers within the product experience to increase K-factor

03Modeling user growth forecasts based on cohort invitation data

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add lev-os/agents viral-coefficient-models

For use in Claude.ai and ChatGPT

Download Skill