What Is A/B Testing?
A/B testing — also known as split testing — is a method of comparing two versions of a single variable (a webpage, ad creative, email subject line, call-to-action button, or any other discrete element) by showing each version to a separate but equivalent group of users simultaneously, then measuring which version achieves a better result against a predetermined metric.
Version A is typically the control — the original or current version. Version B is the variant — the version with a single change applied. By isolating one variable and testing it against a controlled group, marketers can draw statistically valid conclusions about which version performs better.
What Can You A/B Test?
Almost any element of a digital experience can be A/B tested: landing page headlines and body copy, call-to-action text and button color, email subject lines and preview text, ad creative (image vs. image, video vs. static), page layout and navigation structure, form length and field arrangement, pricing display and offer framing, and push notification or social post copy.
How A/B Testing Works
The process begins with identifying a goal and a hypothesis — a specific question ('Will a red CTA button outperform the green one for click-through rate?'). Traffic or send volume is then split, typically 50/50, between version A and version B. Both versions run simultaneously for a sufficient duration to reach statistical significance. At the end of the test, results are analyzed and the winning variant is implemented permanently.
Statistical significance is critical. Running a test on too small a sample or for too short a time can produce misleading results driven by random variation rather than genuine user preference.
Common A/B Testing Pitfalls
Testing multiple variables simultaneously (which becomes multivariate testing and requires much larger samples), running tests for too short a time, ending tests as soon as a variant takes an early lead, and failing to segment results by user cohort are all common mistakes that invalidate A/B test findings.
Tools for A/B Testing
Popular A/B testing platforms include Google Optimize (now sunset, succeeded by server-side solutions), VWO, Optimizely, Convert, and for email, Mailchimp and Klaviyo's built-in split test features. Many ad platforms, including Meta Ads Manager and Google Ads, also have native A/B testing functionality.
A/B Testing at Sagara
Sagara integrates A/B testing into digital campaigns and website optimization work for clients. We help identify which hypotheses are worth testing, set up statistically valid experiments, and interpret results in a way that drives actionable decisions — ensuring that optimization is based on data rather than opinion.