Google has provided programmatic access to the search queries data in Webmaster Tools with ‘Python’. The Python script for downloading search query data was brought by Google in December 2011 and now has new download options that make the data download highly more useful.
With this open source Python script from the webmaster-tools-downloads project, webmasters can now access their search queries data in CSV format. Google has clarified that the search queries data is not currently available via the Webmaster Tools API, and is being considered for the next API update. Here is the example Google gives as to how the search queries downloader Python script can be used to download search queries data and then upload it to a Google Spreadsheet in Google Docs.
“Example usage of the search queries downloader Python script:
- If Python is not already installed on your machine, download and install Python.
- Download and install the Google Data APIs Python Client Library.
- Create a folder and add the downloader.py script to the newly created folder.
- Copy the example-create-spreadsheet.py script to the same folder as downloader.py and edit it to replace the example values for “website,” “email” and “password” with valid values for your Webmaster Tools verified site.
- Open a Terminal window and run the example-create-spreadsheet.py script by entering "python example-create-spreadsheet.py" at the Terminal window command line: python example-create-spreadsheet.py
- Visit Google Docs to see a new spreadsheet containing your search queries data.”
Webmasters can set up these scripts to be run daily or monthly and can archive it for longer periods too. With search query chart data downloads, webmasters have access to information not easily available before. While viewing search query data, the chart in the user interface shows impression and click data per day. Prior to this, the detail has only been available if one hovered over a dot in the chart. But now, the detailed chart data available for download provides a greater understanding of the data.