Automated Business Performance & Insight Engine (Python)

1. Problem Statement

Business teams often receive raw transactional data but lack clear insights to make data-driven decisions. This project builds an end-to-end analytics system that converts raw data into KPIs, insights, and business recommendations using Python.

2. Objectives

~ Analyze revenue, customer behavior, and product performance

~ Identify growth opportunities and churn risks

~ Automate insights generation for stakeholders

3. Key Business Questions Answered

~ How is revenue trending over time?

~ Which products and customers drive profitability?

~ Where is revenue leakage occurring?

~ What actions can improve retention and revenue?

4. Tools & Technologies

~ Python

~ Pandas, NumPy

~ Matplotlib, Seaborn

~ Excel automation

5. KPIs Analyzed

~ Total Revenue & Growth Rate

~ Average Order Value

~ Customer Retention & Churn

~ Product Profitability

~ Repeat Purchase Rate

6. Key Insights (Sample)

~ Revenue declined 11% due to increased churn in Tier-2 cities

~ 20% of products contribute to 78% of total revenue

~ High discount products show low profitability

7. Recommendations

~ Focus retention campaigns on high-value repeat customers

~ Optimize pricing for low-margin high-volume products

~ Reduce dependency on low-profit discount strategies