Implement regression analysis to identify key factors influencing transaction volumes and present the findings through a detailed scatter plot, highlighting potential areas for operational improvement.

Develop a predictive model to forecast customer churn based on transaction patterns, utilizing a confusion matrix for visualization to assess the model's accuracy and reliability.

Conduct a time series analysis to predict future transaction volumes using historical data, with results visualized through an interactive line chart to facilitate trend analysis.

Apply advanced clustering techniques to segment customers into distinct groups based on their transaction behavior, enabling the company to devise customized marketing campaigns for each segment.