Market Analytics

A comprehensive system integrating customer data, engagement metrics, and sentiment analysis to drive revenue growth and retention.

Project Overview

The Challenge

Building a marketing analytics ecosystem that translates fragmented data into actionable business intelligence.

Key Objectives

  • Optimize pricing & inventory
  • Evaluate campaign performance
  • Predict customer churn risk

Technology Stack

Python (Pandas, NumPy) SQL Server Power BI Matplotlib / Seaborn Sentiment Analysis Statistical EDA

Core Analysis Pillars

Pricing Optimization

Identifying pricing elasticity and inventory patterns to maximize sales velocity and margin.

Segmentation

Clustering customers based on engagement and behavioral metrics to highlight churn-risk groups.

Campaign Impact

Data-backed evaluation of marketing spend across various channels and customer segments.