Data Preparation and Organization

Data preparation is the foundation of analytics; without clean, organized, and complete data, every insight you produce will be unreliable.

Stages of Data Preparation

1. Consolidate your data sources: gather data from all platforms (GA4, CRM, ad platforms, e-commerce tools) into one structured place;
2. Clean up the data: remove duplicates, fix typos, align formats, and standardize naming across all files and platforms;
3. Check for missing or broken tracking: verify that UTMs, pixels, events, and integrations are working so no data gets lost;
4. Use AI to speed up cleaning and pattern detection: leverage tools like ChatGPT ADA, MonkeyLearn, or Google Sheets AI to automate repetitive cleanup tasks;
5. Build a long-term organizational system: create naming conventions, folder hierarchies, and documentation to keep data structured and understandable over time.