A/B testing, a longstanding practice in digital marketing, involves testing multiple page variations to determine the most effective one, but it is not always the optimal choice due to performance drawbacks like page load delays and content flickering. These challenges have led to the emergence of alternative analytics tools, such as session recording and product analytics, which offer comprehensive user behavior data without compromising performance. Tools like Heap and feature flagging products like LaunchDarkly have expanded the analytics landscape by providing diverse methods to analyze user interactions and gradually deploy features. In particular, edge-based testing approaches, which generate multiple page versions and serve them based on user segments, are gaining traction, though they remain costly and technically complex. Companies like Novvum, leveraging tools like Heap in conjunction with Gatsby, have demonstrated effective strategies for improving conversion rates by integrating non-intrusive content modules and analyzing user engagement patterns. Despite A/B testing's utility, its drawbacks necessitate careful consideration and, often, the adoption of more holistic analytics methods to enhance user experience and achieve actionable insights.