A comprehensive statistical analysis and interactive dashboard for evaluating the effectiveness of three different marketing promotions for a fast-food chain's new menu item.
This project analyzes a 4-week A/B test across multiple markets to determine which of three promotional campaigns drives the highest sales performance.
- Promotion 1 shows the strongest performance with highest average sales
- Statistically significant differences between promotions (ANOVA p < 0.001)
- Revenue lift opportunity of $10.77k by choosing optimal promotion
- Python - Core analysis
- Streamlit - Interactive dashboard
- Plotly - Data visualizations
- SciPy/Statsmodels - Statistical testing
- Pandas - Data manipulation
- One-Way ANOVA - Compare means across three promotions
- Tukey HSD Post-hoc - Identify specific promotion differences
- Effect Size Analysis - Measure practical significance
- Descriptive Statistics - Summary metrics by promotion
This framework enables data-driven marketing decisions by:
- Quantifying promotional effectiveness
- Providing statistical confidence in results
- Identifying optimal resource allocation
- Supporting scalable testing methodologies