FractalFB - Facebook Ad Analysis and Reporting Tool

Overview

FractalFB is a powerful Python-based tool for analyzing Facebook ad performance data and generating comprehensive PDF reports with visualizations and actionable insights. It processes data from Facebook Ads Manager and evaluates performance against user-defined KPI ranges.

Features

• Automated PDF report generation with detailed ad performance analysis
• Interactive funnel visualizations and performance graphs
• Historical performance tracking and trend analysis
• Customizable KPI ranges and performance metrics
• Automated recommendations for ad optimization
• Sphinx documentation generation

Installation

pip install -r requirements.txt

Requirements

• Python 3.x
• pandas
• PyYAML
• FPDF
• Pillow
• Sphinx (for documentation)

Usage

Basic Usage

python app.py --csv facebook_ads.csv --yaml settings.yaml --output report.pdf

Generate Documentation

python app.py --generate-docs --docs-dir docs

Command Line Arguments

• --csv: Path to Facebook ads CSV file (default: facebook_ads.csv)
• --yaml: Path to settings YAML file (default: settings.yaml)
• --output: Output PDF file path (default: kpi_report.pdf)
• --database: Path to YAML database file (default: reports_database.yaml)
• --generate-docs: Generate Sphinx documentation
• --docs-dir: Directory for Sphinx documentation (default: docs)

Configuration

Create a settings.yaml file with your organization name and KPI ranges:

organization: "Your Organization Name"
kpi_ranges:
  "Quality ranking":
    min: 7
    max: 10
  "CTR (link click-through rate)":
    min: 0.5
    max: 3
  "Cost per results":
    min: 0.01
    max: 30

Output

The tool generates:

1. Comprehensive PDF reports with:
   • KPI analysis
   • Funnel visualizations
   • Performance graphs
   • Recommendations
2. Historical performance database
3. Sphinx documentation

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Copyright

Copyright © Michael Hoyt 2024. All Rights Reserved.

Support

For support, please open an issue in the GitHub repository.

Authors

• Michael Hoyt

Acknowledgments

Special thanks to all contributors and users of FractalFB.