Project Overview & Goals:
This project analyzed the business performance of the Google Merchandise Store from Nov. 2020 to Jan. 2021 using GA4 e-commerce data. The goal was to evaluate how effectively the store converted traffic into revenue and to identify opportunities to improve customer engagement and revenue growth.
Key Metrics:
Revenue, Spending, ROI, Impressions, CTR, Conversions
Data Models:
Analytical Tools:
BigQuery, SQL, Power BI
Project Descriptions:
This project analyzed Google Merchandise Store GA4 e-commerce data to evaluate revenue performance, traffic quality, customer behavior, and marketing effectiveness. I used BigQuery SQL to extract GA4 event, item, campaign, transaction, and customer-level data, then used SQL Server to clean, standardize, and transform the data. SQL processes included event name simplification, campaign/channel standardization, combined table creation, funnel tables by channel and price band, cohort analysis, customer lifespan metrics, and RFEM-based customer segmentation.
Key KPIs included total revenue, sessions, purchases, AOV, session conversion rate, revenue per customer, and customer lifespan. The final Power BI dashboard highlighted revenue performance, channel contributions, funnel drop-off, customer value, and segment-level opportunities.
SQL Queries & Data Preparation:
Clean, transform, validate, and analyze data.