An interactive Tableau dashboard providing both executive and operational insights into Olist’s sales trends, customer satisfaction, order fulfillment, and strategic performance for data-driven decision-making.
Olist E-Commerce Dashboard Read More »
Analyze bank customer churn and optimize Customer Lifetime Value using 11 machine learning models (e.g., Logistic Regression, Random Forest, XGBoost). Includes EDA, churn prediction, CLV analysis, and model evaluation with metrics like Precision, Recall, F1-score, and Confusion Matrix.
Bank Customer Churn Prediction and Customer Lifetime Value (CLV) Optimization Read More »
Funnel and Cohort Analysis for Business Growth: An end-to-end project using Python, SQL, and Tableau to uncover customer behavior, retention trends, and sales insights. Includes interactive dashboards and actionable recommendations for data-driven decision-making
Funnel & Cohort Analysis for Business Growth Read More »
Analyze customer data from the Superstore dataset through RFM segmentation and visualization. Perform EDA to identify key problems, calculate RFM scores, and derive actionable insights. Present findings in a clear, professional Google Slides report, including a Tableau dashboard for added value.
Superstore RFM Analysis: Unlocking Customer Insights for Business Growth Read More »
Uplift Modeling: Discount vs. BOGO (Control: No Offer) | This project analyzes the impact of Discount and BOGO offers compared to No Offer (Control) using S-Learner & Uplift Random Forest. It includes EDA, AUUC, Gain Chart, and model evaluation to optimize marketing conversions. #MarketingAnalytics #MachineLearning
A Netflix Recommendation System using machine learning models (KNN, Decision Tree, Random Forest, Logistic Regression, Naive Bayes, K-Means) evaluated for accuracy and clustering, with insights into content trends and user preferences.
Netflix Recommendation System: Analysis and Machine Learning Implementation Read More »
This project analyzes the impact of a new playlist recommendation algorithm on engagement, retention, and conversion rates using t-tests and chi-square tests. Includes randomized test design, feature engineering, statistical analysis, and visualizations to guide optimization strategies.
A/B Testing of Spotify’s Playlist Recommendation Algorithm Read More »
A Scalable Data Engineering Solution By Hijir Della Wirasti Project Overview This project was conducted as part of a Data Engineering initiative with ID/X Partners, focusing on Data Warehouse Development, ETL Optimization, and SQL Analytics using MSSQL and Talend. The goal was to enhance data integration and streamline reporting for a financial services client by
Data Warehouse & ETL Optimization for Financial Services at ID/X Partners Read More »
Proyek ini bertujuan untuk menganalisis performa bisnis Kimia Farma tahun 2020-2023, dengan fokus pada: Customer Lifetime Value (CLV) untuk memahami pola loyalitas pelanggan Tren penjualan dan profitabilitas Segmentasi pelanggan berdasarkan frekuensi transaksi & nilai pembelian Korelasi antara diskon, nett sales, dan profit Analisis performa cabang dan kepuasan pelanggan berdasarkan rating Proyek ini menggunakan Google BigQuery untuk pemrosesan data dan Tableau/Looker
Kimia Farma CLV & Sales Analysis Read More »
This project analyzes Sales, RFM, Cohort, Churn, and CLV using SQL, Python, and Tableau to help Kalbe Nutritionals understand sales trends, customer segmentation, and retention strategies.
Optimization Strategy for Sales and Customer Loyalty at Kalbe Nutritionals Read More »
