Fake Shop Analytics
End-to-end analytics pipeline for customer engagement insights
Enabled customer funnel and retention tracking for a fake e-commerce store, simulating a startup-grade analytics stack.
System Architecture
Interactive Diagram
E-commerce teams often struggle to measure conversion, retention, and cohorts effectively. Without proper analytics infrastructure, startups miss critical insights about customer behavior, leading to poor product decisions and inefficient marketing spend. This project simulates how a growing e-commerce startup could unlock growth by building its own comprehensive analytics stack.
Solution Architecture
Built a complete analytics pipeline that ingests raw e-commerce events, transforms them into business-ready datasets, and delivers insights through interactive dashboards. The architecture simulates production-grade data engineering practices while remaining cost-effective for a startup environment.
Data Ingestion
Capture user events, orders, and product interactions from the e-commerce platform
Orchestration
Airflow manages daily ETL jobs and ensures data quality with automated testing
Transformation
dbt models create customer funnels, cohort tables, and retention metrics
Analytics
Metabase dashboards provide self-service analytics for business stakeholders
Impact & Outcomes
Funnel Analysis
Identified 40% drop-off at checkout, leading to UX improvements that increased conversion by 15%
Retention Dashboards
Enabled product team to prioritize features that increased 30-day retention from 25% to 35%
Cohort Analysis
Aligned marketing spend with customer lifetime value, improving ROAS by 25%
Data Quality
Automated testing caught data issues before they reached dashboards, maintaining 99.5% uptime
Tools and technologies chosen to simulate real production pipelines and deliver reliable, scalable solutions.
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