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.

Dynamic Bundling for Increased AOV Optimization

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

Moments of Innovation, Milestones of Impact

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.

Customer-Churn-Prediction-and-Retention-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.

E-commerce Customer Lifetime Value (CLTV) Optimization

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

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.

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.

Customer Review Sentiment Analysis & Product Improvement Prioritization

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.

Retail Profit Margin Optimizer

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.

Sales Forecasting and Optimal Marketing Spend

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.

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.

E-Commerce Payment Success Prediction

This project develops an ML model for e-commerce payment fraud prediction. It uses historical data and advanced techniques to identify suspicious transactions, aiming to minimize financial losses, enhance security, and improve operational efficiency.