The process of deploying machine learning models into production is notably challenging and costly, with only a small fraction of projects reaching this stage. To address this, Datagran's Rule Extraction offers a streamlined solution, particularly beneficial in industries like e-commerce. For example, the delivery app Rappi utilized Rule Extraction to analyze why users abandoned their shopping carts. By integrating Datagran's SDK and applying a Classification algorithm to Decision Tree models, they identified a warning message as a significant drop-off point. This insight allowed Rappi to redesign the message and enhance customer retention by offering alternatives through a chatbot. Rule Extraction, enabled by low-code platforms, allows companies to quickly build, test, and iterate pipelines without extensive resources, as demonstrated in a telecommunications churn prediction tutorial. The ability to extract meaningful patterns from vast data volumes aids businesses in strategically addressing customer dissatisfaction and reducing churn.