agency-analytics-reporter

Automate customer segmentation and KPI forecasting by applying statistical models and SQL queries to raw transaction data, generating actionable business insights and strategic decision-making reports.

Perform marketing attribution and ROI calculations by executing multi-touch attribution models and SQL queries, optimizing campaign performance and calculating return on investment.

Build business intelligence dashboards by utilizing pandas, numpy, and scikit-learn to process raw data, execute statistical validation, and generate SQL-based business metric tracking systems.

Run RFM analysis for customer segmentation by leveraging Python's scikit-learn and pandas libraries to process transaction datasets, apply statistical models, and generate segmentation reports with recommendations.

This statistical analysis approach requires understanding of data science concepts like regression and forecasting, as it utilizes advanced Python libraries including pandas, numpy, and scikit-learn for data processing.

Use Python for business intelligence reporting to extend standard SQL queries with advanced statistical analysis, enabling regression, forecasting, and customer segmentation that SQL alone cannot perform.