Sales & Estimation
LinkedIn Lead Automation w/ Horizon Data Wave
This workflow automates LinkedIn lead generation and outreach, from identifying leads based on an Ideal Customer Profile (ICP) to researching company websites, news, posts, and finally sending connection requests and messages. It uses OpenAI and Google Sheets for data processing…
Built · ~4 hours saved per week
Sales and marketing teams
This workflow automates LinkedIn lead generation. It finds leads, enriches their data, scores them, and automates connection requests and initial messages.
1. Set up API access for OpenAI. 2. Set up API access for Google Drive. 3. Set up an API key for horizondatawave.ai. 4. Connect your LinkedIn account.
OpenAI API access, Google Drive access, Horizon Data Wave API key, LinkedIn account.
You can customize the prompt for AI agents to tailor lead search, data enrichment details, lead scoring criteria, and automated message content.
Key Technologies: n8n,OpenAI (GPT-4o),Google Sheets,Horizon Data Wave API (LinkedIn Sales Navigator, Company Website, Google Search Integration)
Automation Value: Automates lead discovery on LinkedIn. Enriches lead data with company websites, news, and posts. Scores leads to prioritize outreach efforts. Automates LinkedIn connection requests. Automates initial messages to connected leads. Maintains a centralized lead database in Google Sheets.
Best Practices: Modular Design: The workflow is broken into logical sections (Finding Leads, Data Enrichment, Scoring, Communication) using sticky notes for clarity. Error Handling: Many nodes utilize retryOnFail: true and onError: "continueRegularOutput", ensuring the workflow is reliable and can handle transient issues without stopping. Rate Limiting Consideration: The "Limit" node (Node 52) and waitBetweenTries parameters in Google Sheets nodes show an awareness of API rate limits, especially important for LinkedIn interactions. AI Integration: AI is strategically used for complex tasks like translating ICP to search parameters, summarizing unstructured text, and scoring leads, automating cognitive tasks. User Customization: Sticky notes explicitly guide users on where to modify AI prompts and workflow logic to align with specific business needs. Data Centralization: Using Google Sheets as a central database for lead information simplifies data management and provides a single source of truth. Scheduled Automation: Utilizing Schedule Trigger nodes ensures that lead generation and communication run consistently without manual intervention.
Tags: Chatbot, Data Transformation, Lead Nurturing, Lead Acquisition, AI Automation, Multi-Agent Chain