What is it?

Sample size refers to the number of users or observations included in an analysis or experiment. In optimisation and testing, adequate sample size is required to draw reliable conclusions from data.

Sample size requirements vary based on traffic volume, baseline performance, and expected impact.

Examples in Action

• Determining how long an A/B test needs to run
  
• Assessing whether observed changes are meaningful
  
• Planning experiments on low-traffic pages
  
• Evaluating confidence in behavioural patterns
  

Typical Outcomes / Results

• More reliable and stable insights
  
• Reduced risk of false conclusions
  
• Better planning of experimentation timelines
  
• Improved trust in reported results
  

This glossary entry reflects standard statistical considerations in testing and analysis.