Tokopaedi E-Commerce — BigQuery SQL Analysis
End-to-end SQL analysis of the Tokopaedi e-commerce database (6 relational datasets) on BigQuery to optimize operational efficiency. Identified seasonal peaks, such as Rp 4.1B in Dec 2024 revenue, and multi-year inventory trends to drive data-backed marketing and stock management. Executed advanced SQL queries utilizing CTEs and Joins across 6 core tables to perform data cleaning, seasonal trend analysis, and multi-year inventory forecasting. Analyzed 4,399 transactions totaling Rp 19.83B in revenue for 2024 and measured conversion efficiency across 82,000+ organic funnel events. Identified the Play Store as the highest-converting organic channel (2.21%) and established a restock priority roadmap for fast-moving categories (F&B and Fashion) to prevent stockouts.
View ProjectTokopaedi e-commerce operates on 6 relational datasets; operational efficiency and stock management needed data-backed insights from seasonal and conversion patterns.
Optimize operational efficiency through seasonal peak identification, channel conversion analysis, and multi-year inventory trends for marketing and stock management.
End-to-end SQL analysis on BigQuery across 6 core tables: data cleaning, seasonal trend analysis, conversion funnel measurement (82K+ organic events), and multi-year inventory forecasting.
Analyzed 4,399 transactions totaling Rp 19.83B in 2024 revenue. Identified Rp 4.1B Dec peak; Play Store as highest-converting organic channel (2.21%). Established restock priority roadmap for fast-moving F&B and Fashion to prevent stockouts.
-- Channel conversion funnel
WITH funnel AS (
SELECT channel, COUNT(*) as events
FROM organic_events
GROUP BY channel
)
SELECT channel, events,
ROUND(100.0 * events / SUM(events) OVER (), 2) as pct
FROM funnel
ORDER BY pct DESC