A/B testing, also known as split testing, is a systematic experimentation method employed to assess the performance of two different variations, typically labeled as A and B, with the aim of identifying the more effective option based on data-driven insights.
Digital marketing teams use A/B testing on their website, in marketing emails or in digital ads. Seeing the results enables them to make informed decisions about which variation yields superior outcomes so they can fine-tune elements of their online presence to enhance user experience, conversion rates, and overall performance.
The key to successfully conducting A/B testing is test only a single variable at a time and track the difference in metrics for the two variations. For example, for testing two different ads on LinkedIn Advertising, you might use the same image and use different text. Once the test is complete, the winning ad would remain on and the underperforming ad would be turned off. Often, marketers continually improve performance through these tweaks.
