In A/B testing, the sample size directly impacts the testâs ability to detect meaningful differences between variants. A small sample size may result in a Type II error, where you fail to detect a difference that actually exists. Conversely, a large sample size increases the testâs power, making it easier to identify true differences between your test variants. This ensures that your marketing decisions are based on robust and reliable data.