Google Maps Lead Generation & Enrichment Workflow for MSP Business Development As the Business Development Director for a multi-MSP portfolio, one of my biggest challenges is consistently sourcing, cleaning, and organizing new lead data across multiple regions. I wanted to share a two-part workflow I recently built in n8n that has streamlined the entire process and provided me with a scalable system for lead generation, enrichment, and outreach automation. Part 1: Lead Scraping & Upload - Starts with a form submission where I specify search terms (e.g., Law Firm, Legal, Attorney) and a location. - Runs an Apify Google Maps Scraper actor to pull company data and enriched contact information (emails, LinkedIn, etc.). - Includes a dynamic wait step (user-specified) since large searches can take several minutes. - Once completed, the dataset is retrieved, converted into a JSON file, and uploaded into a watched Google Drive folder. Part 2: Cleaning & Airtable Ingestion - A Google Drive trigger detects new files in the watched folder. - The file is downloaded, extracted, and passed to a cleaning & formatting code node, which strips non-essential data and maps the records into an Airtable-ready schema. - A routing node directs leads to the correct Airtable table based on business unit/territory - Records are upserted into the LEADS base in Airtable, and a Slack success message confirms completion for each territory. The Use Case We operate multiple MSPs across different regions, and our sales strategy relies heavily on targeting both geographies and industries/verticals. - This workflow allows us to organize leads by territory so each MSP business unit has its own pool of opportunities. - At the same time, we can tag and filter by industry verticals (e.g., Legal, Medical, Manufacturing, Non-Profit, CMMC-focused clients), which lets us prioritize the more profitable markets in the MSP space. - By combining geographic and industry-based segmentation, we can build highly targeted outreach campaigns that maximize ROI.

I wanted to share a workflow I recently built that combines n8n's automation capabilities with AI to create a fully autonomous SEO reporting system. Core Components: 1. Trigger & Data Collection: 2. AI Analysis: 3. Output & Notification: Implementation Details: The agent prompt is the heart of this workflow. It contains detailed instructions for data analysis, insight generation, and report formatting. I structured it to make tool calling explicit and sequential, which greatly improved reliability. The prompt was built on my prompt builder https://www.ageniusailabs.com/agentic-ai-agent-prompt-builder-agenius-ai-labs-v2 For document formatting, I implemented a template-based approach where the agent populates predefined sections while maintaining flexibility for new insights. This ensures consistency while allowing for custom recommendations. Regarding token usage, the GPT-4o-mini model proved sufficient for SEO analysis tasks while keeping costs manageable. The workflow processes data in batches to avoid token limitations. The workflow's architecture is built with flexibility in mind - you can easily add or remove data sources, modify report structures, or change the notification system without affecting other components. This project demonstrates how n8n can serve as an enterprise-grade orchestration layer for AI agents, creating genuinely autonomous business processes that deliver consistent, high-quality outputs with zero human intervention. The entire solution can be deployed on Azure, AWS, or other enterprise platforms for organizations with specific security or compliance requirements.

For a deeper discussion around MCP Servers and building AI Agents, let's chat here. In this video, I walk you through everything you need to know about connecting to MCP servers in n8n. From spinning up a self-hosted instance to installing the MCP community node, I break it all down step by step. You'll learn how to connect to any MCP server, set them up as tools, and understand the current limitations and issues you might run into. P.S., you can download the JSON workflow, but keep in mind you will need to self-host and install the MCP community node yourself :)

I am having a difficult time setting up my enterprise level credentials. For instance my company's GSuite. Could anyone assist me with this?

We've implemented an efficient workflow that automates employee biography creation using N8N as a proof of concept. The system operates as follows: when new hires submit information through a Google Form (included as part of their onboarding process), our workflow detects the entry, extracts data from their social profiles (LinkedIn, Facebook, and other platforms provided in the form) via web scraping, and combines it with their questionnaire responses. The core functionality leverages an AI writing assistant that generates professional biographies while maintaining consistent brand voice through our RAG database of previously approved bios. Each newly approved biography is indexed back into this database, creating a self-improving system. This approach is particularly valuable for this company, which maintains a very specific brand voice across its six global offices in London, Los Angeles, Shanghai, Singapore, Austin (TX), and Colorado. The workflow manages the entire process from initial data collection to final document creation in Google Docs, including review processes and approval tracking. Finalized bios are automatically indexed in our knowledge base for future reference. Currently built on Google Workspace, we plan to port this proof of concept to the Microsoft ecosystem for production, utilizing Power Automate, SharePoint, and Microsoft Graph API for integration with enterprise systems. This solution significantly reduces the time required to create professional biographies while ensuring consistent quality and brand alignment across all employee profiles.