I built an Excel tracker to capture pop‑up/street‑sale activity and turn it into a usable dashboard without needing any extra tools on the street. The design goal was simple: fast entry in the field, clean enough data for real analysis later.
Highlights:
- Two-table structure: Outings (one row per outing) + Sales (one row per transaction line item)
- Dropdown validation lists to reduce messy categories
- Auto-calculated metrics: duration, transactions, gross sales, taxes, and net profit after costs
- Qualitative fields (objections, what worked) to connect the numbers to behavior
Download: Art_Sales_Data_Analysis.xlsx
Docs & code: Data dictionary · Python EDA script · Jupyter notebook
Next steps: export to CSV + run Python EDA (venue ranking, payment mix, profit per hour, and seasonal trends).