Project Overview:

This project analyzed the business performance of the Google Merchandise Store using GA4 e-commerce data. The goal was to evaluate how effectively the store converted traffic into revenue and to identify opportunities to improve marketing performance and revenue growth.

Project Goals:

Give an accurate high-level view on the company’s performance across different regions and channels.

Give some evident based recommendation for future business strategies.

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. I analyzed performance by marketing channel, country, device, product, and customer to identify revenue drivers and traffic quality differences. The final Power BI dashboard highlighted revenue trends, funnel drop-off, product performance, customer value, and segment-level opportunities.

Business Insights Reporting & Dashboards:

Future Recommendations:

Rebalance Budget Allocation

Reallocate investments away from underperforming, high-spend campaigns. Focus on scaling Efficient Winners to drive better return on investment (ROI) and overall efficiency.

Refine Targeting & Improve Relevance

Future strategies should prioritize refining audience targeting, improving landing page experience, and optimizing ad relevance to shift more campaigns into the high-efficiency (top-right) quadrant.