Monitors input keywords, creates batched Google-page queries via SerpAPI, checks results, logs profiles to Google Sheets, and notifies you when complete.
From keyword input to final logging, the AI agent fetches public LinkedIn profiles from Google search results across multiple pages, extracts profile URLs and full names, and logs them with the original keywords into Google Sheets. It searches across multiple pages, formats queries, and handles pagination to ensure a complete dataset. It notifies you when the run is finished and provides an auditable trail for outreach campaigns.
Automates end-to-end collection and logging of LinkedIn profiles from Google search results.
Accepts keywords and page count via a user form.
Formats keywords into Google-ready queries for better relevance.
Builds a batched list of pages to process.
Queries SerpAPI for each page with site:linkedin.com/in and a location filter.
Parses results and handles no-results scenarios gracefully.
Appends results to Google Sheets with Date, Profile URL, Full name, and Keywords.
Before: manual LinkedIn profile gathering is slow, inconsistent, and hard to audit. After: automated multi-page searches reliably log results to Sheets, with date and keyword metadata and a clear completion signal.
A simple 3-step flow that non-technical readers can follow.
User submits keywords and pages via a form to trigger the AI agent.
Formats the keywords, creates a paginated page list, and runs SerpAPI per batch.
Parses results, extracts full names, and appends data to Google Sheets before finishing.
One realistic scenario.
A recruiter wants to source Java developers in Warsaw. They enter keywords 'Java' and 'Warsaw' with Pages to fetch set to 2. The AI agent runs, collects approximately 20 profiles across two Google result pages, and writes Date, Profile URL, Full name, and Keywords to the connected Google Sheet. The sheet now contains an auditable list that can be used for outreach and tracking.
Roles that gain from automated LinkedIn profile collection.
To quickly source candidate pipelines from public profiles.
To expand regional talent pools with keyword-based searches.
To identify targeted leads for outreach from public profiles.
To validate the presence of suitable public profiles for open roles.
To assemble data for sourcing metrics and impact analysis.
To deliver client-ready lists quickly with traceable data.
Core tools used inside the AI agent workflow.
Queries Google with site:linkedin.com/in, keyword groups, and location; uses start offsets for paging.
Appends rows with Date, Profile URL, Full name, and Keywords for each result batch.
Practical scenarios to apply the AI agent for sourcing and outreach.
Practical, real concerns answered.
The agent captures the Date, Public LinkedIn Profile URL, Full name, and the original Keywords. This data is written to your configured Google Sheet, row by row, with each batch appended sequentially. The process maintains an auditable trail by recording the run timestamp and the keywords that produced each result. You can expand the sheet to include optional fields as needed and manage access permissions through Google Sheets settings.
Yes. You can adjust the location parameter in SerpAPI and change the keywords in the input form. The agent supports multiple keywords per run and can paginate across several Google search result pages. If you need other regions, you can modify the location field to reflect the desired area. Changes are applied on the next run, keeping your existing data intact.
Pagination creates successive search batches by adjusting the start offset (e.g., 0, 10, 20) so results from multiple Google pages are retrieved. Each batch is processed in sequence, ensuring comprehensive coverage of the specified pages. If a batch yields no results, that branch stops gracefully and logs the outcome. The final completion notification confirms when all pages have been processed.
The agent writes results to a single Google Sheet with clear per-run metadata. To prevent duplicates, you can add a de-duplication step in Sheets or implement a pre-check in the workflow to skip URLs that already exist. The base flow records the run and results, making it straightforward to identify and remove duplicates if needed. Regular audits help maintain data quality over time.
If a batch returns no results, the agent logs an entry indicating no profiles were found for that batch and continues with any remaining batches. The final notification still triggers to confirm the overall run status. This behavior prevents stalls and keeps you informed about data availability. You can set up alerts for no-result cases to trigger follow-up actions.
The agent relies on public LinkedIn profiles surfaced through Google search. It does not access restricted data. Always respect platform terms of service and local privacy laws when using collected data for outreach. Use the data responsibly, limit distribution, and avoid scraping sensitive information. Maintain an auditable log to demonstrate compliant usage and intentions.
Import the agent template into your n8n instance, connect SerpAPI and Google Sheets credentials, and point the sheet node to your target spreadsheet. Configure the form to supply keywords and the number of pages to fetch, then activate the AI agent. You can test with a small set of keywords to verify formatting and data mapping before broader use. Ensure your Google Sheet has the correct headers and permissions for writes.
Monitors input keywords, creates batched Google-page queries via SerpAPI, checks results, logs profiles to Google Sheets, and notifies you when complete.
