Workflow Templates

Automated SEO Website Audit with n8n, Google Docs & RapidAPI's SEO Analyzer Description: Use n8n to automate SEO audits with the Website SEO Analyzer and Audit AI from RapidAPI. Capture a URL, run a full audit, and export a structured SEO report to Google Docs — all without manual steps. ⚙️ Node-by-Node Explanation 🟢 formTrigger — On Form Submission Starts the workflow when a user submits a URL through a form. Collects the website to be analyzed. 🌐 httpRequest — Website Audit Sends the submitted URL to the Website SEO Analyzer and Audit AI via a POST request. Fetches detailed SEO data, including meta tags, keyword usage, and technical performance. 🧠 code — Reformat Transforms raw JSON from the Website SEO Analyzer and Audit AI into a structured Markdown summary. Organizes insights into sections like Metadata, Keyword Density, Page Performance, and Security. 📄 googleDocs — Add Data In Google Docs Automatically inserts the formatted SEO audit report into a pre-connected Google Docs file. Allows audit data to be easily shared, tracked, or archived. 🌟 Benefits ✅ Powered by **Website SEO Analyzer and Audit AI:** Leverage a reliable, cloud-based SEO tool via RapidAPI. 🔁 End-to-End SEO Workflow: Fully automates input, audit, formatting, and export to documentation. 📊 Human-Readable Reports: Translates raw API output into structured, insightful summaries. 📂 Centralized Documentation: Stores SEO audits in Google Docs for easy reference and historical tracking. 🚀 Use Cases 📈 SEO Agencies: Generate fast and consistent SEO audits using the Website SEO Analyzer and Audit AI — ideal for client reporting. 🏢 In-House Web Teams: Regularly audit corporate websites and track performance in a document-based SEO log. 🧲 Lead Generation for SEO Services: Offer real-time audits through a public form to attract and qualify leads. 📅 Monthly SEO Health Checks: Automate recurring site audits and log results using n8n and RapidAPI. Create your free n8n account and set up the workflow in just a few minutes using the link below: 👉 Start Automating with n8n Save time, stay consistent, and grow your LinkedIn presence effortlessly!

Competitor Analysis & SEO Data Logging Workflow Using Competitor Analysis Semrush API Description This workflow automates SEO competitor analysis using the Competitor Analysis Semrush API and logs the data into Google Sheets for structured reporting. It captures domain overview, organic competitors, organic pages, and keyword-level insights from the Competitor Analysis Semrush API, then appends them to different sheets for easy tracking. Node-by-Node Explanation On form submission – Captures the website URL entered by the user. Competitor Analysis – Sends the website to the Competitor Analysis Semrush API via HTTP POST request. Re format output – Extracts and formats the domain overview data. Domain overview – Saves organic keywords and traffic into Google Sheets. Reformat – Extracts the organic competitors list. Organic Competitor – Logs competitor domains, relevance, and traffic into Google Sheets. Reformat 2 – Extracts organic pages data. Organic Pages – Stores page-level data such as traffic and keyword counts. Reformat2 – Extracts organic keywords details. organic keywords – Logs keyword data like CPC, volume, and difficulty into Google Sheets. Benefits ✅ Automated competitor tracking – No manual API calls, all logged in Google Sheets. ✅ Centralized SEO reporting – Data stored in structured sheets for quick access. ✅ Time-saving – Streamlines research by combining multiple reports in one workflow. ✅ Accurate insights – Direct data from the Competitor Analysis Semrush API ensures reliability. Use Cases 📊 SEO Research – Track domain performance and competitor strategies. 🔍 Competitor Monitoring – Identify competitor domains, keywords, and traffic. 📝 Content Strategy – Find top-performing organic pages and replicate content ideas. 💰 Keyword Planning – Use CPC and difficulty data to prioritize profitable keywords. 📈 Client Reporting – Generate ready-to-use SEO competitor analysis reports in Google Sheets.

Automated Keyword Analysis and Google Sheets Logging Automate keyword research with n8n and log essential SEO data like search volume, trends, competition, and keyword difficulty directly into Google Sheets. Simplify your SEO efforts with real-time insights. Node-by-Node Explanation 1. On form submission (Trigger) Purpose:** Triggers the workflow when a user submits the form with "country" and "keyword" as inputs. Explanation:** This node initiates the process by accepting user input from the form and passing it to the next node for analysis. 2. Keyword Analysis (HTTP Request) Purpose:** Sends a request to an external SEO API to analyze the provided keyword, fetching data like search volume, trends, and competition. Explanation:* This node calls the *Keyword Research Tool API** with the country and keyword inputs from the form, retrieving essential keyword data for further processing. 3. Re-format output (Code) Purpose:** Processes and reformats the API response into a structured format suitable for logging into Google Sheets. Explanation:** Extracts and organizes the keyword data (e.g., competition, CPC, search volume) into a format that can be easily mapped to Google Sheets columns. 4. Google Sheets (Append) Purpose:** Appends the reformatted keyword data into the specified Google Sheets document. Explanation:** Logs the fetched keyword insights into a Google Sheets document, allowing for continuous tracking and analysis. Benefits of This Workflow Automated Keyword Research:* Eliminates manual keyword research by automating the entire process using the *Keyword Research Tool API**. Real-time Data Tracking:* Fetches up-to-date SEO metrics from the *Keyword Research Tool API** and logs them directly into Google Sheets for easy access and analysis. Efficient Workflow:** Saves time by integrating multiple tools (form, SEO API, Google Sheets) into one seamless process. SEO Insights:* Provides detailed insights like search volume, trends, competition, and keyword difficulty, aiding in strategic decision-making with the help of the *Keyword Research Tool API**. Use Case This workflow is ideal for digital marketers, SEO professionals, and content creators who need to analyze keyword performance and track essential SEO metrics efficiently. It automates the process of keyword research by calling the Keyword Research Tool API, fetching relevant data, and logging it into Google Sheets. This makes it easier to monitor and optimize SEO strategies in real-time.

Backlink Checker with Google Sheets Logging (Seo) Description: This workflow helps you analyze top backlinks using Semrush API and logs the results directly into Google Sheets for easy SEO tracking and reporting. It integrates the Top Backlink Checker API from RapidAPI, providing in-depth backlink analysis, and combines that with Google Sheets for efficient data storage and tracking. Node-by-Node Explanation: 1. On form submission Captures the website URL submitted by the user through a form. This node triggers the workflow when the form is filled with a website URL. The Top Backlink Checker API (via RapidAPI) is used to check backlinks after this step. 2. Check webTraffic Sends a request to the Top Backlink Checker API to gather traffic data for the submitted website. This includes important metrics like visits, bounce rate, and more, which will later be stored in Google Sheets for analysis. 3. Reformat output Extracts and re-formats the traffic data received from the Top Backlink Checker API. This node cleans and structures the raw data for easier processing, ensuring it is usable for later stages in the workflow. 4. Reformat Processes the backlink data received from the Top Backlink Checker API (RapidAPI). The data is reformatted and structured to be added to Google Sheets for storage, making it easier to analyze. 5. Backlink overview Appends the re-formatted backlink overview data into a Google Sheets document. This stores important backlink information like source URLs, anchor texts, and more, making it available for later analysis and reporting. 6. Backlinks Appends detailed backlink data, including target URLs, anchors, and internal/external links, into Google Sheets. This helps track individual backlinks, their attributes, and page scores, allowing for deeper SEO analysis and reporting. Benefits and Use Cases: Benefits: Backlink Tracking: The integration of the **Top Backlink Checker API helps you track all the backlinks associated with a website. You can get insights on the source URL, anchor text, first and last seen, and more. Traffic Insights: By integrating **Top Backlink Checker API, this workflow allows you to monitor important website traffic data such as visits, bounce rates, and organic reach, helping with SEO strategies. Automated Google Sheets Logging**: All traffic and backlink data is logged automatically into Google Sheets for easy access and future analysis. This avoids manual data entry and ensures consistency. Efficient Workflow: The automation provided by **n8n streamlines your SEO analysis workflow, ensuring that data is formatted, structured, and updated without any manual intervention. Use Cases: SEO Reports**: Generate regular SEO reports by tracking backlinks and traffic data automatically from Semrush and Top Backlink Checker, saving time and ensuring accurate reporting. Competitor Analysis: Analyze your competitors’ backlinks and traffic to stay ahead in SEO rankings by leveraging data from the **Top Backlink Checker API. Backlink Management: Use the data from **Top Backlink Checker API to assess the health of backlinks, ensuring that high-value backlinks are tracked, and toxic backlinks are identified for removal or disavow. SEO Campaign Tracking**: Monitor how backlinks and website traffic evolve over time to evaluate the effectiveness of your SEO campaigns, keeping all your data in Google Sheets for easy tracking.

Automated Seo Website Traffic Checker with Google Sheets Logging (Seo) Description: This workflow uses the Website Traffic Checker Semrush API to analyze website traffic and performance. It collects data through a user-submitted website URL and stores the results in Google Sheets for easy access and reporting. Ideal for SEO analysis and data tracking. Node-by-Node Explanation: 1. On form submission Captures the website URL submitted by the user through a form. Triggers the workflow when a website URL is submitted via the form interface. 2. Check webTraffic Sends a request to the Website Traffic Checker Semrush API to gather traffic data for the submitted website. Uses the provided URL to fetch real-time traffic statistics using the Semrush API. 3. Re format output Extracts and reformats the raw traffic data from the API response. Cleans and structures the traffic data for easy readability and reporting. 4. Google Sheets Appends the formatted traffic data into a Google Sheet for storage and further analysis. Stores the data in a Google Sheets document for long-term tracking and analysis. Benefits of This Flow: Real-Time Data Collection:** Collects real-time website traffic data directly from the Website Traffic Checker Semrush API, ensuring up-to-date information is always available. Automation:** Automatically processes and formats the website traffic data into an easily accessible Google Sheet, saving time and effort. Customizable:** The workflow can be customized to track multiple websites, and the data can be filtered and expanded as per user needs. SEO Insights:** Get in-depth insights like bounce rate, pages per visit, and visits per user, essential for SEO optimization. Use Case: SEO Monitoring:** Track and analyze the traffic of competitor websites or your own website for SEO improvements. This is ideal for digital marketers, SEO professionals, and website owners. Automated Reporting:** Automatically generate traffic reports for various websites and save them in a Google Sheet for easy reference. No need to manually update data or perform complex calculations. Data-Driven Decisions:** By utilizing data from the Website Traffic Checker Semrush API, users can make informed decisions to improve website performance and user experience.

🧠 Sentiment Analysis of Product Reviews using Google Sheets & OpenAI 🚀 Quick Implementation Steps Automated customer feedback analyzer: Trigger**: Google Sheets triggers on new product review rows. Sentiment Analysis**: Review text sent to OpenAI. Writeback**: Resulting sentiment (Positive, Neutral, Negative) is written back to the sheet. Just connect your credentials and sheet — you're ready to go! 🔍 What It Does This workflow automatically analyzes user-submitted product reviews and classifies them by sentiment using OpenAI’s powerful language models. It eliminates the need to manually sift through feedback by tagging each review with a sentiment score. The sentiment result is then written back to the Google Sheet next to the original review, enabling you to get a fast, clear snapshot of overall customer perception, satisfaction and pain points. Whether you're monitoring 10 or 10,000 reviews, this process scales effortlessly and updates every minute. 👤 Who’s It For This workflow is designed for: E-commerce teams** collecting user reviews. Product teams** monitoring customer feedback. Marketing teams** identifying promotable reviews. Support teams** watching for negative experiences. SaaS platforms**, apps, and survey tools managing structured text feedback. ✅ Requirements You’ll need: A Google Sheet with two columns: Review and Sentiment Google Sheets OAuth2 credentials in n8n OpenAI API Key (for GPT-4o-mini or GPT-3.5) n8n instance with LangChain and OpenAI nodes enabled ⚙️ How It Works Google Sheets Trigger: Watches for new rows every minute OpenAI Integration: Uses LangChain’s Sentiment Analysis node Passes review text into GPT-4o-mini via the OpenAI Chat Model node Sheet Update: The sentiment result (Positive, Negative, or Neutral) is written into the Sentiment column in the same row. Sticky Notes included for better visual understanding inside the workflow editor. 🛠️ Steps to Configure and Use 1. Prepare Your Google Sheet Make sure your sheet is named Sheet1 with the following structure: | Review | Sentiment | |---------------------------------------|-----------| | Absolutely love it! | | | Not worth the price. | | 2. Set Up Credentials Google Sheets**: OAuth2 credentials OpenAI**: API Key added via OpenAI API credential in n8n 3. Import & Activate Workflow Import the workflow JSON into your n8n instance. Assign the proper credentials to the trigger and OpenAI nodes. Activate the workflow. 🧩 How To Customize 🛎️ Alerting: Add Slack/Email nodes for negative sentiment alerts 🔄 Triggering: Change the polling interval to real-time triggers (e.g., webhook) 📊 Extended Sentiment: Modify sentiment categories (e.g., "Mixed", "Sarcastic") 🧾 Summary Report: Add Cron + Aggregation nodes for daily/weekly summaries 🧠 Prompt Tuning: Adjust system prompt for deeper or context-based sentiment evaluation 🧱 Add‑ons (Optional Features) Email Digest of Negative Reviews Google Drive Logging Team Notification via Slack Summary to Notion, Airtable, or Google Docs 📌 Use Case Examples Online Stores**: Auto-tag reviews for reputation monitoring Product Teams**: See which feature releases generate positive or negative buzz CX Dashboards**: Feed real-time sentiment to internal BI tools Marketing**: Extract glowing reviews for social proof Support**: Triage issues by flagging critical comments instantly ...and many more applications wherever text feedback is collected. 🧰 Troubleshooting Guide | Issue | Possible Cause | Suggested Fix | |-------------------------|---------------------------------------------|---------------------------------------------------| | Sentiment not updating | Sheet credentials missing or misconfigured | Reconnect Google Sheets OAuth2 | | Blank sentiment | Review column empty or misaligned | Ensure proper column header & value present | | OpenAI errors | Invalid or expired API key | Regenerate API Key from OpenAI and re-auth | | Workflow doesn’t run | Polling settings incorrect | Confirm interval & document ID in trigger node | 🤝 Need Help? If you need assistance for ✅ Help setting up this workflow ⚙️ Customizing prompts or output 🚀 Automating your full review pipeline 👉 Contact us today at WeblineIndia. We will be happy to assist.

Description: Discover which marketing channels actually convert with this n8n automation template. The workflow fetches all opportunities from HighLevel (GHL), filters for “Closed Won” deals, computes lead-to-sale conversion metrics per source, and sends a summary report to Slack while logging raw data into Google Sheets for ongoing analysis. Perfect for marketing teams, growth analysts, and sales managers who want to reduce wasted ad spend and double down on sources that deliver real ROI. ✅ What This Template Does (Step-by-Step) ⚡ Manual or Scheduled Trigger Run the workflow manually for instant analysis or automate it daily/weekly with a schedule trigger. 📥 Fetch All Opportunities from HighLevel Pulls every deal record from your GHL CRM, including status, amount, and lead source fields. 🔍 Filter for Closed-Won Deals Separates deals by outcome — only “Won” deals are used for conversion tracking, while others trigger Slack alerts for team review. 📊 Log Won Deals to Google Sheets Saves every successful deal’s details into a structured Google Sheet for long-term performance tracking. 🧮 Calculate Lead Source Metrics Aggregates results by lead source, calculating total deals, conversion rate, and total revenue per source automatically. 📢 Send Slack Summary Report Posts a neat summary of conversion metrics to a dedicated Slack channel like #lead-source-report, ensuring visibility for the marketing and sales teams. 🔔 Alert for Lost/Pending Deals Non-won opportunities are flagged and shared with the team via Slack for timely follow-ups. ##🧠 Key Features 📊 Automated lead source performance tracking 💬 Slack alerts for both success and loss updates 📈 Real-time conversion and ROI visibility ⚙️ Seamless GHL + Google Sheets + Slack integration 🔁 Ready to run on-demand or on schedule 💼 Use Cases 💡 Measure campaign ROI across channels 🎯 Identify top-performing ad platforms 📢 Send weekly sales source reports to marketing 💰 Optimize budget allocation using data-driven insights 📦 Required Integrations HighLevel (GHL) – for opportunity data retrieval Google Sheets – for storing and visualizing deal data Slack – for team notifications and reports 🎯 Why Use This Template? ✅ Saves hours of manual reporting work ✅ Ensures consistent performance tracking ✅ Highlights winning and underperforming sources ✅ Helps marketing teams focus on what truly converts

Smart Blockchain Monitor with ScrapeGraphAI Risk Detection and Instant Alerts 🎯 Target Audience Cryptocurrency traders and investors DeFi protocol managers and developers Blockchain security analysts Financial compliance officers Crypto fund managers and institutions Risk management teams Blockchain developers monitoring smart contracts Digital asset custodians 🚀 Problem Statement Manual blockchain monitoring is time-consuming and prone to missing critical events, often leading to delayed responses to high-value transactions, security threats, or unusual network activity. This template solves the challenge of real-time blockchain surveillance by automatically detecting, analyzing, and alerting on significant blockchain events using AI-powered intelligence and instant notifications. 🔧 How it Works This workflow automatically monitors blockchain activity in real-time, uses ScrapeGraphAI to intelligently extract transaction data from explorer pages, performs sophisticated risk analysis, and instantly alerts your team about significant events across multiple blockchains. Key Components Blockchain Webhook - Real-time trigger that activates when new blocks are detected Data Normalizer - Standardizes blockchain data across different networks ScrapeGraphAI Extractor - AI-powered transaction data extraction from blockchain explorers Risk Analyzer - Advanced risk scoring based on transaction patterns and values Smart Filter - Intelligently routes only significant events for alerts Slack Alert System - Instant formatted notifications to your team 📊 Risk Analysis Specifications The template performs comprehensive risk analysis with the following parameters: | Risk Factor | Threshold | Score Impact | Description | |-------------|-----------|--------------|-------------| | High-Value Transactions | >$10,000 USD | +15 per transaction | Individual transactions exceeding threshold | | Block Volume | >$1M USD | +20 points | Total block transaction volume | | Block Volume | >$100K USD | +10 points | Moderate block transaction volume | | Failure Rate | >10% | +15 points | Percentage of failed transactions in block | | Multiple High-Value | >3 transactions | Alert trigger | Multiple large transactions in single block | | Critical Failure Rate | >20% | Alert trigger | Extremely high failure rate indicator | Risk Levels: High Risk**: Score ≥ 50 (Immediate alerts) Medium Risk**: Score ≥ 25 (Standard alerts) Low Risk**: Score < 25 (No alerts) 🌐 Supported Blockchains | Blockchain | Explorer | Native Support | Transaction Detection | |------------|----------|----------------|----------------------| | Ethereum | Etherscan | ✅ Full | High-value, DeFi, NFT | | Bitcoin | Blockchair | ✅ Full | Large transfers, institutional | | Binance Smart Chain | BscScan | ✅ Full | DeFi, high-frequency trading | | Polygon | PolygonScan | ✅ Full | Layer 2 activity monitoring | 🛠️ Setup Instructions Estimated setup time: 15-20 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Slack workspace with webhook or bot token Blockchain data source (Moralis, Alchemy, or direct node access) Basic understanding of blockchain explorers Step-by-Step Configuration 1. Install Community Nodes Install required community nodes npm install n8n-nodes-scrapegraphai 2. Configure ScrapeGraphAI Credentials Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials Enter your API key from ScrapeGraphAI dashboard Test the connection to ensure proper functionality 3. Set up Slack Integration Add Slack OAuth2 or webhook credentials Configure your target channel for blockchain alerts Test message delivery to ensure notifications work Customize alert formatting preferences 4. Configure Blockchain Webhook Set up the webhook endpoint for blockchain data Configure your blockchain data provider (Moralis, Alchemy, etc.) Ensure webhook payload includes block number and blockchain identifier Test webhook connectivity with sample data 5. Customize Risk Parameters Adjust high-value transaction threshold (default: $10,000) Modify risk scoring weights based on your needs Configure blockchain-specific risk factors Set failure rate thresholds for your use case 6. Test and Validate Send test blockchain data to trigger the workflow Verify ScrapeGraphAI extraction accuracy Check risk scoring calculations Confirm Slack alerts are properly formatted and delivered 🔄 Workflow Customization Options Modify Risk Analysis Adjust high-value transaction thresholds per blockchain Add custom risk factors (contract interactions, specific addresses) Implement whitelist/blacklist address filtering Configure time-based risk adjustments Extend Blockchain Support Add support for additional blockchains (Solana, Cardano, etc.) Customize explorer URL patterns Implement chain-specific transaction analysis Add specialized DeFi protocol monitoring Enhance Alert System Add email notifications alongside Slack Implement severity-based alert routing Create custom alert templates Add alert escalation rules Advanced Analytics Add transaction pattern recognition Implement anomaly detection algorithms Create blockchain activity dashboards Add historical trend analysis 📈 Use Cases Crypto Trading**: Monitor large market movements and whale activity DeFi Security**: Track protocol interactions and unusual contract activity Compliance Monitoring**: Detect suspicious transaction patterns Institutional Custody**: Alert on high-value transfers and security events Smart Contract Monitoring**: Track contract interactions and state changes Market Intelligence**: Analyze blockchain activity for trading insights 🚨 Important Notes Respect ScrapeGraphAI API rate limits and terms of service Implement appropriate delays to avoid overwhelming blockchain explorers Keep your API credentials secure and rotate them regularly Monitor API usage to manage costs effectively Consider blockchain explorer rate limits for high-frequency monitoring Ensure compliance with relevant financial regulations Regularly update risk parameters based on market conditions 🔧 Troubleshooting Common Issues: ScrapeGraphAI extraction errors: Check API key and account status Webhook trigger failures: Verify webhook URL and payload format Slack notification failures: Check bot permissions and channel access False positive alerts: Adjust risk scoring thresholds Missing transaction data: Verify blockchain explorer accessibility Rate limit errors: Implement delays and monitor API usage Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Blockchain explorer API documentation Slack API documentation for advanced configurations Cryptocurrency compliance and regulatory guidelines

Copyright Infringement Detector with ScrapeGraphAI Analysis and Legal Action Automation 🎯 Target Audience Intellectual property lawyers and legal teams Brand protection specialists Content creators and publishers Marketing and brand managers Digital rights management teams Copyright enforcement agencies Media companies and publishers E-commerce businesses with proprietary content Software and technology companies Creative agencies protecting client work 🚀 Problem Statement Manual monitoring for copyright infringement is time-consuming, often reactive rather than proactive, and can miss critical violations that damage brand reputation and revenue. This template solves the challenge of automatically detecting copyright violations, analyzing infringement patterns, and providing immediate legal action recommendations using AI-powered web scraping and automated legal workflows. 🔧 How it Works This workflow automatically scans the web for potential copyright violations using ScrapeGraphAI, analyzes content similarity, determines legal action requirements, and provides automated alerts for immediate response to protect intellectual property rights. Key Components Schedule Trigger - Runs automatically every 24 hours to monitor for new infringements ScrapeGraphAI Web Search - Uses AI to search for potential copyright violations across the web Content Comparer - Analyzes potential infringements and calculates similarity scores Infringement Detector - Determines legal action required and creates case reports Legal Action Trigger - Routes cases based on severity and urgency Brand Protection Alert - Sends urgent alerts for high-priority violations Monitoring Alert - Tracks medium-risk cases for ongoing monitoring 📊 Detection and Analysis Specifications The template monitors and analyzes the following infringement types: | Infringement Type | Detection Method | Risk Level | Action Required | |-------------------|------------------|------------|-----------------| | Exact Text Match | High similarity score (>80%) | High | Immediate cease & desist | | Paraphrased Content | Moderate similarity (50-80%) | Medium | Monitoring & evidence collection | | Unauthorized Brand Usage | Brand name detection in content | High | Legal consultation | | Competitor Usage | Known competitor domain detection | High | DMCA takedown | | Image/Video Theft | Visual content analysis | High | Immediate action | | Domain Infringement | Suspicious domain patterns | Medium | Investigation | 🛠️ Setup Instructions Estimated setup time: 30-35 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Telegram or other notification service credentials Legal team contact information Copyrighted content database Step-by-Step Configuration 1. Install Community Nodes Install required community nodes npm install n8n-nodes-scrapegraphai 2. Configure ScrapeGraphAI Credentials Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials Enter your API key from ScrapeGraphAI dashboard Test the connection to ensure it's working 3. Set up Schedule Trigger Configure the monitoring frequency (default: every 24 hours) Adjust timing to match your business hours Set appropriate timezone for your legal team 4. Configure Copyrighted Content Database Update the Content Comparer node with your protected content Add brand names, slogans, and unique phrases Include competitor and suspicious domain lists Set similarity thresholds for different content types 5. Customize Legal Action Rules Update the Infringement Detector node with your legal thresholds Configure action plans for different infringement types Set up case priority levels and response timelines Define evidence collection requirements 6. Set up Alert System Configure Telegram bot or other notification service Set up different alert types for different severity levels Configure legal team contact information Test alert delivery and formatting 7. Test and Validate Run the workflow manually with test search terms Verify all detection steps complete successfully Test alert system with sample infringement data Validate legal action recommendations 🔄 Workflow Customization Options Modify Detection Parameters Adjust similarity thresholds for different content types Add more sophisticated text analysis algorithms Include image and video content detection Customize brand name detection patterns Extend Legal Action Framework Add more detailed legal action plans Implement automated cease and desist generation Include DMCA takedown automation Add court filing preparation workflows Customize Alert System Add integration with legal case management systems Implement tiered alert systems (urgent, high, medium, low) Add automated evidence collection and documentation Include reporting and analytics dashboards Output Customization Add integration with legal databases Implement automated case tracking Create compliance reporting systems Add trend analysis and pattern recognition 📈 Use Cases Brand Protection**: Monitor unauthorized use of brand names and logos Content Protection**: Detect plagiarism and content theft Legal Enforcement**: Automate initial legal action processes Competitive Intelligence**: Monitor competitor content usage Compliance Monitoring**: Ensure proper attribution and licensing Evidence Collection**: Automatically document violations for legal proceedings 🚨 Important Notes Respect website terms of service and robots.txt files Implement appropriate delays between requests to avoid rate limiting Regularly review and update copyrighted content database Monitor API usage to manage costs effectively Keep your credentials secure and rotate them regularly Ensure compliance with local copyright laws and regulations Consult with legal professionals before taking automated legal action Maintain proper documentation for all detected violations 🔧 Troubleshooting Common Issues: ScrapeGraphAI connection errors: Verify API key and account status False positive detections: Adjust similarity thresholds and detection parameters Alert delivery failures: Check notification service credentials Legal action errors: Verify legal team contact information Schedule trigger failures: Check timezone and interval settings Content analysis errors: Review the Code node's JavaScript logic Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Copyright law resources and best practices Legal automation and compliance guidelines Brand protection and intellectual property resources

Carbon Footprint Tracker with ScrapeGraphAI Analysis and ESG Reporting Automation 🎯 Target Audience Sustainability managers and ESG officers Environmental compliance teams Corporate social responsibility (CSR) managers Energy and facilities managers Supply chain sustainability coordinators Environmental consultants Green building certification teams Climate action plan coordinators Regulatory compliance officers Corporate reporting and disclosure teams 🚀 Problem Statement Manual carbon footprint calculation and ESG reporting is complex, time-consuming, and often inaccurate due to fragmented data sources and outdated emission factors. This template solves the challenge of automatically collecting environmental data, calculating accurate carbon footprints, identifying reduction opportunities, and generating comprehensive ESG reports using AI-powered data collection and automated sustainability workflows. 🔧 How it Works This workflow automatically collects energy and transportation data using ScrapeGraphAI, calculates comprehensive carbon footprints across all three scopes, identifies reduction opportunities, and generates automated ESG reports for sustainability compliance and reporting. Key Components Schedule Trigger - Runs automatically every day at 8:00 AM to collect environmental data Energy Data Scraper - Uses ScrapeGraphAI to extract energy consumption data and emission factors Transport Data Scraper - Collects transportation emission factors and fuel efficiency data Footprint Calculator - Calculates comprehensive carbon footprint across Scope 1, 2, and 3 emissions Reduction Opportunity Finder - Identifies cost-effective carbon reduction opportunities Sustainability Dashboard - Creates comprehensive sustainability metrics and KPIs ESG Report Generator - Automatically generates ESG compliance reports Create Reports Folder - Organizes reports in Google Drive Save Report to Drive - Stores final reports for stakeholder access 📊 Carbon Footprint Analysis Specifications The template calculates and tracks the following emission categories: | Emission Scope | Category | Data Sources | Calculation Method | Example Output | |----------------|----------|--------------|-------------------|----------------| | Scope 1 (Direct) | Natural Gas | EPA emission factors | Consumption × 11.7 lbs CO2/therm | 23,400 lbs CO2 | | Scope 1 (Direct) | Fleet Fuel | EPA fuel economy data | Miles ÷ MPG × 19.6 lbs CO2/gallon | 11,574 lbs CO2 | | Scope 2 (Electricity) | Grid Electricity | EPA emission factors | kWh × 0.92 lbs CO2/kWh | 46,000 lbs CO2 | | Scope 3 (Indirect) | Employee Commute | EPA transportation data | Miles × 0.77 lbs CO2/mile | 19,250 lbs CO2 | | Scope 3 (Indirect) | Air Travel | EPA aviation factors | Miles × 0.53 lbs CO2/mile | 26,500 lbs CO2 | | Scope 3 (Indirect) | Supply Chain | Estimated factors | Electricity × 0.1 multiplier | 4,600 lbs CO2 | 🛠️ Setup Instructions Estimated setup time: 25-30 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Google Drive API access for report storage Organizational energy and transportation data ESG reporting requirements and standards Step-by-Step Configuration 1. Install Community Nodes Install required community nodes npm install n8n-nodes-scrapegraphai 2. Configure ScrapeGraphAI Credentials Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials Enter your API key from ScrapeGraphAI dashboard Test the connection to ensure it's working 3. Set up Schedule Trigger Configure the daily schedule (default: 8:00 AM UTC) Adjust timezone to match your business hours Set appropriate frequency for your reporting needs 4. Configure Data Sources Update the Energy Data Scraper with your energy consumption sources Configure the Transport Data Scraper with your transportation data Set up organizational data inputs (employees, consumption, etc.) Customize emission factors for your region and industry 5. Customize Carbon Calculations Update the Footprint Calculator with your organizational data Configure scope boundaries and calculation methodologies Set up industry-specific emission factors Adjust for renewable energy and offset programs 6. Configure Reduction Analysis Update the Reduction Opportunity Finder with your investment criteria Set up cost-benefit analysis parameters Configure priority scoring algorithms Define implementation timelines and effort levels 7. Set up Report Generation Configure Google Drive integration for report storage Set up ESG report templates and formats Define stakeholder access and permissions Test report generation and delivery 8. Test and Validate Run the workflow manually with test data Verify all calculation steps complete successfully Check data accuracy and emission factor validity Validate ESG report compliance and formatting 🔄 Workflow Customization Options Modify Data Collection Add more energy data sources (renewables, waste, etc.) Include additional transportation modes (rail, shipping, etc.) Integrate with building management systems Add real-time monitoring and IoT data sources Extend Calculation Framework Add more Scope 3 categories (waste, water, etc.) Implement industry-specific calculation methodologies Include carbon offset and credit tracking Add lifecycle assessment (LCA) capabilities Customize Reduction Analysis Add more sophisticated ROI calculations Implement scenario modeling and forecasting Include regulatory compliance tracking Add stakeholder engagement metrics Output Customization Add integration with sustainability reporting platforms Implement automated stakeholder notifications Create executive dashboards and visualizations Add compliance monitoring and alert systems 📈 Use Cases ESG Compliance Reporting**: Automate sustainability disclosure requirements Carbon Reduction Planning**: Identify and prioritize reduction opportunities Regulatory Compliance**: Meet environmental reporting mandates Stakeholder Communication**: Generate transparent sustainability reports Investment Due Diligence**: Provide ESG data for investors and lenders Supply Chain Sustainability**: Track and report on Scope 3 emissions 🚨 Important Notes Respect data source terms of service and rate limits Implement appropriate delays between requests to avoid rate limiting Regularly review and update emission factors for accuracy Monitor API usage to manage costs effectively Keep your credentials secure and rotate them regularly Ensure compliance with local environmental reporting regulations Validate calculations against industry standards and methodologies Maintain proper documentation for audit and verification purposes 🔧 Troubleshooting Common Issues: ScrapeGraphAI connection errors: Verify API key and account status Data source access issues: Check website accessibility and rate limits Calculation errors: Verify emission factors and organizational data Report generation failures: Check Google Drive permissions and quotas Schedule trigger failures: Check timezone and cron expression Data accuracy issues: Validate against manual calculations and industry benchmarks Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance EPA emission factor databases and methodologies GHG Protocol standards and calculation guidelines ESG reporting frameworks and compliance requirements Sustainability reporting best practices and standards

Enhance Your Workflow with 2Ndmoises_Generator AI This n8n workflow integrates with Replicate’s moicarmonas/2ndmoises_generator model to generate custom outputs based on your prompt. It handles authentication, triggers the prediction, monitors progress, and processes the final result automatically. 📌 Section 1: Trigger & Authentication ⚡ On Clicking ‘Execute’ (Manual Trigger) Purpose: Start the workflow manually whenever you want to run it. Benefit: Great for testing or running on-demand without needing automation. 🔑 Set API Key (Set Node) Purpose: Stores your Replicate API key in the workflow. How it works: Adds your API key as a variable that other nodes can reference. Benefit: Keeps credentials secure and reusable. 📌 Section 2: Sending the AI Request 📤 Create Prediction (HTTP Request Node) Purpose: Sends a request to the Replicate API to start generating output with the model. Input Parameters: prompt (text you provide) seed (for reproducibility) width / height / lora\_scale (generation settings) Benefit: Allows full customization of the AI’s generation process. 🆔 Extract Prediction ID (Code Node) Purpose: Pulls out the Prediction ID and status from the API response. Why important: The ID is required to check the job’s progress later. Benefit: Automates polling without manual tracking. 📌 Section 3: Polling & Waiting ⏳ Wait (Wait Node) Purpose: Adds a short pause (2 seconds) between checks. Benefit: Prevents hitting the API too quickly and avoids errors. 🔄 Check Prediction Status (HTTP Request Node) Purpose: Calls Replicate again to ask if the prediction is finished. Benefit: Automates progress monitoring without manual refresh. ✅ Check If Complete (If Node) Purpose: Decides whether the model has finished generating. Paths: True → Move on to processing the result. False → Go back to Wait and recheck. Benefit: Ensures the workflow loops until a final output is ready. 📌 Section 4: Handling the Result 📦 Process Result (Code Node) Purpose: Cleans up the final API response and extracts: Status Output (generated result) Metrics Timestamps (created\_at / completed\_at) Model info Benefit: Provides a structured, ready-to-use output for other workflows or integrations. 📊 Workflow Overview Table | Section | Node Name | Purpose | | ----------------- | ----------------------- | ---------------------------- | | 1. Trigger & Auth | On Clicking ‘Execute’ | Starts the workflow manually | | | Set API Key | Stores API credentials | | 2. AI Request | Create Prediction | Sends request to Replicate | | | Extract Prediction ID | Gets prediction ID + status | | 3. Polling | Wait | Adds delay before recheck | | | Check Prediction Status | Monitors progress | | | Check If Complete | Routes based on completion | | 4. Result | Process Result | Extracts and cleans output | | Notes | Sticky Note | Explains setup + model info | 🎯 Key Benefits 🔐 Secure authentication using Set node for API key storage. 🤖 Hands-free generation — just provide a prompt, the workflow handles everything else. 🔄 Automated polling ensures you always get the final result without manual checking. 📦 Clean structured output ready for downstream use in apps, dashboards, or notifications.

This workflow allows you to add a datapoint to Beeminder when a new activity is added to Strava. You can use this workflow to keep a track of your fitness activities and connect Strava with Beeminder. If you want to keep a track of different activities like the number of hours worked in a week or the number of tasks completed, you can use the relevant node. For example, you can use the Clockify Trigger node or the Toggl Trigger node.