ecommerce-sales-optimization

Project Overview This project focuses on analyzing e-commerce sales data to understand sales trends and customer behavior, with the goal of optimizing revenue through data-driven insights Project Objectives* Analyze sales trends over time Understand product and customer behavior Identify factors influencing revenue Evaluate the impact of promotions using statistical methods 🧠 Analysis Components The project covers the following components: 🧹 Data Wrangling Handling missing orders Removing duplicates Treating outliers Standardizing data formats 📊 Exploratory Data Analysis (EDA) Univariate and multivariate analysis Sales and revenue trends Product-level and customer-level insights Data visualizations with clear interpretations 🧠 Feature Engineering & Selection Temporal features (day, month, weekday) Customer segmentation features Encoding categorical variables Feature selection techniques 📐 Probability & Hypothesis Testing Modeling sales patterns using Poisson distribution Probability calculations Hypothesis testing (t-test) to measure promotional effectiveness 📉 Dimensionality Reduction (PCA) Applying Principal Component Analysis (PCA) Interpreting principal components Visualizing customer and product patterns