Workflow Templates

Smart Supplier Health Monitor with ScrapeGraphAI Risk Detection and Multi-Channel Alerts 🎯 Target Audience Procurement managers and directors Supply chain risk analysts CFOs and financial controllers Vendor management teams Enterprise risk managers Operations managers Contract administrators Business continuity planners 🚀 Problem Statement Manual supplier monitoring is reactive and time-consuming, often missing early warning signs of financial distress that could disrupt your supply chain. This template solves the challenge of proactive supplier health surveillance by automatically monitoring financial indicators, news sentiment, and market conditions to predict supplier risks before they impact your business operations. 🔧 How it Works This workflow automatically monitors your critical suppliers' financial health using AI-powered web scraping, analyzes multiple risk factors, identifies alternative suppliers when needed, and sends intelligent alerts through multiple channels to ensure your procurement team can act quickly on emerging risks. Key Components Weekly Health Check Scheduler - Automated trigger based on supplier criticality levels Supplier Database Loader - Dynamic supplier portfolio management with risk-based monitoring frequency ScrapeGraphAI Website Analyzer - AI-powered extraction of financial health indicators from company websites Financial News Scraper - Intelligent monitoring of financial news and sentiment analysis Advanced Risk Scorer - Industry-adjusted risk calculation with failure probability modeling Alternative Supplier Finder - Automated identification and ranking of backup suppliers Multi-Channel Alert System - Email, Slack, and API notifications with escalation rules 📊 Risk Analysis Specifications The template performs comprehensive financial health analysis with the following parameters: | Risk Factor | Weight | Score Impact | Description | |-------------|--------|--------------|-------------| | Financial Issues | 40% | +0-24 points | Revenue decline, debt levels, cash flow problems | | Operational Risks | 30% | +0-18 points | Management changes, restructuring, capacity issues | | Market Risks | 20% | +0-12 points | Industry disruption, regulatory changes, competition | | Reputational Risks | 10% | +0-6 points | Negative news, legal issues, public sentiment | Industry Risk Multipliers: Technology: 1.1x (Higher volatility) Manufacturing: 1.0x (Baseline) Energy: 1.2x (Regulatory risks) Financial: 1.3x (Market sensitivity) Logistics: 0.9x (Generally stable) Risk Levels & Actions: Critical Risk**: Score ≥ 75 (CEO/CFO escalation, immediate transition planning) High Risk**: Score ≥ 55 (Procurement director escalation, backup activation) Medium Risk**: Score ≥ 35 (Manager review, increased monitoring) Low Risk**: Score < 35 (Standard monitoring) 🏢 Supplier Management Features | Feature | Critical Suppliers | High Priority | Medium Priority | |---------|-------------------|---------------|-----------------| | Monitoring Frequency | Weekly | Bi-weekly | Monthly | | Risk Threshold | 35+ points | 40+ points | 50+ points | | Alert Recipients | C-Level + Directors | Directors + Managers | Managers only | | Alternative Suppliers | 3+ pre-qualified | 2+ identified | 1+ researched | | Transition Timeline | 24-48 hours | 1-2 weeks | 1-3 months | 🛠️ Setup Instructions Estimated setup time: 25-30 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Gmail account for email alerts (or alternative email service) Slack workspace with webhook or bot token Supplier database or CRM system API access Basic understanding of procurement processes Step-by-Step Configuration 1. Configure ScrapeGraphAI Credentials Sign up for ScrapeGraphAI API account Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials with your API key Test the connection to ensure proper functionality 2. Set up Email Integration Add Gmail OAuth2 credentials in n8n Configure sender email and authentication Test email delivery with sample message Set up email templates for different risk levels 3. Configure Slack Integration Create Slack webhook URL or bot token Add Slack credentials to n8n Configure target channels for different alert types Customize Slack message formatting and buttons 4. Load Supplier Database Update the "Supplier Database Loader" node with your supplier data Configure supplier categories, contract values, and criticality levels Set monitoring frequencies based on supplier importance Add supplier website URLs and contact information 5. Customize Risk Parameters Adjust industry risk multipliers for your business context Modify risk scoring thresholds based on risk tolerance Configure economic factor adjustments Set failure probability calculation parameters 6. Configure Alternative Supplier Database Populate the alternative supplier database in the "Alternative Supplier Finder" node Add supplier ratings, capacities, and specialties Configure geographic coverage and certification requirements Set suitability scoring parameters 7. Set up Procurement System Integration Configure the procurement system webhook endpoint Add API authentication credentials Test webhook payload delivery Set up automated data synchronization 8. Test and Validate Run test scenarios with sample supplier data Verify ScrapeGraphAI extraction accuracy Check risk scoring calculations and thresholds Confirm all alert channels are working properly Test alternative supplier recommendations 🔄 Workflow Customization Options Modify Risk Analysis Add custom risk indicators specific to your industry Implement sector-specific economic adjustments Configure contract-specific risk factors Add ESG (Environmental, Social, Governance) scoring Extend Data Sources Integrate credit rating agency APIs (Dun & Bradstreet, Experian) Add financial database connections (Bloomberg, Reuters) Include social media sentiment analysis Connect to government regulatory databases Enhance Alternative Supplier Management Add automated supplier qualification workflows Implement dynamic pricing comparison Create supplier performance scorecards Add geographic risk assessment Advanced Analytics Implement predictive failure modeling Add supplier portfolio optimization Create supply chain risk heatmaps Generate automated compliance reports 📈 Use Cases Supply Chain Risk Management**: Proactive monitoring of supplier financial stability Procurement Optimization**: Data-driven supplier selection and management Business Continuity Planning**: Automated backup supplier identification Financial Risk Assessment**: Early warning system for supplier defaults Contract Management**: Risk-based contract renewal and negotiation Vendor Diversification**: Strategic supplier portfolio management 🚨 Important Notes Respect ScrapeGraphAI API rate limits and terms of service Implement appropriate delays between supplier assessments Keep all API credentials secure and rotate them regularly Monitor API usage to manage costs effectively Ensure compliance with data privacy regulations (GDPR, CCPA) Regularly update supplier databases and contact information Review and adjust risk parameters based on market conditions Maintain confidentiality of supplier financial information 🔧 Troubleshooting Common Issues: ScrapeGraphAI extraction errors: Check API key validity and rate limits Email delivery failures: Verify Gmail credentials and permissions Slack notification failures: Check webhook URL and channel permissions False positive alerts: Adjust risk scoring thresholds and industry multipliers Missing supplier data: Verify website URLs and accessibility Alternative supplier errors: Check supplier database completeness Monitoring Best Practices: Set up workflow execution monitoring and error alerts Regularly review and update supplier information Monitor API usage and costs across all integrations Validate risk scoring accuracy with historical data Test disaster recovery and backup procedures Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Procurement best practices and industry standards Financial risk assessment methodologies Supply chain management resources and tools

Description🔍 This n8n workflow is a complete marketing automation system that connects to your CDP (Customer Data Platform), selects which flows to send, and delivers personalized emails using Brevo. It's modular and extensible — you can also add SMS, push notifications, Telegram messages, or other channels. To build a full marketing automation system, you need four key components: Workflow Automation – using n8n (this workflow) CDP – store and manage user data (e.g., NocoDB, Metabase, Power BI, etc.) Database – track transactions, templates, and send statuses (e.g., NocoDB) BI / Analytics – monitor performance by flows, journeys, and sent events This workflow represents the Workflow Automation layer. You can connect it to your own data stack or use the included example databases (cdp-ecrm, n8n-templates-ecrm, and n8n-transaction-ecrm) to get started quickly. 👤 Who’s it for? Growth & CRM teams managing user engagement flows Ecommerce marketers running time-sensitive email journeys Marketing automation pros using low-code CRM stacks Data teams building custom campaign triggers from CDPs ✅ Features 🔁 Two modular flows: "Insert user_id" and "Sending Email" 🧠 Select flow using flow_id from templates in NocoDB ✏️ Insert user data into n8n-transaction-ecrm with processing status 🔍 Filter duplicate users by user_id to avoid over-sending 📧 Validate email fields and flag disposables 📨 Send personalized emails using Brevo template parameters 📊 Track delivery with sent_result, sent_at, and status updates 🕒 Runs every 30 minutes via schedule trigger 🛠 How to Use Set your flow In the Setup Flow node, change the flow_id to match a row in your n8n-templates-ecrm table. Prepare your tables in NocoDB cdp-ecrm: contains users (user_id, email, first_name, phone_number) n8n-templates-ecrm: contains flows with metadata n8n-transaction-ecrm: stores and updates user send status Configure credentials NocoDB API Token Brevo (Sendinblue) API Key Trigger the flows Run “Insert user_id” manually or on a schedule to prepare users “Sending Email” runs automatically every 30 minutes 📌 Notes Disposable email domains are filtered using regex Status: 0-processing → just inserted 1-sending → ready to send 2-sent → email sent successfully 3-no-email → missing email address 4-disposal-email → disposable or banned email Easily duplicate the "Insert user_id" flow to add more campaigns

This n8n workflow automates replying to Google Play Store reviews using AI. It analyzes each review’s sentiment and tone and posts a human-like response — saving time for indie devs, founders, and PMs managing multiple apps. 💡 Use Cases Respond to reviews at scale without sounding robotic Prioritize negative sentiment feedback Maintain consistent tone and support messaging Free up time for teams to focus on product instead of ops 🧠 How it works Uses the Play Store API to fetch new app reviews Filters out reviews that have already been replied to Analyzes sentiment using OpenAI GPT-4o Passes sentiment and review context to an AI Agent node that crafts a reply Replies are posted to Play Store via Google API (Optional) Logs the reply to Slack for visibility 🛠️ Setup Instructions (Sticky notes included in the workflow) 1. HTTPS Node Replace the package name with your app’s package ID Add Google Service Account credentials → Create from Google Cloud Console with access to Play Console → Add to n8n Credential Manager 2. OpenAI Node Add your OpenAI API key → GPT-4o or GPT-4o mini supported → Customize model or instructions if needed 3. AI Agent Node Modify prompt to reflect your app name, tone, and feature set → E.g. polite, witty, casual, support-friendly, etc. → You can add reply conditions or logic for different types of reviews 4. Slack Node (Optional) Configure Slack Webhook or OAuth credentials if you want reply logs → Otherwise, delete the node to simplify the workflow ⚡ Requirements Google Play Developer Console access Google Cloud Project with service account OpenAI account (GPT-4o or mini) (Optional) Slack workspace & app for logging 🙌 Don’t want to set this up yourself? I’ll do it for you. Just drop me an email: imarunavadas@gmail.com Let’s automate the boring stuff so you can focus on growth. 🚀

:car: Business Value Proposition Accelerates ISO 26262 compliance for automotive/industrial systems by automating safety analysis while maintaining rigorous audit standards. :gear: How It Works graph TD A[Engineer uploadssystem description] --> B(LLM identifies hazards) B --> C(LLM scores risks per ISO 26262) C --> D(Generates mitigation strategies) D --> E(Produces audit-ready reports) :chart_with_upwards_trend: Key Benefits Time 50-70% faster than manual HAZOP/FMEA sessions Instant report generation vs. weeks of documentation Risk Mitigation Pre-validated templates reduce human error Auto-generated traceability simplifies audits :warning: Governance Controls Human-in-the-loop: All LLM outputs require engineer sign-off Version tracking: Full history of modifications Audit mode: Export all decision rationales :computer: Technical Requirements Runs on existing n8n instances Docker deployment (<1hr setup) Integrates with JAMA/DOORS (optional) :wrench: Setup and Usage Prerequisites Docker (Install Guide) Docker Compose (Install Guide) n8n instance (Free Self-Hosted or Cloud - Paid) OpenAI API key (Get Key) Enterprise-ready deployment: When supported by IT infrastructure teams, this solution transforms into a scalable AI safety assistant, providing real-time HARA guidance akin to engineering Co-pilot tools. :arrow_down: Installation and :play_or_pause_button: Running the Workflow For installation procedures and usage of workflow, refer the repository :warning: Validation & Limitations AI-Assisted Analysis Considerations | Advantage | Mitigation Strategy | Implementation Example | |-----------|---------------------|------------------------| | Rapid hazard identification | Human validation layer | Manual review nodes in workflow | | Consistent S/E/C scoring | Rule-based validation | ASIL-D → Redundancy check | | Edge case coverage | Cross-reference with historical data | Integration with incident databases | Critical Validation Steps AI Output Review node in n8n Example: (by code) { "type": "function", "parameters": { "functionCode": "if ($input.item.json.ASIL === 'D' && !$input.item.json.redundancy) throw new Error('ASIL D requires redundancy');" } } Version Control Prompt versions tied to ISO standard editions (e.g., ISO26262:2018-v1.2) Git-tracked changes to ai_models/training_data/ Audit trails Providing a log structure for audit trails Log structure /logs/ └── YYYY-MM-DD/ ├── hazards_approved.log └── hazards_rejected.log

Attachments Gmail to Drive and Google Sheets Description Automatically process invoice emails by saving attachments to Google Drive and extracting key invoice data to Google Sheets using AI. This workflow monitors your Gmail for unread emails with attachments, saves PDFs to a specified Google Drive folder, and uses OpenAI's GPT-4o to extract invoice details (date, description, amount) into a structured spreadsheet. Use cases Invoice Management**: Automatically organize and track invoices received via email Financial Record Keeping**: Maintain a structured database of all invoice information Document Organization**: Keep digital copies of invoices organized in Google Drive Automated Data Entry**: Eliminate manual data entry for invoice processing Resources Gmail account Google Drive account Google Sheets account OpenAI API key Setup instructions Prerequisites Active Gmail, Google Drive, and Google Sheets accounts OpenAI API key (GPT-4o model access) n8n instance with credentials manager Steps Gmail and Google Drive Setup: Connect your Gmail account in n8n credentials Connect your Google Drive account with appropriate permissions Create a destination folder in Google Drive for invoice storage Google Sheets Setup: Connect your Google Sheets account Create a spreadsheet with columns: Invoice date, Invoice Description, Total price, and Fichero Copy your spreadsheet ID for configuration OpenAI Setup: Add your OpenAI API key to n8n credentials Configure Email Filter: Update the email filter node to match your specific sender requirements Benefits Time Saving**: Eliminates manual downloading, filing, and data entry Accuracy**: AI-powered data extraction reduces human error Organization**: Consistent file naming and storage structure Searchability**: Creates a searchable database of all invoice information Automation**: Runs every minute to process new emails as they arrive Related templates Email Parser to CRM Document Processing Workflow Financial Data Automation

Who this is for The TrustPilot SaaS Product Review Tracker is designed for product managers, SaaS growth teams, customer experience analysts, and marketing teams who need to extract, summarize, and analyze customer feedback at scale from TrustPilot. This workflow is tailored for: Product Managers** - Monitoring feedback to drive feature improvements Customer Support & CX Teams** - Identifying sentiment trends or recurring issues Marketing & Growth Teams** - Leveraging testimonials and market perception Data Analysts** - Tracking competitor reviews and benchmarking Founders & Executives** - Wanting aggregated insights into customer satisfaction What problem is this workflow solving? Manually monitoring, extracting, and summarizing TrustPilot reviews is time-consuming, fragmented, and hard to scale across multiple SaaS products. This workflow automates that process from unlocking the data behind anti-bot layers to summarizing and storing customer insights enabling teams to respond faster, spot trends, and make data-backed product decisions. This workflow solves: The challenge of scraping protected review data (using Bright Data Web Unlocker) The need for structured insights from unstructured review content The lack of automated delivery to storage and alerting systems like Google Sheets or webhooks What this workflow does Extract TrustPilot Reviews: Uses Bright Data Web Unlocker to bypass anti-bot protections and pull markdown-based content from product review pages Convert Markdown to Text: Leverages a basic LLM chain to clean and convert scraped markdown into plain text Structured Information Extraction: Uses OpenAI GPT-4o via the Information Extractor node to extract fields like product name, review date, rating, and reviewer sentiment Summarization Chain: Generates concise summaries of overall review sentiment and themes using OpenAI Merge & Aggregate Output: Consolidates individual extracted records into a structured batch output Outbound Data Delivery: Google Sheets – Appends summary and structured review data Write to Disk – Persists raw and processed content locally Webhook Notification – Sends a real-time alert with summarized insights Pre-conditions You need to have a Bright Data account and do the necessary setup as mentioned in the "Setup" section below. You need to have an OpenAI Account. Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. In n8n, Configure the Google Sheet Credentials with your own account. Follow this documentation - Set Google Sheet Credential In n8n, configure the OpenAi account credentials. Ensure the URL and Bright Data zone name are correctly set in the Set URL, Filename and Bright Data Zone node. Set the desired local path in the Write a file to disk node to save the responses. How to customize this workflow to your needs Target Multiple Products : Configure the Bright Data input URL dynamically for different SaaS product TrustPilot URLs Loop through a product list and run parallel jobs for each Customize Extraction Fields : Update the prompt in the Information Extractor to include: Review title Response from company Specific feature mentions Competitor references Tune Summarization Style Change tone**: executive summary, customer pain-point focus, or marketing quote extract Enable sentiment aggregation** (e.g., 30% negative, 50% neutral, 20% positive) Expand Output Destinations Push to Notion, Airtable, or CRM tools using additional webhook nodes Generate and send PDF reports (via PDFKit or HTML-to-PDF nodes) Schedule summary digests via Gmail or Slack

How it works Many users have asked in the support forum about different methods to analyze images and PDF documents with Google Gemini AI in n8n. This workflow answers that question by demonstrating five different approaches: Single image with auto binary passthrough - The simplest approach using AI Agent's automatic binary handling Multiple images with predefined prompts - For customized analysis with different instructions per image Native n8n item-by-item processing - For handling multiple items using n8n's standard workflow paradigm PDF analysis via direct API - For document analysis and text extraction Image analysis via direct API - For direct control over API parameters Each method has advantages depending on your specific use case, data volume, and customization needs. Set up steps Setup time: ~5-10 minutes You'll need: A Google Gemini API key n8n with HTTP Request and AI Agent nodes Important: For the HTTP Request nodes making direct API calls to Gemini (Methods 3, 4, and 5), you'll need to set up Query Authentication with your Gemini API key. Add a parameter named "key" with your API key value in the Query Auth section of these nodes. I'll updated this if I find better ways. Also let me know if you know other ways. Eager to learn :)

Automatically scrape Meta Threads for posts hiring specific roles (e.g. automation engineers, video editors, graphic designers), filter true hiring intent, deduplicate, and send alerts. We are taking automation roles as an example for now. What it does This workflow continuously scans Threads for fresh posts mentioning the roles you care about. It uses AI to filter out self-promotion and service ads, keeping only posts where the author is hiring. Qualified posts are saved into Google Sheets for tracking and sent to Telegram for instant alerts. It’s ideal for freelancers, agencies, and job seekers who want a steady radar of opportunities. How it works (Step by Step) Schedule trigger – Runs on a set interval (e.g. every 12 hours). Scrape Threads posts – Fetches recent posts from multiple keywords (e.g., “n8n expert”, “hire video editor”, “graphic designer”, etc.) via Apify. Merge results – Combines posts into a single stream. Normalize fields – Maps raw data into clean fields: text, author, URL, timestamp, profile link. AI filter – Uses an AI Agent to: Accept only posts where someone is hiring (rejects “hire me” style self-promo). Apply simple geography rules (e.g., allow US, UK, UAE, CA; pass unknowns). Exclude roles outside your scope. Deduplication – Checks Google Sheets to skip posts already seen. Save to Google Sheets – Writes qualified posts with full details. Telegram alerts – Sends you the matched post instantly so you can act. Who it’s for Freelancers: Get first dibs on gigs before others spot them. Agencies: Build a client pipeline by tracking hiring signals. Job seekers: Spot hidden opportunities in your target field. Customization Ideas Swap keywords to monitor roles you care about (e.g., “UI/UX designer”, “motion graphics editor”, “copywriter”). Add Slack or Discord notifications instead of Telegram. Expand geo rules to match your region. Use Sheets as a CRM—add columns for status, outreach date, etc

A n8n workflow designed to shorten URLs using Dub.co API. How it works: It shortens a url using Dub.co API, with the ability to use custom domains and projects. It updates the current shortened url if the slug has been already used. Estimated Time: Around 15 minutes. Requirements: A Dub.co account. Configuration: Configure the "API Auth" node to add your Dub.co API key, project slug, and the long URL. There some extras that you're able to configure too. You will be able to do that by clicking the "API Auth" node and filling the fields. Detailed Instructions: Sticky notes within the workflow provide extensive setup information and guidance. Keywords: n8n workflow, dub.co, dub.sh, url shortener, short urls, short links

Who is this for? This workflow is perfect for: HR professionals** seeking to automate employee and department management Startups and SMBs** that want an AI-powered HR assistant on Telegram Internal operations teams** that want to simplify onboarding and employee data tracking What problem is this workflow solving? Managing employee databases manually is error-prone and inefficient—especially for growing teams. This workflow solves that by: Enabling natural language-based HR operations directly through Telegram Automating the creation, retrieval, and deletion of employee records in Airtable Dynamically managing related data such as departments and job titles Handling data consistency and linking across relational tables automatically Providing a conversational interface backed by OpenAI for smart decision-making What this workflow does Using Telegram as the interface and Airtable as the backend database, this intelligent HR workflow allows users to: Chat in natural language (e.g. “Show me all employees” or “Create employee: Sarah, Marketing…”) Interpret and route requests via an AI Agent that acts as the orchestrator Query employee, department, and job title data from Airtable Create or update records as needed: Add new departments and job titles automatically if they don’t exist Create new employees and link them to the correct department and job title Delete employees based on ID Respond directly in Telegram, providing user-friendly feedback Setup View & Copy the Airtable base here: 👉 Employee Database Management – Airtable Base Template Telegram Bot: Set up a Telegram bot and connect it to the Telegram Trigger node Airtable: Prepare three Airtable tables: Employees with links to Departments and Job Titles Departments with Name & Description Job Titles with Title & Description Connect your Airtable API key and base/table IDs into the appropriate Airtable nodes Add your OpenAI API key to the AI Agent nodes Deploy both workflows: the main chatbot workflow and the employee creation sub-workflow Test with sample messages like: “Create employee: John Doe, john@company.com, Engineering, Software Engineer” “Remove employee ID rec123xyz” How to customize this workflow to your needs Switch databases**: Replace Airtable with Notion, PostgreSQL, or Google Sheets if desired Enhance security**: Add authentication and validation before allowing deletion Add approval flows**: Integrate Telegram button-based approvals for sensitive actions Multi-language support**: Expand system prompts to support multiple languages Add logging**: Store every user action in a log table for auditability Expand capabilities**: Integrate payroll, time tracking, or Slack notifications Extra Tips This is a two-workflow setup. Make sure the sub-workflow is deployed and accessible from the main agent. Use Simple Memory per chat ID to preserve context across user queries. You can expand the orchestration logic by adding more tools to the main agent—such as “Get active employees only” or “List employees by job title.”

Chat with local LLMs using n8n and Ollama This n8n workflow allows you to seamlessly interact with your self-hosted Large Language Models (LLMs) through a user-friendly chat interface. By connecting to Ollama, a powerful tool for managing local LLMs, you can send prompts and receive AI-generated responses directly within n8n. Use cases Private AI Interactions Ideal for scenarios where data privacy and confidentiality are important. Cost-Effective LLM Usage Avoid ongoing cloud API costs by running models on your own hardware. Experimentation & Learning A great way to explore and experiment with different LLMs in a local, controlled environment. Prototyping & Development Build and test AI-powered applications without relying on external services. How it works When chat message received: Captures the user's input from the chat interface. Chat LLM Chain: Sends the input to the Ollama server and receives the AI-generated response. Delivers the LLM's response back to the chat interface. Set up steps Make sure Ollama is installed and running on your machine before executing this workflow. Edit the Ollama address if different from the default.

🛒 Lead Workflow: Yelp & Trustpilot Scraping + OpenAI Analysis via BrightData > Description: Automated lead generation workflow that scrapes business data from Yelp and Trustpilot based on location and category, analyzes credibility, and sends personalized outreach emails using AI. > ⚠️ Important: This template requires a self-hosted n8n instance to run. 📋 Overview This workflow provides an automated lead generation solution that identifies high-quality prospects from Yelp and Trustpilot, analyzes their credibility through reviews, and sends personalized outreach emails. Perfect for digital marketing agencies, sales teams, and business development professionals. ✨ Key Features 🎯 Smart Location Analysis** AI breaks down cities into sub-locations for comprehensive coverage 🛍 Yelp Integration** Scrapes business details using BrightData's Yelp dataset ⭐ Trustpilot Verification** Validates business credibility through review analysis 📊 Data Storage** Automatically saves results to Google Sheets 🤖 AI-Powered Outreach** Generates personalized emails using Claude AI 📧 Automated Sending** Sends emails directly through Gmail integration 🔄 How It Works User Input: Submit location, country, and business category through a form AI Location Analysis: Gemini AI identifies sub-locations within the specified area Yelp Scraping: BrightData extracts business information from multiple locations Data Processing: Cleans and stores business details in Google Sheets Trustpilot Verification: Scrapes reviews and company details for credibility check Email Generation: Claude AI creates personalized outreach messages Automated Outreach: Sends emails to qualified prospects via Gmail 📊 Data Output | Field | Description | Example | |---------------|----------------------------------|----------------------------------| | Company Name | Business name from Yelp/Trustpilot | Best Local Restaurant | | Website | Company website URL | https://example-restaurant.com | | Phone Number | Business contact number | (555) 123-4567 | | Email | Business email address | demo@example.com | | Address | Physical business location | 123 Main St, City, State | | Rating | Overall business rating | 4.5/5 | | Categories | Business categories/tags | Restaurant, Italian, Fine Dining | 🚀 Setup Instructions ⏱️ Estimated Setup Time: 10–15 minutes Prerequisites n8n instance (self-hosted or cloud) Google account with Sheets access BrightData account with Yelp and Trustpilot datasets Google Gemini API access Anthropic API key for Claude Gmail account for sending emails Step 1: Import the Workflow Copy the JSON workflow code In n8n: Workflows → + Add workflow → Import from JSON Paste JSON and click Import Step 2: Configure Google Sheets Integration Create two Google Sheets: Yelp data: Name, Categories, Website, Address, Phone, URL, Rating Trustpilot data: Company Name, Email, Phone Number, Address, Rating, Company About Copy Sheet IDs from URLs In n8n: Credentials → + Add credential → Google Sheets OAuth2 API Complete OAuth setup and test connection Update all Google Sheets nodes with your Sheet IDs Step 3: Configure BrightData Set up BrightData credentials in n8n Replace API token with: BRIGHT_DATA_API_KEY Verify dataset access: Yelp dataset: gd_lgugwl0519h1p14rwk Trustpilot dataset: gd_lm5zmhwd2sni130p Test connections Step 4: Configure AI Models Google Gemini (Location Analysis)** Add Google Gemini API credentials Configure model: models/gemini-1.5-flash Claude AI (Email Generation)** Add Anthropic API credentials Configure model: claude-sonnet-4-20250514 Step 5: Configure Gmail Integration Set up Gmail OAuth2 credentials in n8n Update "Send Outreach Email" node Test email sending Step 6: Test & Activate Activate the workflow Test with sample data: Country: United States Location: Dallas Category: Restaurants Verify data appears in Google Sheets Check that emails are generated and sent 📖 Usage Guide Starting a Lead Generation Campaign Access the form trigger URL Enter your target criteria: Country: Target country Location: City or region Category: Business type (e.g., restaurants) Submit the form to start the process Monitoring Results Yelp Data Sheet:** View scraped business information Trustpilot Sheet:** Review credibility data Gmail Sent Items:** Track outreach emails sent 🔧 Customization Options Modifying Email Templates Edit the "AI Generate Email Content" node to customize: Email tone and style Services mentioned Call-to-action messages Branding elements Adjusting Data Filters Modify rating thresholds Set minimum review counts Add geographic restrictions Filter by business size Scaling the Workflow Increase batch sizes Add delays between requests Use parallel processing Add error handling 🚨 Troubleshooting Common Issues & Solutions 1. BrightData Connection Failed Cause: Invalid API credentials or dataset access Solution: Verify credentials and dataset permissions 2. No Data Extracted Cause: Invalid location or changed page structure Solution: Verify location names and test other categories 3. Gmail Authentication Issues Cause: Expired OAuth tokens Solution: Re-authenticate and check permissions 4. AI Model Errors Cause: API quota exceeded or invalid keys Solution: Check usage limits and API key Performance Optimization Rate Limiting:** Add delays Error Handling:** Retry failed requests Data Validation:** Check for malformed data Memory Management:** Process in smaller batches 📈 Use Cases & Examples 1. Digital Marketing Agency Lead Generation Goal:** Find businesses needing marketing Target:** Restaurants, retail stores Approach:** Focus on good-rated but low-online-presence businesses 2. B2B Sales Prospecting Goal:** Find software solution clients Target:** Growing businesses Approach:** Focus on recent positive reviews 3. Partnership Development Goal:** Find complementary businesses Target:** Established businesses Approach:** Focus on reputation and satisfaction scores ⚡ Performance & Limits Expected Performance Processing Time:** 5–10 minutes/location Data Accuracy:** 90%+ Success Rate:** 85%+ Daily Capacity:** 100–500 leads Resource Usage API Calls:** ~10–20 per business Storage:** Minimal (Google Sheets) Execution Time:** 3–8 minutes/10 businesses Network Usage:** ~5–10MB/business 🤝 Support & Community Getting Help n8n Community Forum:** community.n8n.io Docs:** docs.n8n.io BrightData Support:** Via dashboard Contributing Share improvements Report issues and suggestions Create industry-specific variations Document best practices > 🔒 Privacy & Compliance: Ensure GDPR/CCPA compliance. Always respect robots.txt and terms of service of scraped sites. 🎯 Ready to Generate Leads! This workflow provides a complete solution for automated lead generation and outreach. Customize it to fit your needs and start building your pipeline today! For any questions or support, please contact: 📧 info@incrementors.com or fill out this form: Contact Us