A/B Testing
Comparing two versions of a page, email, or element to determine which performs better.
Why It Matters
A/B testing replaces guesswork with data, ensuring changes actually improve performance before full rollout.
How It Works
You create two variants (A and B) that differ by one element, split traffic equally between them, and measure which version achieves a higher conversion rate. Statistical analysis determines when results are significant enough to declare a winner.
Real-World Example
An A/B test of a green vs. orange CTA button reveals the orange version converts 22% better with 95% statistical confidence.
Common Mistakes
Testing too many variables at once in a single A/B test
Stopping the test before reaching statistical significance
Related Terms
Testing multiple variables simultaneously to find the best combination of page elements.
The systematic process of increasing the percentage of visitors who take a desired action on your website.
The process of improving conversion rates at each stage of the marketing or sales funnel.
A/B Testing FAQs
How long should an A/B test run?
Run tests for at least 2 full business cycles (typically 2-4 weeks) and until you reach 95% statistical significance.
What should I A/B test first?
Start with high-traffic, high-impact pages like your homepage, pricing page, or checkout flow where even small improvements drive significant revenue.
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