Quick Answer (TL;DR)
Viral Coefficient (K-factor) measures number of new users each existing user brings. The formula is Invites sent per user x Conversion rate of invites. Industry benchmarks: >1.0 means viral growth. Track this metric when evaluating organic growth loops.
What Is Viral Coefficient (K-factor)?
Number of new users each existing user brings. This is one of the core metrics in the acquisition metrics category and is essential for any product team serious about data-driven decision making.
In the acquisition stage of the funnel, viral coefficient (k-factor) helps you understand how efficiently you are attracting potential customers. Without visibility into this metric, you risk over-spending on channels that do not convert or under-investing in channels with untapped potential.
Understanding viral coefficient (k-factor) in context --- alongside related metrics --- gives you a more complete picture than tracking it in isolation. Use it as part of a balanced metrics dashboard.
The Formula
Invites sent per user x Conversion rate of invites
How to Calculate It
Apply the formula Invites sent per user x Conversion rate of invites using data from a consistent time period. Pull the values from your analytics platform or data warehouse, compute the result, and compare against the benchmarks below.
Benchmarks
>1.0 means viral growth
Benchmarks vary significantly by industry, company stage, business model, and customer segment. Use these ranges as starting points and calibrate to your own historical data over 2-3 quarters. Your trend matters more than any absolute number --- consistent improvement is the goal.
When to Track Viral Coefficient (K-factor)
When evaluating organic growth loops. Specifically, prioritize this metric when:
You are building or reviewing your metrics dashboard and need acquisition indicators
Leadership or investors ask about acquisition performance
You suspect a change in product, pricing, or go-to-market strategy has affected this area
You are running experiments that could impact viral coefficient (k-factor)
You need a quantitative baseline before making a strategic decision
How to Improve
Invest in compounding channels. Organic acquisition (SEO, content marketing, community) grows over time while paid channels hit diminishing returns. Shift budget toward sustainable growth engines.
A/B test landing pages and campaigns. Small improvements in conversion rates at the top of the funnel compound into significant acquisition gains. Test headlines, CTAs, and page layouts systematically.
Track by channel and segment. Blended metrics hide underperformance. Break this metric down by acquisition channel, geography, and customer segment to find optimization opportunities.
Common Pitfalls
Treating this as a standalone number. No metric tells the full story alone. Always analyze this metric in context alongside related metrics to get an accurate picture.
Not attributing correctly. Multi-touch attribution is difficult, and last-click models over-credit bottom-of-funnel channels. Use a consistent attribution model and acknowledge its limitations.
Measuring without acting. Tracking this metric is only valuable if you have a process for reviewing it regularly and a playbook for responding when it moves outside acceptable ranges.
Related Metrics
Install Rate --- percentage of app store visitors who install
Impression Share --- percentage of available impressions your ads capture
Signup Rate --- percentage of visitors who create an account
Marketing Qualified Leads (MQLs) --- leads that meet marketing qualification criteria
Product Metrics Cheat Sheet --- complete reference of 100+ metrics