Workflow Templates

Overview This n8n workflow automatically retrieves Brevo contact reports and inserts summarized engagement data into NocoDB. It groups campaign activity by email, creating a clean, unified record that includes sent, delivered, opened, clicked, and blacklisted events. This setup keeps your CRM or marketing database synchronized with the latest Brevo email performance data. ✅ Tasks ⏰ Runs automatically on schedule or manually 🌐 Fetches contact activity data from Brevo API 🧩 Groups all campaign activity per email 💾 Inserts summarized data into NocoDB ⚙️ Keeps engagement metrics synced between Brevo and NocoDB 🛠 How to Use 🧱 Prepare your NocoDB table Create a table with fields for: email, messagesSent, delivered, opened, clicked, done, and blacklisted. 🔑 Connect your Brevo credentials Add your Brevo API Key in the HTTP Request node to fetch contact data securely. 🧮 Review the Code Nodes These nodes group contact activity by email and prepare a single dataset for insertion. 🚀 Run or schedule the workflow Execute it manually or use a Schedule Trigger to automate the data sync process. 📌 Notes 🗂 Make sure the field names in NocoDB match those used in the workflow. 🔐 Keep your Brevo API Key secure and private. ⚙️ The workflow can be expanded to include additional fields or filters. 📊 Use the data for engagement analytics, segmentation, or campaign performance tracking.

Description: Ensure your customer SLAs never slip with this n8n automation template. The workflow runs on a schedule, fetching open tickets from Zendesk, calculating SLA time remaining, and sending proactive alerts to Slack when tickets approach breach thresholds (75% and 90%). It also updates ticket priority in Zendesk and logs compliance metrics to Google Sheets for reporting. Perfect for support operations, CX teams, and SaaS companies looking to maintain SLA compliance and reduce response delays automatically. ✅ What This Template Does (Step-by-Step) ⏰ Run Every Hour: Automatically triggers every hour to check for SLA-sensitive tickets. 📥 Fetch All Open Zendesk Tickets: Pulls all tickets via the Zendesk API, returning essential fields: ID, status, created_at, sla_due, and priority. 🔍 Filter Only “Open” Tickets: Excludes closed, on-hold, or pending tickets — monitoring focuses only on actionable cases. ⏱️ Calculate SLA Time Remaining: Computes total SLA duration, remaining minutes, and % of SLA consumed for each ticket. 🟡 Warn at 75% Threshold: When 75% of the SLA window has passed, automatically sends a Slack warning to the #general-information channel. 🔴 Escalate at 90% Threshold: For tickets nearing breach (≥90%), the workflow updates Zendesk ticket priority to “High,” adds escalation notes, and notifies the support team for immediate action. 📊 Log SLA Compliance in Google Sheets: Each ticket’s SLA metrics (ID, % elapsed, time remaining, timestamp) are appended to a Google Sheet for tracking and reporting. ✅ No-Ticket Confirmation: If no open tickets exist, the workflow posts a “✅ No open tickets” message to Slack — keeping teams informed of a clear queue. 🧠 Key Features ⏱️ Automated SLA tracking and escalation 📊 Real-time logging to Google Sheets ⚡ Hourly auto-trigger — no manual checks needed 📢 Slack alerts at warning and critical thresholds 🔄 Dynamic Zendesk ticket updates via API 💼 Use Cases 💬 Proactively manage customer support SLAs 🚨 Automatically escalate critical tickets before breach 📈 Maintain transparent SLA compliance reporting 📢 Keep your support team updated in real time 📦 Required Integrations Zendesk API – for ticket retrieval and updates Slack API – for alert notifications Google Sheets – for compliance and reporting logs 🎯 Why Use This Template? ✅ Prevent SLA breaches before they happen ✅ Automate escalation and communication ✅ Provide real-time visibility to support leads ✅ Build a historical SLA performance dataset

Description: Guarantee that only fully compliant stories and tasks make it into your release with this n8n automation template. The workflow monitors Jira for issue updates and link changes, validates whether each story meets the Definition of Done (DoD), and automatically flags non-compliant items. It also creates a tracking record in Monday.com for unresolved blockers and sends Slack alerts summarizing readiness status for every version. Perfect for release managers, QA leads, and engineering teams who need an automated guardrail for production readiness. ✅ What This Template Does (Step-by-Step) 🎯 Jira Webhook Trigger: Activates automatically when an issue is updated or linked in Jira — ideal for continuous readiness validation. 📋 Fetch Full Issue Details: Retrieves the complete issue payload, including custom fields, status, and Definition of Done flags. 🔄 Batch Processing (1-by-1): Ensures each issue is validated individually, allowing precise error handling and clean audit trails. ✅ Check Definition of Done (DoD): Evaluates whether the customfield_DoD field is marked as true — a key signal of readiness for release. ⚠️ Flag Non-Compliant Issues: If DoD isn’t met, marks the issue as “Non-Compliant” with the reason “Definition of Done not met.” 📊 Create Tracking Record in Monday.com: Logs non-compliant issues to a dedicated Release Issues board for visibility and coordination with cross-functional teams. 📢 Send Slack Notifications: Posts to the #release-updates channel summarizing compliant vs non-compliant items per version, helping the team take timely action. 🧠 Key Features 🚦 Real-time Jira readiness validation ✅ Automated DoD enforcement before release 📊 Monday.com tracker for all non-compliant issues 📢 Slack summary notifications for release teams ⚙️ Batch-wise validation for scalable QA 💼 Use Cases 🚀 Enforce Definition of Done across linked Jira stories 📦 Automate pre-release checks for every version increment 🧩 Provide visibility into blockers via Monday.com dashboard 📢 Keep engineering and QA teams aligned on release status 📦 Required Integrations Jira Software Cloud API – to monitor issue updates and retrieve details Monday.com API – to log and track non-compliant items Slack API – for real-time release alerts 🎯 Why Use This Template? ✅ Eliminates manual pre-release validation ✅ Reduces release delays due to missed criteria ✅ Keeps all stakeholders aligned on readiness status ✅ Creates a transparent audit trail of compliance

Tags*: AI Agent, MCP Server, n8n API, Monitoring, Debugging, Workflow Analytics, Automation Context Hi! I’m Samir — a Supply Chain Engineer and Data Scientist based in Paris, and founder of LogiGreen Consulting. This workflow is part of my latest project: an AI assistant that automatically analyses n8n workflow executions, detects failures, and identifies root causes through natural conversation with Claude Desktop. > Turn your automation logs into intelligent conversations with an AI that understands your workflows. The idea is to use Claude Desktop to help monitor and debug your workflows deployed in production. The workflow shared here is part of the setup. 📬 For business inquiries, you can find me on LinkedIn Who is this template for? This template is designed for automation engineers, data professionals, and AI enthusiasts who manage multiple workflows in n8n and want a smarter way to track errors or performance without manually browsing execution logs. If you’ve ever discovered a failed workflow hours after it happened — this is for you. What does this workflow do? This workflow acts as the bridge between your n8n instance and the Claude MCP Server. It exposes three main routes that can be triggered via a webhook: get_active_workflows → Fetches all currently active workflows get_workflow_executions → Retrieves the latest executions and calculates health KPIs get_execution_details → Extracts detailed information about failed executions for debugging Each request is automatically routed and processed, providing Claude with structured execution data for real-time analysis. How does it fit in the overall setup? Here’s the complete architecture: Claude Desktop ←→ MCP Server ←→ n8n Monitor Webhook ←→ n8n API The MCP Server (Python-based) communicates with your n8n instance through this workflow. The Claude Desktop app can then query workflow health, execution logs, and error patterns using natural language. The n8n workflow aggregates, cleans, and returns the relevant metrics (failures, success rates, timing, alerts). 📘 The full concept and architecture are explained in my article published on my blog: 👉 Deploy your AI Assistant to Monitor and Debug n8n Workflows using Claude and MCP 🎥 Tutorial The full setup tutorial (with source code and demo) is available on YouTube: How does it work? 🌐 Webhook Trigger receives the MCP server requests 🔀 Switch node routes actions based on "action" parameter ⚙️ HTTP Request nodes fetch execution and workflow data via the n8n API 🧮 A Code node calculates KPIs (success/failure rates, timing, alerts) 📤 The processed results are returned as JSON for Claude to interpret Example use cases Once connected, you can ask Claude questions like: “Show me all workflows that failed in the last 25 executions.” “Why is my Bangkok Meetup Scraper workflow failing?” “Give me a health report of my n8n instance.” Claude will reply with structured insights, including failure patterns, node diagnostics, and health status indicators (🟢🟡🔴). What do I need to get started? You’ll need: A self-hosted n8n instance Claude Desktop** app installed The MCP server source code (shared in the tutorial description) The webhook URL from this workflow is configured in your .env file Follow the tutorial for more details, don't hesitate to leave your questions in the comment section. Next Steps 🗒️ Use the sticky notes inside the workflow to: Replace <YOUR_N8N_INSTANCE> with your own URL Test the webhook routes individually using the “Execute Workflow” button Connect the MCP server and Claude Desktop to start monitoring This template was built using n8n v.116.2 Submitted: November 2025

TEMPLATE DESCRIPTION Eliminate manual farm operations logging and gain real-time visibility into machinery performance, fuel consumption, and equipment breakdowns. This webhook-based workflow automatically captures operational data from your web interface and organizes it across three structured Google Sheets—giving you audit-ready records without the 30-60 minutes of daily paperwork. Who's it for Farm operations managers running 200-2000 acre operations who need enterprise-grade operational tracking without enterprise software costs. Perfect for teams struggling with incomplete manual logs, delayed maintenance alerts, or unclear fuel waste patterns. How it works The webhook receives JSON data from your web UI capturing operator details, timestamps, fuel usage, breakdown incidents, and field work completion. Data is automatically parsed and routed to three separate Google Sheets: daily operations log, fuel consumption tracking, and equipment maintenance records. Each entry is timestamped and validated for completeness. ⚙️ How to set up 📥 Import the workflow JSON into your n8n instance. 🔗 Configure the webhook URL and add your Google Sheets credentials. 📊 Create three Google Sheets with the provided column headers (main_logs, fuel, breakdowns), then update the workflow with your Sheet IDs. 🚀 Deploy the webhook and integrate the URL into your existing web form or data collection UI. ⏱️ Setup takes less than 30 minutes. 🔐 Security note: Store Google Sheets credentials securely using n8n's credential system. Never expose webhook URLs publicly without authentication. 📋 Requirements 🧩 Active n8n instance (cloud or self-hosted) 🟢 Google account with Sheets API access 📲 Web form or mobile app that can POST JSON data to a webhook URL 📊 Three Google Sheets for operations, fuel, and maintenance data 🛠️ How to customize the workflow 🧩 Modify the JSON parsing nodes to match your specific data structure. 🚨 Add conditional routing for priority alerts, for example critical breakdowns trigger Slack notifications. 📦 Integrate additional sheets for inventory tracking or employee time logs. 📈 Add data validation rules or calculated columns in Google Sheets for automatic fuel efficiency metrics and maintenance forecasting. 🚜 Want this working in your operation? This template gives you the core engine. What most farms need is a version tuned to their machines, their operators, and their reporting requirements. If you want this set up, customized, or fully implemented for your operation, I can: Connect this to your existing web or mobile capture system Map your machines, operators, and fields Add automatic alerts for breakdowns, fuel abuse, or missed logs Create clean, management-ready reports from the data Make sure it runs reliably day after day with no babysitting This is built for real farms running real equipment, not demo data. 📧 Email: vaughnai2023@gmail.com 🔗 LinkedIn: https://www.linkedin.com/in/vaughnbotha/

How It Works: The 5-Node Certificate Management Flow 🗓️ This workflow efficiently monitors your domains for certificate expiry. Scheduled Check (Cron Node): This is the workflow's trigger. It's configured to run on a regular schedule, such as every Monday morning, ensuring certificate checks are automated and consistent. List Domains to Monitor (Code Node): This node acts as a static database, storing a list of all the domains you need to track. Check Certificate Expiry (HTTP Request Node): For each domain in your list, this node makes a request to a certificate checking API. The API returns details about the certificate, including its expiry date. Is Certificate Expiring? (If Node): This is the core logic. It compares the expiry date from the API response with the current date. If the certificate is set to expire within a critical timeframe (e.g., less than 30 days), the workflow proceeds to the next step. Send Alert (Slack Node): If the If node determines a certificate is expiring, this node sends a high-priority alert to your team's Slack channel. The message includes the domain name and the exact expiry date, providing all the necessary information for a quick response. How to Set Up Here's a step-by-step guide to get this workflow running in your n8n instance. Prepare Your Credentials & API: Certificate Expiry API: You need an API to check certificate expiry. The workflow uses a sample API, so you may need to adjust the URL and parameters. For production use, you might use a service like Certspotter or a similar tool. Slack Credential: Set up a Slack credential in n8n and get the Channel ID of your security alert channel (e.g., #security-alerts). Import the Workflow JSON: Create a new workflow in n8n and choose "Import from JSON." Paste the JSON code for the "SSL/TLS Certificate Expiry Monitor" workflow. Configure the Nodes: Scheduled Check (Cron): Set the schedule according to your preference (e.g., every Monday at 8:00 AM). List Domains to Monitor (Code): Edit the domainsToMonitor array in the code and add all the domains you want to check. Check Certificate Expiry (HTTP Request): Update the URL to match the certificate checking API you are using. Is Certificate Expiring? (If): The logic is set to check for expiry within 30 days. You can adjust the 30 in the expression new Date(Date.now() + 30 * 24 * 60 * 60 * 1000) to change the warning period. Send Alert (Slack): Select your Slack credential and enter the correct Channel ID. Test and Activate: Manual Test: Run the workflow manually to confirm it fetches certificate data and processes it correctly. You can test with a domain that you know is expiring soon to ensure the alert is triggered. Verify Output: Check your Slack channel to confirm that alerts are formatted and sent correctly. Activate: Once you're confident everything works, activate the workflow. n8n will now automatically monitor your domain certificates on the schedule you set.

Smart IoT Device Health Monitor with AI-Powered Dashboard Analysis and Real-Time Alerting 🎯 Target Audience IT operations and infrastructure teams IoT system administrators and engineers Facility and building management teams Manufacturing and industrial operations managers Smart city and public infrastructure coordinators Healthcare technology administrators Energy and utilities monitoring teams Fleet and asset management professionals Security and surveillance system operators Property and facility maintenance teams 🚀 Problem Statement Monitoring hundreds of IoT devices across multiple dashboards is overwhelming and reactive, often leading to costly downtime, missed maintenance windows, and system failures. This template solves the challenge of proactive IoT device monitoring by automatically analyzing device health metrics, detecting issues before they become critical, and delivering intelligent alerts that help teams maintain optimal system performance. 🔧 How it Works This workflow automatically monitors your IoT dashboard every 30 minutes using AI-powered data extraction, analyzes device health patterns, calculates system-wide health scores, and sends intelligent alerts only when intervention is needed, preventing alert fatigue while ensuring critical issues are never missed. Key Components Schedule Trigger - Runs every 30 minutes for continuous device monitoring AI Dashboard Scraper - Uses ScrapeGraphAI to extract device data from any IoT dashboard without APIs Health Analyzer - Calculates system health scores and identifies problematic devices Smart Alert System - Sends notifications only when health drops below thresholds Telegram Notifications - Delivers formatted alerts with device details and recommendations Activity Logger - Maintains historical records for trend analysis and reporting 📊 Device Health Analysis Specifications The template monitors and analyzes the following device metrics: | Metric Category | Monitored Parameters | Analysis Method | Alert Triggers | Example Output | |-----------------|---------------------|-----------------|----------------|----------------| | Device Status | Online/Offline/Error | Real-time status check | Any offline devices | "Device-A01 is offline" | | Battery Health | Battery percentage | Low battery detection | Below 20% charge | "Sensor-B03 low battery: 15%" | | Temperature | Device temperature | Overheating detection | Above 70°C | "Gateway-C02 overheating: 75°C" | | System Health | Overall health score | Online device ratio | Below 80% health | "System health: 65%" | | Connectivity | Network status | Connection monitoring | Loss of communication | "3 devices offline" | | Performance | Response metrics | Trend analysis | Degraded performance | "Response time increasing" | 🛠️ Setup Instructions Estimated setup time: 15-20 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Telegram bot token and chat ID Access to your IoT dashboard URL Basic understanding of your device naming conventions 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 30 minutes) Adjust timing based on your operational needs: Every 15 minutes: */15 * * * * Every hour: 0 * * * * Every 5 minutes: */5 * * * * 4. Configure Dashboard URL Update the "Get Data" node with your IoT dashboard URL Customize the AI prompt to match your dashboard structure Test data extraction to ensure proper JSON formatting Adjust device field mappings as needed 5. Set up Telegram Notifications Create a Telegram bot using @BotFather Get your chat ID from @userinfobot Configure Telegram credentials in n8n Test message delivery to ensure alerts work 6. Customize Health Thresholds Adjust health score threshold (default: 80%) Set battery alert level (default: 20%) Configure temperature warning (default: 70°C) Customize alert conditions based on your requirements 7. Test and Validate Run the workflow manually with your dashboard Verify device data extraction accuracy Test alert conditions and message formatting Confirm logging functionality works correctly 🔄 Workflow Customization Options Modify Monitoring Frequency Adjust schedule for different device criticality levels Add business hours vs. off-hours monitoring Implement variable frequency based on system health Add manual trigger for on-demand monitoring Extend Device Analysis Add more device metrics (memory, CPU, network bandwidth) Implement predictive maintenance algorithms Include environmental sensors (humidity, air quality) Add device lifecycle and warranty tracking Customize Alert Logic Implement escalation rules for critical alerts Add alert suppression during maintenance windows Create different alert channels for different severity levels Include automated ticket creation for persistent issues Output Customization Add integration with monitoring platforms (Grafana, Datadog) Implement email notifications for management reports Create executive dashboards with health trends Add integration with maintenance management systems 📈 Use Cases Industrial IoT Monitoring**: Track manufacturing equipment and sensors Smart Building Management**: Monitor HVAC, lighting, and security systems Fleet Management**: Track vehicle telematics and diagnostic systems Healthcare Device Monitoring**: Ensure medical device uptime and performance Smart City Infrastructure**: Monitor traffic lights, environmental sensors, and public systems Energy Grid Monitoring**: Track smart meters and distribution equipment 🚨 Important Notes Respect your dashboard's terms of service and rate limits Implement appropriate delays between requests to avoid overloading systems Regularly review and update device thresholds based on operational experience Monitor ScrapeGraphAI API usage to manage costs effectively Keep your credentials secure and rotate them regularly Ensure alert recipients are available to respond to critical notifications Consider implementing backup monitoring systems for critical infrastructure Maintain device inventories and update monitoring parameters as systems evolve 🔧 Troubleshooting Common Issues: ScrapeGraphAI connection errors: Verify API key and account status Dashboard access issues: Check URL accessibility and authentication requirements Data extraction failures: Review AI prompt and dashboard structure changes Missing device data: Verify device naming conventions and field mappings Alert delivery failures: Check Telegram bot configuration and chat permissions False alerts: Adjust health thresholds and alert logic conditions Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Telegram Bot API documentation IoT platform-specific monitoring best practices Device manufacturer monitoring guidelines Industrial IoT monitoring standards and frameworks

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!

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.

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.