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Assessed brand loyalty patterns and price elasticity metrics to provide insights for brand’s market growth. Recommended strategies for the top 3 brands based on competitor analysis, customer profiling and customer retention through RFM analysis and multinomial logit.
Creation of a MultiLayer Perceptron using Back Propagation Algorithm. It was trained to efficiently classify the data into two sets:exit and stay. This was able to predict whether a customer might stay with the bank or leave it in future.
A machine learning model to forecast customer retention, as well as performing exploratory data analysis to examine which metrics may be most relevant to increase retention.
This demo repository demonstrates how to analyze customer reviews with Azure OpenAI Service (AOAI). I leveraged "ASOS Customer Review" from Kaggle to obtain valuable insight from the customer review content.
This is A Telco Customer Churn Rate Dashboard project that provides insights into customer behavior and churn rates. The dashboard was built using Microsoft Power BI.
Loyalty Bridge is a web-based loyalty management system that enables businesses to track and incentivize customer loyalty. With Loyalty Bridge, customers earn loyalty coins for each purchase, which can then be redeemed for discounts on future purchases.
This project promises to predict and prevent customer attrition, ensuring long-term loyalty and competitiveness, by leveraging supervised machine learning algorithms.
This project predicts Customer Lifetime Value (CLV) for e-commerce. It aims at forecasting the revenue a business can expect from a customer over time. I did an explatory analysis. From Linear Regression to Neural Networks, explore how different models perform in predicting CLV.