• Developed and tested a hypothesis investigating the impact of price changes on churn for a leading energy utility company PowerCo. • Led comprehensive exploratory data analysis (EDA), uncovering key churn behavior patterns and influencing factors. • Developed predictive model to tackle high churn rate in PowerCo's SME division, observing 9.7% churn across 14,606 customers. • Identified top churn drivers: Yearly consumption, forecasted consumption, and net margin, surpassing customer price sensitivity. • Proposed targeted 20% discount strategy, highlighting its efficacy when directed at high-value customers with substantial churn risk.