A/B testing, also known as split testing, is a controlled experiment that compares two versions of an ad, landing page, or other marketing asset to determine which one performs better.
A/B testing removes guesswork from advertising optimization, replacing assumptions with quantitative data. It enables advertisers to understand what resonates most with their target audience, leading to continuous improvement of key performance metrics. By methodically testing creative elements, marketers can refine their messaging, avoid creative fatigue, and systematically increase their conversion rates. This iterative process of testing and learning is crucial for achieving sustainable growth and a competitive advantage in a crowded digital landscape.
