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18 public repositories
matching this topic...
A customer intelligence engine that predicts subscription probability, models purchase frequency, and computes a unified loyalty risk score. Includes explainability, segment insights, and a scenario simulator, all integrated into an interactive Streamlit dashboard.
LoyalPyME: Integrated digital loyalty (LCo) and hospitality service (LC) platform for SMEs. Boost customer retention and streamline operations with points, tiers, rewards, digital menus, QR codes, and advanced customer management. (React, Node.js, PostgreSQL)
A Machine Learning Case Study based on helping the company target customers by predicting the customer loyalty score based on the transactions data.
Power BI analysis of customer satisfaction & loyalty (NPS): regional trends, demographic segmentation, Promoters/Detractors insights for retention strategies.
Web Service: Customer Loyalty Scheme Management
This project focuses on analyzing customer lifetime value using various data visualization techniques. By leveraging Python libraries such as Pandas, Seaborn, Plotly, and Matplotlib, the analysis provides insights into customer acquisition costs, revenue generation, conversion rates, and return on investment across different marketing channels.
顧客ロイヤリティ遷移を考慮したカスタマージャーニーの中期予測モデル
Business performance analysis of Snack Attack Shack (2022–2024), uncovering revenue drivers, customer loyalty, product lifecycle, and operational efficiency using Google Sheets and AI.
An analysis of the customer base of a fictional company called AD Mobile to answer the business question 'how loyal are the customers of AD Mobile?'
Sketches Business Model Canvas, discusses A/B testing and randomized control trials (RCTs), codes a proof-of-concept in Python.
Análisis de datos de clientes para identificar patrones de comportamiento y generar insights accionables que optimicen estrategias de fidelización y retención.
A Go-based REST API for membership stamp tracking system. Manages transactions, digital stamp rewards, and redemptions for seller-customer loyalty programs.
Advanced business analytics project applying statistical and machine learning techniques to derive actionable insights from data.
This project focuses on RFM (Recency, Frequency, and Monetary) Analysis, a powerful customer segmentation technique used in marketing and business analytics. The analysis helps businesses identify their most valuable customers, potential loyalists, at-risk customers, and churned users.
Predictive model for customer loyalty using XGBoost & MLP — predicting next-month repurchase behavior from transactional data
Event-driven Shopify automation using n8n webhooks & OpenAI. Automatically identifies High-Value Customers in real-time and sends AI-generated VIP loyalty emails to boost retention.
🔍 Analyze subscription loyalty risks with machine learning models and gain insights into customer retention and frequency patterns.
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