The LinkedIn School Scraper automation allows you to gather detailed information about schools and universities listed on LinkedIn, including alumni, program offerings, and notable departments. This tool is valuable for recruiters, educational institutions, and marketers who want to analyze school data, build alumni networks, or track educational trends. Follow this guide to configure the automation, with options to export data to Google Sheets or CSV for easy management and analysis.

Step 1: Log in to the TexAu App and Locate the Automation

Log in to your TexAu account at v2-prod.texau.com. In the Automation Store, use the search bar to locate LinkedIn School Scraper for a quick start.

Screenshot Suggestion: Show the Automation Store screen with "LinkedIn School Scraper" entered in the search bar.

Step 2: Connect to LinkedIn with TexAu

To access LinkedIn school data, connect your LinkedIn account with TexAu. Click Add Account and select LinkedIn. TexAu provides two secure connection options:

Magic Link: Sends a secure link to your email for easy login without manually entering cookies.
Add Account: Uses TexAu’s built-in browser extension for direct connection, simplifying setup.

Tip: Magic Link provides a quick, secure login method that bypasses cookie handling.

Screenshot Suggestion: Show the LinkedIn connection options, highlighting both Magic Link and Add Account choices.

Step 3: Select Your Input Source

With LinkedIn connected, define the input source to specify the schools you want to gather data from. TexAu allows you to use a single LinkedIn School URL or upload multiple URLs through Google Sheets or CSV.

Single School URL: For a quick, single-school extraction, enter the LinkedIn School URL. This option is useful for analyzing data from one institution.
Google Sheet or CSV for Multiple Schools: For collecting data on multiple schools, use a Google Sheet or CSV file. List each LinkedIn School URL in a separate row, then paste the Google Sheet URL or upload the CSV file in TexAu. This setup enables data extraction from multiple institutions in one automation run.
Filtering Options: For more targeted scraping, apply filters such as location or school size. This helps you focus on schools within specific regions or with certain enrollment sizes, ensuring data aligns with your project goals.

Screenshot Suggestion: Display the input source options screen with LinkedIn School URL, Google Sheet, and CSV options highlighted.

Step 4: Schedule the Automation (Optional)

If you’d like the automation to run at specific intervals, use TexAu’s scheduling feature. Click Schedule to set the date and time, or configure a Recurrence Frequency to repeat the automation:

At Regular Intervals (e.g., every 24 hours or every week)
Once
Every Day
On Specific Days of the Week (e.g., every Monday and Thursday)
On Specific Days of the Month (e.g., the 10th and 20th)
On Specific Dates (e.g., March 1)

Scheduling is ideal for ongoing data collection on schools, allowing you to capture updates over time.

Screenshot Suggestion: Show the scheduling interface with options for selecting start time and recurrence frequency.

Step 5: Set an Iteration Delay (Optional)

To simulate natural browsing and avoid LinkedIn’s rate limits, set an Iteration Delay to control the interval between each school profile extraction. Configure both Minimum Delay and Maximum Delay values to create variability, helping avoid detection. Adjust the delay in seconds, minutes, hours, or days, depending on your needs.

Screenshot Suggestion: Include a screenshot of the Iteration Delay settings, showing Minimum Delay, Maximum Delay, and time unit options.

Step 6: Choose Your Output Mode (Optional)

In Output Mode, choose how you’d like to save and organize the extracted data. You can export data to Google Sheets or a CSV file for flexible analysis and sharing.

Export Options: Choose Google Sheets or CSV file for data export. If you select Google Sheets, link your Google account to enable a direct export to Google Drive.
Output Management:
- Append (Default): Adds each new dataset to the existing file, allowing you to build a continuous database of schools.
- Split: Creates a new file for each run, helpful for organizing data by different automation sessions.
- Overwrite: Replaces old data with the latest extraction, ideal if you only need the most recent school information.
Duplicate Management: Use Deduplicate to automatically remove duplicate entries, keeping your dataset organized and accurate.

Tip: Google Sheets is ideal for collaborative analysis, as it enables real-time sharing with your team.

Screenshot Suggestion: Show the output mode options screen with Google Sheets, CSV, and Deduplicate options highlighted.

Step 7: Run the Automation on Cloud or Desktop

Once configurations are complete, click Run to start the automation. Choose between Cloud or Desktop mode for executing the automation:

Cloud: Runs the automation from TexAu’s servers, ideal for hands-free operation.
Desktop: Run the automation locally on your device if you prefer to use your own IP address, which can be helpful for simulating manual activity.

Tip: Running automations on Desktop mode saves cloud runtime costs and provides greater control over the task.

Screenshot Suggestion: Show the Run button with Cloud and Desktop options visible.

Step 8: Access the Data from the Data Store

After the automation completes, go to the Data Store section in TexAu to access the extracted school data. Locate the LinkedIn School Scraper automation and click See Data to view or download the results.

Screenshot Suggestion: Display the Data Store screen with the “See Data” button highlighted.

The LinkedIn School Scraper automation simplifies gathering school data from LinkedIn, helping recruiters, educational institutions, and marketers collect and analyze educational insights. With scheduling, bulk input options, and easy export to Google Sheets or CSV, this tool enables efficient data collection on schools and alumni networks, supporting targeted outreach and research projects.

LinkedIn School Scraper