https://github.com/filippodanesi/seo-traffic-forecasting
Python-based Streamlit app for forecasting SEO traffic and analytics metrics using Prophet. Supports both Google Search Console and GA4 data with interactive visualizations and exportable reports.
https://github.com/filippodanesi/seo-traffic-forecasting
analytics data-science data-visualization forecasting google-analytics google-search-console machine-learning prophet python seo streamlit time-series-analysis
Last synced: 4 months ago
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Python-based Streamlit app for forecasting SEO traffic and analytics metrics using Prophet. Supports both Google Search Console and GA4 data with interactive visualizations and exportable reports.
- Host: GitHub
- URL: https://github.com/filippodanesi/seo-traffic-forecasting
- Owner: filippodanesi
- Created: 2025-02-17T09:34:59.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-02-17T10:13:39.000Z (4 months ago)
- Last Synced: 2025-02-17T10:31:50.348Z (4 months ago)
- Topics: analytics, data-science, data-visualization, forecasting, google-analytics, google-search-console, machine-learning, prophet, python, seo, streamlit, time-series-analysis
- Language: Python
- Homepage:
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# SEO Traffic Forecasting Tool
A Streamlit-based tool for forecasting SEO traffic and analytics metrics using [Facebook's Prophet algorithm](https://facebook.github.io/prophet/).
## Features
- Support for both Google Search Console and Google Analytics 4 data
- Monthly traffic forecasting up to 24 months ahead
- Interactive visualizations with confidence intervals
- Exportable reports in Excel format
- Customizable visualization options
## Requirements
- Python 3.8+
- Dependencies listed in `requirements.txt`
## Installation
1. Clone the repository:
```bash
git clone https://github.com/filippodanesi/seo-traffic-forecasting.git
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
## Usage
1. Run the application:
```bash
streamlit run app.py
```
2. Upload your data:
- For GSC: Export Performance data (last 16 months recommended)
- For GA4: Export Acquisition Overview data (minimum 8 weeks recommended)
3. Configure forecast settings in the sidebar
4. Generate and explore forecasts
## Data Format Requirements
### Google Search Console
- Required columns: Date, Clicks, Impressions, Position, CTR
- Minimum 14 months of historical data recommended
### Google Analytics 4
- Required columns: **Nth week**, **Active users**
- Minimum 8 weeks of historical data recommended
## License
MIT