Translating Vision into Tomorrow's Wins:

Dynamic E-commerce Price Optimizer

Built a dynamic pricing engine using machine learning to recommend optimal product prices based on various factors, aiming to maximize revenue and sales in an e-commerce setting.

Designed a dynamic product bundling recommendation system using association rules and clustering to increase Average Order Value (AOV) and enhance cross-selling in e-commerce.

Dynamic Bundling for Increased AOV Optimization

Predicting Free Trial Conversion for Enhanced Customer Acquisition and Revenue Growth

Developed a machine learning model to predict free trial conversion, identifying key factors influencing conversion and enabling targeted marketing strategies for customer acquisition and revenue growth.

Developed a machine learning model to predict customer churn and lifetime value, enabling targeted retention strategies and personalized marketing campaigns for improved profitability.

E-commerce Customer Lifetime Value (CLTV) Optimization

Customer Churn Prediction Model

Built a machine learning model to predict customer churn, identifying at-risk customers and key churn drivers to enable proactive retention efforts and improve customer loyalty.

Ad Performance Prediction and Optimization

Developed a machine learning solution to predict ad click-through rates and optimize ad placement for enhanced campaign performance, including a recommendation system.

Customer Review Sentiment Analysis

Implemented a sentiment analysis solution for customer reviews, categorizing feedback into positive, negative, and neutral to provide actionable insights for product improvement and customer service.

Dead Stock Detection and Auto Clearance System Implementation

Developed a system to detect dead stock items in inventory and recommend automatic clearance strategies, significantly reducing holding costs and improving inventory turnover.

Developed a machine learning model to predict and optimize retail profit margins, identifying key drivers influencing profitability and providing strategies for cost reduction and revenue enhancement.

Retail Profit Margin Optimizer

Created a sales forecasting model and an optimization framework to predict future sales accurately and recommend optimal marketing spend allocation for maximized ROI and business growth.

Sales Forecasting and Optimal Marketing Spend

Real-Time Financial Fraud Detection

Developed a real-time financial fraud detection system using machine learning, employing techniques to handle imbalanced data and prevent fraudulent transactions efficiently.

Ad Engagement Prediction

Developed a machine learning solution to predict ad click-through rates and optimize ad placement for enhanced campaign performance, including a recommendation system.

Food Wastage Forecasting and Optimization

Developed a comprehensive food wastage forecasting system for food service/retail environments, identifying trends and predicting future wastage to recommend cost-saving optimization strategies.