This n8n workflow automates the process of scoring LinkedIn profiles based on their fit to your Ideal Customer Profile (ICP). The goal is to extract detailed information from a LinkedIn profile—such as name, job title, employer, location, connections, and about section—and assess the individual’s interest in AI, seniority, and technical depth. Using this data, the workflow calculates an ICP score that helps prioritize leads or segment prospects effectively.
The process begins with a trigger node, either a form submission or an execution from another workflow, which provides the LinkedIn profile URL and Airtop profile reference. Parameter nodes ensure the correct passing of these values downstream. The core node, an Airtop extraction service, queries the LinkedIn profile, requesting detailed information: personal details, professional data, and interest levels.
The Airtop node uses a prompt with specific scoring criteria for AI interest, technical depth, and seniority, assigning points accordingly. These criteria help to quantify the relevance of the profile to your ICP. The scores are then formatted and returned in a structured JSON output.
This workflow is valuable for sales and marketing teams aiming to qualify LinkedIn leads quickly, streamline prospect segmentation, and prioritize outreach efforts based on computed ICP scores. It can be integrated with CRM systems or used in batch processes to evaluate multiple profiles simultaneously.
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