kaze nesia
Full-Stack Data Specialist | Automation & Predictive
New to Contra
kaze is ready for their next project!
This project is an in-depth Strategic & Growth Analysis of retail business performance as a global market leader. The main focus is to evaluate how digital technology integration, e-commerce innovation, and supply chain optimization contribute to the company's financial health amid a competitive market dynamic.
Key Insights :
Solid Financial Performance: Successfully recorded significant revenue growth and overall profitability improvement. Global Market Dominance: Strengthened international expansion strategies and effective customer loyalty programs to maintain consumer retention. Supply Chain Efficiency: Implementation of the latest technology to accelerate the distribution process from warehouse to consumer (last-mile delivery).
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This project is an end-to-end machine learning analysis designed to predict churn (customer attrition) and calculate Customer Lifetime Value (CLV) on an e-commerce platform. Using a dataset containing 5,630 customers, this project integrates a data pipeline ranging from cleaning and RFM segmentation to predictive modeling to optimize customer retention strategies.
Key Findings :
High Model Performance: The optimized LightGBM algorithm achieved a ROC-AUC score of 0.9994.
Cost Efficiency: The model successfully achieved 0 False Negatives (no churners missed) at the optimized cost threshold.
Financial Impact: Retention strategy simulations show a potential campaign ROI of 1,007.5% with total net profits reaching 170,514.
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RFM Customer Segmentation Analysis
I developed a comprehensive RFM (Recency, Frequency, Monetary) Customer Segmentation Analysis using Python to help businesses identify, understand, and target their most valuable customers. This data-driven approach transforms raw transaction data into actionable marketing strategies, enabling personalized customer engagement and improved ROI.
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3
226
Retail Analytics Dashboard - Business Intelligence Solution
I developed a comprehensive Retail Analytics Dashboard using Python in Google Colab, designed to transform raw sales data into actionable business insights. This end-to-end data analytics solution helps businesses understand their performance, customer behavior, and growth opportunities through interactive visualizations and advanced analytics.
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220
Movie Industry Data Storytelling & Analytics
I developed a comprehensive data storytelling project analyzing 10,000+ movies using Python (Pandas, Matplotlib, Seaborn, Plotly) to uncover actionable insights for commercial decision-making in the entertainment industry. The analysis transforms raw movie metadata into strategic business intelligence through advanced data cleaning, statistical analysis, and publication-ready visualizations.
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🚀 Sales Performance Analytics
Delivered comprehensive sales analytics solution transforming raw transaction data into actionable business insights using Python (Pandas, Matplotlib, Seaborn, Plotly).
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