€23.16 – €26.88
Methodology:
- Data Preprocessing: Missing values were handled using mean imputation for numerical data and mode imputation for categorical data. Outliers were identified and removed using the IQR method.
- Exploratory Data Analysis (EDA): Descriptive statistics and visualizations were employed to uncover trends in sales, campaign effectiveness, and customer behaviors.
- Statistical Analysis: Correlation analysis was used to identify relationships between marketing spend and sales volume. A linear regression model was built to quantify the impact of various factors on sales performance.
- Machine Learning Model: A Random Forest model was implemented to predict future sales based on historical trends and campaign variables.
