E-commerce Customer Lifetime Value (CLV) Analysis and Dashboard

Category: Data Science

Budget: 1525–1525 USDC

We are seeking a skilled data analyst to analyze our Shopify store's historical transaction data to identify high-value customer segments and predict future Lifetime Value (CLV). The project requires cleaning a dataset of approximately 50,000 rows, performing RFM (Recency, Frequency, Monetary) analysis, and identifying churn patterns. The final deliverable should be a comprehensive technical report detailing your findings and a dynamic, interactive dashboard in Tableau or Power BI that our marketing team can use for seasonal targeting. The project must be completed within three weeks. You will be expected to provide the cleaned dataset, the source code used for analysis (Python/SQL preferred), and a 30-minute walkthrough of the dashboard functionality. Success will be measured by the accuracy of the segmentation and the clarity of the visualizations.

Skills required

• Python
• Power BI
• SQL
• RFM Analysis
• Data Visualization

Milestones are funded into USDC escrow on Polygon before work begins.