What Is A/B Testing?
A/B testing (also called split testing) is a method of comparing two versions of a page to determine which performs better. Traffic is randomly split between version A (the control) and version B (the variant), and statistical analysis determines which version drives more conversions. It's the gold standard for making data-driven optimization decisions rather than relying on opinions.
Why A/B Testing Matters
Without A/B testing, page optimization is guesswork. You might think a new headline is better, but without data, you're relying on intuition, which is wrong surprisingly often. A/B testing gives you statistical confidence that a change actually improves performance. Even small, validated improvements compound over time: a 5% lift every month leads to an 80% improvement over a year.
How Adaptly Relates to A/B Testing
Adaptly includes built-in A/B testing for every personalization it delivers. When AI personalizes your page for a visitor segment, some visitors in that segment still see the original page as a control group. This lets you measure the exact conversion lift from personalization with statistical confidence, with no separate testing tool or setup required.
A/B Testing in Practice
You want to test whether personalizing your headline for Google Ads traffic improves conversions. Adaptly automatically splits Google Ads visitors: 50% see the AI-personalized headline and body copy, 50% see your original page. After 500 visitors per variant, the personalized version shows a 35% higher conversion rate with 95% statistical significance. You now have proof that personalization works for your specific traffic and audience.
Frequently Asked Questions
How long should I run an A/B test?
Until you reach statistical significance, typically requiring at least 100-500 conversions per variant. For most sites, this means 1-4 weeks. Ending a test too early leads to false conclusions. Use a sample size calculator based on your current conversion rate and the minimum detectable improvement you want to measure.
What should I A/B test first on my landing page?
Start with the highest-impact elements: headline, hero section, and primary CTA. These affect every visitor's first impression. Testing button colors or minor copy changes typically produces smaller lifts. The biggest wins come from testing fundamentally different value propositions or messaging approaches.
What's the difference between A/B testing and personalization?
A/B testing finds the single best-performing page variant for all visitors. Personalization shows different content to different visitor segments based on their context. They're complementary: personalization creates targeted variants, and A/B testing validates that they perform better. Adaptly combines both approaches automatically.
Put A/B Testing Into Practice — Automatically
Adaptly uses AI to personalize your landing pages for every ad visitor. One script, zero configuration, measurable results.
Free plan available. No credit card required.