E-Commerce Marketing Insights and Analytics

Business Context:

One of the leading E-Commerce companies aims to gain valuable marketing insights from their data to define effective marketing strategies. They also intend to build an analytical dashboard to monitor key performance indicators (KPIs) and business metrics.

Available Data:

The provided data consists of transaction data from January 1st, 2019 to December 31st, 2019. The datasets include:

Online_Sales.csv:

This file contains actual order data at the transaction level, containing information such as customer ID, transaction ID, product details, quantity, price, delivery charges, and coupon status.

Customers_Data.csv:

This file contains customer demographics, including customer ID, gender, location, and tenure.

Discount_Coupon.csv:

This file contains discount coupons given for different product categories in different months.

Marketing_Spend.csv:

This file contains marketing spend on offline and online channels on a daily basis.

Tax_Amount.csv:

This file contains GST details for different product categories.

Analysis Objectives:

1. Calculate invoice amount/sale_amount/revenue for each transaction and item level.
2. Perform detailed exploratory analysis to gain insights into:
   • Customer acquisition and retention.
   • Revenue from existing and new customers.
   • Impact of discounts on revenue.
   • Key performance indicators (revenue, number of orders, average order value, etc.).
   • Sales trends and seasonality by category, location, and time.
   • Relationship between marketing spend and revenue.
   • Popular and frequently purchased products.
3. Conduct customer segmentation using heuristic and scientific approaches to define strategies for different customer segments.
4. Predict customer lifetime value (low value, medium value, high value) using classification models.
5. Identify cross-selling opportunities by analyzing product associations.
6. Predict the next purchase day for customers based on their historical behavior.
7. Perform cohort analysis to understand customer behavior and retention patterns.

This project aims to provide valuable marketing insights and enable data-driven decision-making for the E-Commerce company, leveraging advanced analytical techniques and comprehensive exploratory analysis.