The A/B Test Calculator helps users evaluate the effectiveness of two different variants, A and B, by comparing conversion rates or other metrics. This tool is invaluable for anyone looking to optimize their website, campaign, or product without needing deep statistical knowledge. It provides a clear, quantifiable way to determine which variant yields better performance.
Formula of A/B Test Calculator Online
The accuracy of an A/B test hinges on several statistical calculations:
- Conversion rate for variant A: CR_A = Conversions_A / Visitors_A
- Conversion rate for variant B: CR_B = Conversions_B / Visitors_B
- Pooled Conversion Rate: CR_pooled = (Conversions_A + Conversions_B) / (Visitors_A + Visitors_B)
- Standard Error: SE = sqrt(CR_pooled * (1 – CR_pooled) * (1 / Visitors_A + 1 / Visitors_B))
- Z-Score: Z = (CR_A – CR_B) / SE
- P-Value: Determined by the Z-score to assess the significance of the results.
Understanding these calculations will help you accurately interpret the results from the A/B Test Calculator.
Table of General Terms and Useful Conversions
Here’s a table that includes typical values needed when conducting an A/B test. This table serves as a quick reference to understand various metrics without calculating each time manually.
| Term | Description | Example Value |
|---|---|---|
| Visitors_A | Total number of visitors on variant A | 4,000 |
| Conversions_A | Total number of conversions from visitors on variant A | 200 |
| Visitors_B | Total number of visitors on variant B | 4,000 |
| Conversions_B | Total number of conversions from visitors on variant B | 240 |
| CR_A (Conversion Rate A) | Conversion rate of variant A | 5% (200/4000) |
| CR_B (Conversion Rate B) | Conversion rate of variant B | 6% (240/4000) |
| CR_pooled | Pooled conversion rate combining both variants | 5.5% |
| Standard Error | Standard error of the sampling distribution of the difference in means | Computed from formula |
| Z-Score | Measures the standard deviation of the difference between two means | Computed from formula |
| P-Value | Probability that the observed difference is due to chance | Look up in table |
Example of A/B Test Calculator Online
Imagine you are testing two different designs for a website’s landing page. Variant A receives 200 conversions from 4,000 visitors, and Variant B receives 240 conversions from 4,000 visitors. Here’s how you’d use the A/B Test Calculator to analyze which variant performs better:
- Calculate the conversion rate for each variant:
- CR_A = 200 / 4000 = 0.05 (5%)
- CR_B = 240 / 4000 = 0.06 (6%)
- Calculate the pooled conversion rate:
- CR_pooled = (200 + 240) / (4000 + 4000) = 440 / 8000 = 0.055 (5.5%)
- Calculate the standard error:
- SE = sqrt(0.055 * (1 – 0.055) * (1/4000 + 1/4000)) = sqrt(0.055 * 0.945 * 0.0005) = 0.0051
- Calculate the Z-Score:
- Z = (0.05 – 0.06) / 0.0051 = -0.0196 / 0.0051 = -1.96
- Reference the Z-score in a standard normal distribution table to find the p-value. If the p-value is less than 0.05, the result is considered statistically significant, indicating that Variant B performs better than Variant A.
Most Common FAQs
A/B testing is a method to compare two versions of a single variable to determine which one performs better.
It is highly accurate, provided the input data is correct. It uses standard statistical methods to ensure reliability.
Yes, it’s versatile and can be used across different domains wherever A/B testing is applicable.