# Using the Humblytics A/B Split Test Sample Size Calculator

A/B split testing is a method used to compare two versions of a webpage or app to determine which one performs better. By testing A (the control) against B (the variation), you can make data-driven decisions to optimize your website or app for a better user experience and higher conversion rates.

#### Why is Sample Size Important in A/B Testing?

Determining the correct sample size is crucial in A/B testing to ensure that your results are statistically significant. A sample size that is too small may lead to inconclusive results, while a sample size that is too large may waste resources.

#### How to Use the Humblytics A/B Split Test Sample Size Calculator

The Humblytics A/B Split Test Sample Size Calculator helps you determine the number of visitors you need for each variant to achieve statistically significant results. Here’s how you can use it:

**Access the Tool**Navigate to the Humblytics A/B Split Test Sample Size Calculator.

**Input the Required Fields****Baseline Conversion Rate (%):**This is your current conversion rate or the rate at which visitors are currently converting on your site. For example, if your current conversion rate is 5%, you would enter 5.**Minimum Detectable Effect (%):**This is the smallest change in conversion rate that you want to detect. For instance, if you want to detect a change of 1%, you would enter 1.**Statistical Significance (%):**This represents the confidence level you want for your results. Commonly used levels are 95% or 99%. For a 95% confidence level, enter 95.**Statistical Power (%):**This is the probability that your test will detect a difference when one actually exists. A common value is 80%. For 80% power, enter 80.

**Calculate the Sample Size**Click the "Calculate" button. The tool will then provide the required sample size for each variant (A and B) to achieve statistically significant results.

**Review the Results**The calculator will display the required sample size for each group. Make a note of these numbers to guide your testing.

**Implement in Your Testing**Use the calculated sample size to plan your A/B test. Ensure you reach the required number of visitors for each variant before drawing conclusions.

#### Example Calculation

Suppose your current conversion rate is 5%, and you want to detect a minimum change of 1% with a 95% confidence level and 80% power. Here’s how you would fill out the fields in the tool:

**Baseline Conversion Rate:**5**Minimum Detectable Effect:**1**Statistical Significance:**95**Statistical Power:**80

After clicking "Calculate," the tool might indicate that you need, for example, 4,000 visitors for each variant (A and B) to achieve statistically significant results.

#### Best Practices for A/B Testing

**Test One Variable at a Time:**Ensure that you are only testing one element (e.g., headline, button color) at a time to isolate the impact.**Run Tests for an Appropriate Duration:**Make sure your test runs long enough to account for variations in traffic patterns.**Avoid Stopping Tests Early:**Wait until you have the required sample size before making decisions based on your test results.**Analyze Data Thoroughly:**Look beyond just the conversion rate and consider other metrics like bounce rate, time on page, and user behavior.**Repeat Tests:**Conduct multiple tests over time to continuously optimize and improve your site’s performance.

By following this guide and utilizing the Humblytics A/B Split Test Sample Size Calculator, you can accurately determine the necessary sample size for your A/B tests, ensuring your results are statistically significant and your decisions are data-driven.

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