This Streamlit tool was developed to integrate Google Trends analysis with Google Search Console (GSC) performance data, enabling users to visualize trends for their top-performing GSC keywords. By leveraging Google's Trend API through the pytrends
library, this application processes up to 200 keywords, comparing their performance over specified timeframes and geographical settings. This unique approach provides valuable insights into keyword popularity trends, aiding in strategic decision-making for SEO and content marketing.
- Upload CSV files containing Google Search Console performance data.
- Customize analysis by selecting the number of queries, pause duration between calls, timeframe, and geographical focus.
- Automatically sorts keywords based on selected performance metrics (Clicks, Impressions, CTR, Position).
- Visual representation of keyword trends (Up, Down, Flat, N/A) based on historical data.
- Downloadable CSV file with the trend analysis results.
- Export your Google Search Console performance data (Impressions, CTR, Position) and prepare a
Queries.csv
file from the zip file. - Ensure all dependencies are installed from
requirements.txt
. - Launch the Streamlit application using the command:
streamlit run streamlit_app.py
- Upload your
Queries.csv
file through the Streamlit user interface. - Customize your analysis parameters and click on "Run Analysis" to view and download the trend analysis.
pytrends
: A Python library for accessing Google Trends API for keyword trend data.pandas
: An open-source data manipulation and analysis library.streamlit
: An open-source app framework for Machine Learning and Data Science projects.
To install the necessary dependencies, run:
pip install -r requirements.txt
This tool extends the capabilities of Google Search Console data analysis by integrating with Google Trends, offering a streamlined way to monitor keyword performance trends over time. Developed with the aim of enhancing SEO strategies and content planning, this application stands as a practical solution for digital marketers and content creators.
Author: Greg Bernhardt | Friends: importSEM and Physics Forums