How an E-Commerce Retailer Improved Conversion

This retailer needed to optimize their checkout flow to reduce cart abandonment and increase conversion rates. However, they were hesitant to make changes without proper testing, fearing they might negatively impact revenue. Their previous A/B testing tools were disconnected from their deployment process, making experimentation slow and risky. They also lacked the ability to quickly rollback changes that weren't performing well.

Through systematic A/B testing and progressive rollouts powered by Feature Beam, they optimized their checkout flow iteratively. They ran numerous experiments testing different UI variations, payment options, and user flows. The platform's real-time analytics allowed them to identify winning variations quickly and roll them out progressively. Automatic traffic allocation ensured statistical significance while minimizing risk.