Google Analytics API
Automated Python pipeline to extract website traffic metrics from the Google Analytics Reporting API and store them as structured JSON and CSV files for further analysis.
Problem
Marketing analysts needed a reliable and repeatable process to extract web performance data from Google Analytics. Manual downloads through the GA interface were inefficient, prone to human error, and limited by date range constraints.
Solution
Built a Python script that connects to the Google Analytics Reporting API v4, retrieves dimensions and metrics such as users, sessions, bounce rate, and pageviews, and exports them into clean CSV files. The process supports parameterized date ranges and automatic folder organization for historical data storage.
Impact
Reduced manual data collection time from hours to minutes, enabling faster analytics and integration with external BI tools such as Power BI or Looker Studio. Provided a reproducible data source for marketing performance tracking.
Tech Stack Used
Key Challenges & Learnings
- Configuring secure API access with OAuth 2.0 credentials
- Dealing with Google Analytics API quotas and pagination limits
- Structuring the extracted data for easy analysis while maintaining performance across multiple metrics
- Improved skills in using REST APIs for data extraction and automation
- Learned practical handling of authentication and API pagination with Google APIs
- Developed a modular and reusable approach to exporting and managing data from external sources