yay66/Marketing-Campaign-Analytics

Implemented STP marketing model, ML model and Statistical method to analyze customer campaign project, including a Power BI dashboard and data analytics for data preprocessing, feature engineering, data mining, EDA, Marketing STP model, ML model, Statistical method and tweaking parameters.

Marketing-Campaign-Analytics

• Power BI: https://app.powerbi.com/groups/me/reports/9557735e-b9f4-4620-b70d-98e952ad7b67?ctid=d7270324-ea10-47a1-ae5f-74dba073f8fd&pbi_source=linkShare

A data-intensive analysis project focused on customer segmentation and decision-making processes. The Power BI dashboard also included recommendations for decision-making.

• Developed and optimized a Linear SVM Prediction Model to improve prediction accuracy, demonstrating expertise in model selection and parameter tuning using GridSearchCV.
• Conducted extensive data preprocessing using Pandas and NumPy, including outlier detection, missing value imputation, feature engineering, and normalization, ensuring high-quality datasets for analysis.
• Utilized STP and K-Mean clustering for user segmentation and behavior analysis, alongside RFM analysis to identify high-value clients.
• Applied A/B testing and ANOVA to assess marketing campaign effectiveness and presented results and recommendations via Power BI dashboards