📊 MarketLens

Consumer Behavior & Food Service Intelligence

Python-based consumer analytics platform for demographics, purchasing behavior, food preferences, sustainability, and customer satisfaction insights.

🎯 Project Objective

Analyze consumer survey and food service datasets to uncover behavioral patterns, identify emerging food trends, evaluate sustainability preferences, and measure customer satisfaction to support data-driven business decisions.

⚙️ Technology Stack

Python
Pandas
NumPy
Matplotlib
Seaborn
Excel

🚀 Key Analytics

👥 Consumer Demographic Analysis
🛒 Purchasing Habit Analysis
🍽️ New Food & Cuisine Preference Analysis
🌱 Sustainability Preference Analysis
😊 Customer Satisfaction Analysis

🧠 Analytical Techniques

Exploratory Data Analysis (EDA)
Consumer Profiling
Frequency & Percentage Analysis
Distribution Analysis
Cross-Dataset Integration
Quarterly Trend Analysis
Comparative Analysis
Satisfaction Index Calculation
Aggregation & Business KPI Analysis
Business Data Visualization

💡 Business Impact

Identified demographic patterns influencing consumer purchasing decisions and food preferences.
Revealed quarterly demand trends for cuisines and emerging food products through integrated consumer and food service data.
Evaluated consumer attitudes toward sustainability to support environmentally conscious product strategies.
Measured customer satisfaction across quality, pricing, branding, and customization to identify improvement opportunities.
Delivered actionable insights for product development, customer engagement, and targeted marketing initiatives.