EastView Marketing Dataset Analysis
Overview
A comprehensive data analysis project focused on EastView Marketing's dataset, utilizing root cause analysis techniques and developing key performance indicators (KPIs) to drive business insights and strategic decision-making.
Project Status
🟡 In Progress - Currently analyzing Excel datasets and developing visualization dashboards
Key Features
- Root Cause Analysis: Deep dive into marketing campaign performance issues
- KPI Development: Creating meaningful metrics for marketing effectiveness
- Excel Data Processing: Advanced analysis of marketing datasets
- Statistical Analysis: Correlation analysis and trend identification
- Data Visualization: Interactive charts and dashboards for stakeholders
- Performance Metrics: ROI analysis and campaign optimization insights
Technologies Used
- Data Analysis: Python 3.9+, Pandas, NumPy for data manipulation
- Visualization: Matplotlib, Seaborn for statistical plots and charts
- Data Processing: Excel integration and CSV data handling
- Statistical Analysis: SciPy for advanced statistical computations
- Notebook Environment: Jupyter for interactive analysis and documentation
- Database: SQL for data querying and aggregation
Analysis Approach
The project follows a structured analytical methodology:
- Data Collection: Processing Excel datasets from EastView Marketing
- Data Cleaning: Handling missing values and data quality issues
- Exploratory Analysis: Understanding data patterns and distributions
- Root Cause Analysis: Identifying factors affecting marketing performance
- KPI Development: Creating actionable business metrics
- Visualization: Building charts and dashboards for stakeholder communication
Key Performance Indicators (KPIs)
- Campaign ROI: Return on investment for marketing campaigns
- Customer Acquisition Cost (CAC): Cost per new customer acquisition
- Conversion Rates: Lead to customer conversion metrics
- Customer Lifetime Value (CLV): Long-term customer value analysis
- Marketing Attribution: Channel performance and contribution analysis
- Engagement Metrics: Customer interaction and response rates
Root Cause Analysis Findings
- Channel Performance: Identifying underperforming marketing channels
- Seasonal Trends: Understanding temporal patterns in customer behavior
- Demographic Insights: Customer segmentation and targeting opportunities
- Budget Allocation: Optimizing marketing spend across channels
- Campaign Effectiveness: Measuring and improving campaign performance
Deliverables
- Interactive Dashboards: Real-time visualization of marketing metrics
- Statistical Reports: Comprehensive analysis with actionable insights
- Excel Integration: Automated data processing and reporting
- Recommendations: Strategic recommendations for marketing optimization
- Performance Monitoring: Ongoing KPI tracking and alerting system