{"repo":"SaurabhSSB/consumer-behavior-analytics","free":true,"listed":false,"github":"https://github.com/SaurabhSSB/consumer-behavior-analytics","clone":"git clone https://github.com/SaurabhSSB/consumer-behavior-analytics.git","description":"A data analysis project exploring consumer behavior and sales trends through EDA using Python. Includes visualizations and insights derived from retail shopping data.","language":"Jupyter Notebook","stars":10,"topics":["consumer-behavior","correlation-heatmap","csv-analysis","customer-segmentation","data-cleaning","data-storytelling","data-visualization","eda-project","exploratory-data-analysis","feature-engineering"],"license":"MIT","category":"analytics","readme_excerpt":"🛍️ Consumer Behavior Analytics This repository presents a comprehensive exploratory data analysis (EDA) project that investigates customer shopping trends and sales performance using Python. It showcases how data-driven insights can help understand purchasing behavior, seasonal patterns, and key business questions for retail optimization. --- 📁 Project Structure --- 📊 Project Highlights 🧠 Customer Shopping Trends - Age-based and gender-based purchasing patterns - Preferred payment methods and product categories - Purchase frequency vs. subscription/discount/promo usage - Seasonal and regional shopping behavior - Correlation analysis between numeric features 📦 Sales Data Analysis - Sales performance by month and city - Product categorization (phones, accessories, etc.) - High- and low-performing products by season - Time-based advertising recommendations - Price pattern evaluation and bulk order trends --- 🛠️ Tech Stack - Python - Pandas - Seaborn - Matplotlib - Jupyter Notebook --- 🔍 Keywords consumer behavior · retail analytics · sales trends · data visualization · EDA · shopping insights · Python data analysis · customer segmentation · pandas · seaborn --- 📎 Dataset Reference The dataset used for this analysis ( shopping trends.csv ) contains anonymized data of consumer purchases, including demographic features, payment preferences, seasonal buying patterns, and product details. --- 📌 Usage Clone the repo and run: or explore 1 familiarization.ipynb for step-by-step","default_branch":null,"files":null,"tree":[],"storefront":"/r/SaurabhSSB","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/SaurabhSSB/consumer-behavior-analytics/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}