A/B Testing / Marketing Terms A/B Testing A/B testing is a controlled experiment that compares two versions of a digital asset to determine which one performs better. This method splits an audience into two groups. One group is shown version A, often the current version, while the other group sees version B, which includes a single change. By measuring how each version affects a key metric such as click-through rate, form submissions or donation completions, organizations can identify which option delivers stronger results. Widely used in marketing, product development and user experience design, A/B testing is especially valuable for optimizing digital experiences over time. For example, a nonprofit might test two different subject lines in an email campaign to see which drives higher open rates. A B2B SaaS company might test different button text on a pricing page to increase demo bookings. To maintain accuracy, each test should isolate one change at a time, such as a headline, colour, image or call to action. This allows teams to pinpoint the exact element responsible for performance differences. A/B testing supports data-informed decision-making and helps reduce assumptions, bias and risk. It encourages a culture of curiosity, experimentation and continuous improvement. When set up with clear goals, consistent sample sizes and reliable tracking, A/B tests can lead to meaningful gains in engagement, retention and revenue. Whether you are working to improve a landing page, onboarding flow or campaign performance, A/B testing provides practical insight into how real users respond to your content or design choices.