Expected Revenue Calculator

A comprehensive Python tool for projecting and visualizing revenue growth based on different customer acquisition scenarios, including various revenue streams and one-time fees.

Features

• Multiple customer acquisition scenarios (1-6 customers per month)
• Detailed revenue breakdown by stream (Hosting, Premium, Web Dev Care, Analytics, SEO)
• Interactive visualizations with dual-axis charts
• Comprehensive Excel reports with auto-adjusted column widths
• Support for both recurring and one-time revenue streams
• Configurable probabilities for different service up-sells

Prerequisites

• Python 3.7+
• pip (Python package manager)

Installation

1. Clone the repository:

   git clone <repository-url>
   cd ExpectedRevenueCalculator

2. Install dependencies:

   pip install -r requirements.txt

Project Structure

• main.py: Main script to run the revenue calculator
• revenue_calculator.py: Core revenue calculation logic
• generate_charts.py: Visualization and chart generation
• excel.py: Excel report generation
• hidden_costs.py: Configuration for pricing, probabilities, and revenue streams
• output/: Directory containing generated charts and reports

Configuration

Revenue Streams

Modify hidden_costs.py to adjust:

• Base and premium hosting fees
• Setup fees
• Service probabilities and pricing
• Revenue stream configurations

Scenarios

Modify the scenarios dictionary in main.py to change the customer acquisition rates:

scenarios = {
    "1 customer per month": 1,
    "2 customers per month": 2,
    "3 customers per month": 3,
    "4 customers per month": 4,
    "6 customers per month": 6
}

Usage

Run the calculator:

python main.py

Output Files

• output/ directory will contain:
  • revenue_breakdown_*.png: Individual revenue breakdown charts for each scenario
  • revenue_comparison.png: Comparison of monthly revenue across all scenarios
  • cumulative_revenue_projection.png: Cumulative revenue projection by scenario
  • customer_revenue_breakdown.xlsx: Excel file with detailed revenue breakdown by scenario

Customization

Chart Styling

Modify generate_charts.py to adjust:

• Figure sizes and layouts
• Color schemes
• Line styles and markers
• Axis formatting and labels
• Legend position and styling

Revenue Streams

Update REVENUE_STREAMS in hidden_costs.py to add or modify revenue streams, including:

• Display names
• Colors
• Associated revenue calculations

Dependencies

• pandas: Data manipulation and Excel export
• matplotlib: Data visualization
• openpyxl: Excel file handling
• python-dotenv: Environment variable management
• numpy: Numerical operations

License

This project is for demonstration purposes. Please ensure you have the right to use and modify the code as needed for your specific use case.