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Finding relevant job opportunities on LinkedIn can be time-consuming, especially when searching for niche roles like fractional executives. In this article, we’ll explore how to automate this process using a combination of tools: Make.com, RSS.app, Airtable, and ChatGPT. This solution streamlines job posting discovery and shares them efficiently within a community platform, saving countless hours while ensuring timely updates.
The Problem
Manually searching LinkedIn for specific job opportunities is labour-intensive. For example, searching for “fractional” roles often yields over 1,200 results, many of which are irrelevant. Furthermore, job listings on LinkedIn can become outdated quickly, as applications close soon after posting. The challenge was twofold:
Efficiency: Automate job searches to save time.
Timeliness: Ensure the community receives fresh and relevant job opportunities promptly.
The Solution: Key Tools and Workflow
Tools Overview
Make.com: Automates the flow of data between different tools.
RSS.app: Converts web pages into RSS feeds for easy data extraction.
Airtable: Serves as a central database to store and manage job listings.
ChatGPT: Formats the job data into usable information.
Step-by-Step Workflow
Job Search Automation with RSS.app
Go to LinkedIn Jobs and search for roles with specific keywords (e.g., “fractional” in the United States).
Copy the search results URL into RSS.app to generate an RSS feed.
Apply filters in RSS.app to exclude duplicate posts and ensure only new, relevant jobs appear.
Building the Automation in Make.com
Set up the Scenario: Create a new scenario in Make.com and configure it to run every 12 hours.
RSS Feed Integration: Use the RSS.app feed as the first module in Make.com to retrieve job listings.
Filter Duplicates: Before adding new listings to Airtable, check if the job’s URL already exists in the database to avoid duplicates.
Store Data in Airtable: Extract the job title, summary, URL, and location from the RSS feed and input these into an Airtable database.
Enhancing Job Summaries with ChatGPT
Use Make.com’s HTTP module to visit the job posting URL and extract the job description.
Pass the extracted HTML content to ChatGPT via Make.com to generate a concise, one-paragraph summary.
Replace the raw HTML in Airtable with the refined summary.
Posting to the Community Platform
Use Zapier to monitor new Airtable records and automatically post job listings to the Better Mode community platform.
Include essential details such as the job title, URL, location, and summary in the community post.
Advanced Features
Geographical Filters: Set up separate RSS feeds for different locations (e.g., United States, Canada, United Kingdom) and route them through Make.com to consolidate all listings into Airtable.
Real-Time Updates: Configure the RSS feed to exclude posts older than 24 hours, ensuring fresh opportunities.
Scalable Setup: Easily replicate the process for other roles or industries by modifying search keywords and filters.
Benefits
Time Savings: Automates repetitive tasks, freeing up hours of manual work.
Improved Accuracy: Filters out irrelevant and duplicate posts, delivering only high-quality opportunities.
Enhanced Community Value: Provides members with timely and curated job postings, increasing engagement and satisfaction.
Conclusion
This automated workflow transforms the tedious process of searching for and sharing job opportunities into a seamless, efficient system. By leveraging tools like Make.com, RSS.app, Airtable, and Zapier, small business owners and community managers can focus on higher-value tasks while maintaining a vibrant, resourceful community. If you’d like to replicate this setup, check the link in the description to download the pre-built templates and get started immediately.