E-Commerce Customer Behaviour & Engagement Tracker
Completed Project
Data Analytics.
- Microsoft Excel.
- Pivot Tables.
- Slicers.
- KPI Reporting.
- Advanced Formulas.
- Dashboard Design.
Business Problem
I discovered that despite strong revenue growth, the business was experiencing a high customer churn rate (67%), indicating that many customers were not returning after making purchases. I also identified that customer value and marketing performance varied significantly across customer segments and acquisition channels, highlighting opportunities to improve retention and maximize marketing ROI.
Key Results & Insights
- $6.4M in total spend and 64.9K total orders analyzed to identify historical purchasing trends
- 67% customer churn rate tracked against a 640-day average customer lifespan
- Multi-channel acquisition breakdown highlighting marketing ROI across Paid Ads, Social Media, and Email Campaigns
- Year-over-year Purchased trend analysis
What I Did
- Cleaned raw transactional e-commerce data using Excel formulas and data validation rules.
- Built Excel formulas and advanced Pivot Tables analyzing high-level retail KPIs, including Average Order Value ($97.1K), churn rates, and average customer satisfaction scores.
- Analyzed demographic purchasing preferences across multiple product lines (such as Electronics, Beauty, and Clothing) and segment tiers (Platinum, Gold, Silver, Bronze).
- Created interactive charts covering yearly purchase trajectories, customer retention metrics, and the baseline impact of email marketing campaigns.
- Identified high-risk attrition points and channel performance gaps to support data-driven decision-making for customer engagement strategies.
