Traditionally, marketers have relied on A/B testing to optimize campaigns by changing one variable at a time. While still relevant and widely used, this method can be slow, limited, and resource-intensive. It often forces teams to test one idea at a time, delaying insights and potentially missing out on better-performing combinations.
To understand the power of AI experimentation, it's important to first look at how marketers have traditionally approached testing. AI-driven....