Overview
The Marketing Funnel Analysis project explores the journey of leads through the marketing funnel, from qualification to deal closure. It aims to optimize the lead-to-deal conversion process by analyzing trends, identifying bottlenecks, and improving marketing and sales alignment.
Project Objectives
- Combine data: Marketing-qualified leads (MQLs) and closed deals for comprehensive funnel analysis.
- Identify KPIs: Conversion rates and drop-off points in the funnel.
- Visualize performance: Using treemaps, bar charts, and funnel charts.
- Provide insights: Recommendations to reduce drop-off and improve conversions.
Technologies Used
- Programming Languages: Python
- Libraries: Pandas, Matplotlib, Squarify
- Database: SQLite3
Insights
- Identify bottlenecks: Stages with the highest drop-off rates.
- Highlight lead quality: Specific sources with better performance.
- Demonstrate success: Faster closures correlate with improved success rates.
Recommendations
- Prioritize leads: Focus on high-conversion sources.
- Streamline processes: Improve progression criteria for MQLs.
- Foster collaboration: Align marketing and sales for better outcomes.
Next Steps
- Develop predictive models: Forecast funnel performance.
- Real-time monitoring: Build a dashboard to track metrics.
- Regular strategy updates: Ensure alignment between teams.