Content Performance Tracker
My role:
Automation Engineer
Information Architecture
Information Architecture
Information Architecture
Information Architecture
Information Architecture
Information Architecture
Information Architecture
Information Architecture
Information Architecture
Information Architecture
Information Architecture
Information Architecture
Task: A marketing team needed to identify which creative attributes in ads actually drive performance and what patterns (signals) in the content works better that others.
Process: I designed a structured system where each creative asset is tagged against a defined taxonomy — visual attributes, geography and more — and joined with performance data from Meta Ads Manager (CPA, CPM, CTR, spend, custom KPIs).
On top of this data layer, I built a custom interface for hypothesis testing and signal analysis. The system includes:
Content tagging and creative taxonomy management
Custom business metrics and benchmark logic
A/B comparison across any tag combination
Flexible filter settings for data quality control
Gemini AI integration for performance interpretation and creative insights
Result: Marketing managers can go from a question to a documented, data-backed answer in under five minutes, without involving analysts or additional tools. The team now has a working instrument for creative strategy, built on a lightweight system during couple of weeks.
Information Architecture
Information Architecture
Information Architecture
Information Architecture
Information Architecture
