Sample Size Calculation
Definition
Determining the minimum number of users needed in an experiment to detect a meaningful effect with sufficient statistical power before running the test.
Why It Matters
Key Takeaways
- 1.Sample Size Calculation is a core concept for modern business and technology strategy
- 2.Practical application requires combining theory with data-driven experimentation
- 3.Understanding this concept helps teams make better technology and growth decisions
Real-World Examples
Applied sample size calculation to achieve competitive advantages.
Growth Relevance
Sample Size Calculation directly impacts growth by influencing how companies acquire, activate, and retain customers.
Ehsan's Insight
Sample size calculation should happen before the test starts, not after. The formula considers four inputs: baseline conversion rate, minimum detectable effect (MDE), statistical significance level (typically 95%), and statistical power (typically 80%). For a 5% baseline conversion rate and a 10% relative improvement (to 5.5%), you need approximately 31,000 visitors per variant. Most teams do not run this calculation and end up with two problems: (1) tests that run for months because they are underpowered, or (2) tests declared successful with insufficient data. Use an online sample size calculator before every test. If you cannot reach the required sample in 2 weeks, the test is not viable.
Ehsan Jahandarpour
AI Growth Strategist & Fractional CMO
Forbes Top 20 Growth Hacker · TEDx Speaker · 716 Academic Citations · Ex-Microsoft · CMO at FirstWave (ASX:FCT) · Forbes Communications Council