Workflow Templates

Fetches workflow definitions from within n8n, selecting only the ones that have one or more (configurable) assigned tags and then: Derives a suitable backup filename by reducing the workflow name to a string with alphanumeric characters and no-spaces Note: This isn't bulletproof, but works as long as workflow names aren't too crazy. Determines which workflows need to be backed up based on whether each one: has been modified. (Note: Even repositioning a node counts.) ...or... is new. (Note: Renaming counts as this.) Commits JSON copies of each workflow, as necessary, to a Gitlab repository with a generated, date-stamped commit message. Setup Credentials Create a Gitlab Credentials item and assign it to all Gitlab nodes. Create an n8n Credentials item and assign it to the n8n node Note: This was tested with http://localhost:5678/api/v1 but should work with any reachable n8n instance and API key. Modify these values in the "Globals" Node gitlab_owner - {{your gitlab account}} gitlab_project - {{ your gitlab project name }} gitlab_workflow_path - {{ subdirectory in the project where backup files should be saved/committed }} tags_to_match_for_backup - {{tag(s) to match for backup selection}} *ALERT: According to the n8n node's Filters -> tags field annotations, and API documentation, this supports a CSV list of multiple tags (e.g. tag1,tag2), but the API behavior requires workflows to have all-of the listed tags, not any-of them.* See: https://github.com/n8n-io/n8n/issues/10348 TL/DR - Don't expect a multiple tag list to be more inclusive. Possible workaround: To match more than one tag value, duplicate the n8n node into multiple single-tag matches, or split and iterate multiple values, and merge the results. Possible Enhancements Make the branch ("Reference") for all the gitlab nodes configurable. Fixed on all as "main" in the template. Add an n8n node to generate an audit and store the output in gitlab along with the backups. Extend the workflow at the end to create a Gitlab release/tag whenever any backup files are actually updated or created.

🎥 Bulk TikTok Video Download Without Watermark to Google Drive This workflow automates the process of downloading TikTok videos and uploading them to Google Drive. It reads TikTok URLs from a Google Sheet, downloads the video using the TikTok Video Downloader — a tool for downloading TikTok videos without watermark in HD quality — uploads it to Drive, makes it public, and updates the same sheet with the Drive link. 🔧 What It Does ✅ Manually triggered when ready to run. 📄 Reads TikTok URLs from a Google Sheet. 🔁 Loops through each URL one at a time. 🌐 Fetches video download links using the TikTok Video Downloader — a reliable TikTok video downloader without watermark. ⬇️ Downloads each video in high-definition (HD) format using the direct media link. ☁️ Uploads the video to Google Drive. 🔓 Sets public sharing permission for the video. ✏️ Updates the original Google Sheet with the public Drive URL. 📋 Google Sheet Example Make sure your sheet has at least these columns: | url | drive_link (to be auto-filled) | |-------------------------------------|--------------------------------| | https://www.tiktok.com/@user1... | (blank initially) | | https://www.tiktok.com/@user2... | (blank initially) | > The workflow reads from url and fills in drive_link after upload. 🧩 Nodes Used | Node Name | Type | Purpose | |------------------------------|-------------------|-------------------------------------------------------| | When clicking ‘Execute’ | Manual Trigger | Starts the workflow manually | | Get Data From Google Sheets | Google Sheets | Fetches rows (TikTok URLs) | | Loop Over Items | Split In Batches | Iterates over each row | | Call TikTok Downloader | HTTP Request | Gets video download link from TikTok Video Downloader | | Wait | Wait | Optional delay to prevent overload | | Download File | HTTP Request | Downloads HD video using media link | | Upload File In Google Drive | Google Drive | Uploads the video to Google Drive | | Set Public Permission | Google Drive | Makes the uploaded file publicly accessible | | Update Row In Google Sheet | Google Sheets | Adds Drive link to the same row | | Sleep | Wait | Small delay between each iteration | 📝 Requirements ✅ Google API credentials (Service Account) with access to: Google Sheets Google Drive 🔐 RapidAPI Key for TikTok Video Downloader – a TikTok video downloader without watermark (HD supported) 🗂 A Google Sheet with a url column containing TikTok video URLs 🧩 Challenges Solved | ❗ Challenge | ✅ Solution | |-------------|-------------| | TikTok video URLs often have watermarks and low quality | Used TikTok Video Downloader API for HD + no watermark download links | | No easy way to bulk download and organize TikToks | Automated fetching, downloading, and uploading using n8n + Google Drive | | Manual video saving and re-uploading to Drive is time-consuming | Eliminated all manual steps with a fully automated workflow | | Tracking which videos are already processed | Automatically updates the Google Sheet row with the final Drive link | | Drive files are private by default | Automatically sets public sharing permission on uploaded videos | | Risk of API rate limits or throttling | Added Wait nodes and batch processing to avoid overload | 🎁 Benefits | 🌟 Benefit | 💬 Description | |------------|----------------| | 🚀 Saves Time | Fully automates a previously manual workflow | | 🎥 High Quality Content | Videos downloaded are HD + watermark-free — ready for reuse or archives | | 🔁 Reusable Setup | Can process unlimited TikTok URLs via the Google Sheet | | 📊 Organized Output | Keeps track of source URL and uploaded Drive link in a single sheet | | 🔐 Secure but Shareable | Drive links are auto-shared publicly while remaining under your control | | 🔄 Scalable | Can be run daily, weekly, or triggered by new rows — completely scalable | | 💸 Cost-Effective | No need for paid tools or manual freelancers — runs on n8n + free APIs | 💡 Use Cases Content curation from TikTok Archiving user-submitted TikToks Automating social-to-cloud workflows Bulk migration of video content Saving TikTok videos in HD without watermark for sharing or archiving 📌 Tips Replace manual trigger with Cron for full automation. Use the TikTok Video Downloader responsibly — check API limits. Store metadata (e.g., uploader, hashtags) in additional Google Sheet columns. This tool helps ensure you're always downloading high-quality TikTok videos without watermark.

Apply to jobs automatically from Google Sheets with status tracking Who's it for Job seekers who want to streamline their application process, save time on repetitive tasks, and never miss following up on applications. Perfect for anyone managing multiple job applications across different platforms. What it does This workflow automatically applies to jobs from a Google Sheet, tracks application status, and keeps you updated with notifications. It handles the entire application lifecycle from submission to status monitoring. Key features: Reads job listings from Google Sheets with filtering by priority and status Automatically applies to jobs on LinkedIn, Indeed, and other platforms Updates application status in real-time Checks application status every 2 days and notifies you of changes Sends email notifications for successful applications and status updates Prevents duplicate applications and manages rate limiting How it works The workflow runs on two main schedules: Daily Application Process (9 AM, weekdays): Reads your job list from Google Sheets Filters for jobs marked as "Not Applied" with Medium/High priority Processes each job individually to prevent rate limiting Applies to jobs using platform-specific APIs (LinkedIn, Indeed, etc.) Updates the sheet with application status and reference ID Sends confirmation email for each application Status Monitoring (Every 2 days at 10 AM): Checks all jobs with "Applied" status Queries job platforms for application status updates Updates the sheet if status has changed Sends notification emails for status changes (interviews, rejections, etc.) Requirements Google account with Google Sheets access Gmail account for notifications Resume stored online (Google Drive, Dropbox, etc.) API access to job platforms (LinkedIn, Indeed) - optional for basic version n8n instance (self-hosted or cloud) How to set up Step 1: Create Your Job Tracking Sheet Create a Google Sheet with these exact column headers: | Job_ID | Company | Position | Status | Applied_Date | Last_Checked | Application_ID | Notes | Job_URL | Priority | |--------|---------|----------|--------|--------------|--------------|----------------|-------|---------|----------| | JOB001 | Google | Software Engineer | Not Applied | | | | | https://careers.google.com/jobs/123 | High | | JOB002 | Microsoft | Product Manager | Not Applied | | | | | https://careers.microsoft.com/jobs/456 | Medium | Column explanations: Job_ID**: Unique identifier (JOB001, JOB002, etc.) Company**: Company name Position**: Job title Status**: Not Applied, Applied, Under Review, Interview Scheduled, Rejected, Offer Applied_Date**: Auto-filled when application is submitted Last_Checked**: Auto-updated during status checks Application_ID**: Platform reference ID (auto-generated) Notes**: Additional information or application notes Job_URL**: Direct link to job posting Priority**: High, Medium, Low (Low priority jobs are skipped) Step 2: Configure Google Sheets Access In n8n, go to Credentials → Add Credential Select Google Sheets OAuth2 API Follow the OAuth setup process to authorize n8n Test the connection with your job tracking sheet Step 3: Set Up Gmail Notifications Add another credential for Gmail OAuth2 API Authorize n8n to send emails from your Gmail account Test by sending a sample email Step 4: Update Workflow Configuration In the "Set Configuration" node, update these values: spreadsheetId**: Your Google Sheet ID (found in the URL) resumeUrl**: Direct link to your resume (make sure it's publicly accessible) yourEmail**: Your email address for notifications coverLetterTemplate**: Customize your cover letter template Step 5: Customize Application Logic For basic version (no API access): The workflow includes placeholder HTTP requests that you can replace with actual job platform integrations. For advanced version (with API access): Replace LinkedIn/Indeed HTTP nodes with actual API calls Add your API credentials to n8n's credential store Update the platform detection logic for additional job boards Step 6: Test and Activate Add 1-2 test jobs to your sheet with "Not Applied" status Run the workflow manually to test Check that the sheet gets updated and you receive notifications Activate the workflow to run automatically How to customize the workflow Adding New Job Platforms Update Platform Detection: Modify the "Check Platform Type" node to recognize new job board URLs Add New Application Node: Create HTTP request nodes for new platforms Update Status Checking: Add status check logic for the new platform Customizing Application Strategy Rate Limiting**: Add "Wait" nodes between applications (recommended: 5-10 minutes) Application Timing**: Modify the cron schedule to apply during optimal hours Priority Filtering**: Adjust the filter conditions to match your criteria Multiple Resumes**: Use conditional logic to select different resumes based on job type Enhanced Notifications Slack Integration**: Replace Gmail nodes with Slack for team notifications Discord Webhooks**: Send updates to Discord channels SMS Notifications**: Use Twilio for urgent status updates Dashboard Updates**: Connect to Notion, Airtable, or other productivity tools Advanced Features AI-Powered Personalization**: Use OpenAI to generate custom cover letters Job Scoring**: Implement scoring logic based on job requirements vs. your skills Interview Scheduling**: Auto-schedule interviews when status changes Follow-up Automation**: Send follow-up emails after specific time periods Important Notes Platform Compliance Always respect rate limits to avoid being blocked Follow each platform's Terms of Service Use official APIs when available instead of web scraping Don't spam job boards with excessive applications Data Privacy Store credentials securely using n8n's credential store Don't hardcode API keys or personal information in nodes Regularly review and clean up old application data Ensure your resume link is secure but accessible Quality Control Start with a small number of jobs to test the workflow Review application success rates and adjust strategy Monitor for errors and set up proper error handling Keep your job list updated and remove expired postings This workflow transforms job searching from a manual, time-consuming process into an automated system that maximizes your application efficiency while maintaining quality and compliance.

How it works Ever wonder how to make your workflows smarter? How to handle different types of data in different ways? This template is a hands-on tutorial that teaches you the three most fundamental nodes for controlling the flow of your automations: Merge, IF, and Switch. To make it easy to understand, we use a simple package sorting center analogy: Data Items** are packages on a conveyor belt. The Merge Node is where multiple conveyor belts combine into one. The IF Node is a simple sorting gate with two paths (e.g., "Fragile" or "Not Fragile"). The Switch Node is an advanced sorting machine that routes packages to many different destinations. This workflow takes you on a step-by-step journey through the sorting center: Creating Packages: Three different "packages" (two letters and one parcel) are created using Set nodes. Merging: The first Merge node combines all three packages onto a single conveyor belt so they can be processed together. Simple Sorting: An IF node checks if a package is fragile. If true, it's sent down one path; if false, it's sent down another. Re-Grouping: After being processed separately, another Merge node brings the packages back together. This "Split > Process > Merge" pattern is a critical concept in n8n! Advanced Sorting: A Switch node inspects each package's destination and routes it to the correct output (London, New York, Tokyo, or a Default bin). By the end, you'll see how all packages have been correctly sorted, and you'll have a solid understanding of how to build intelligent, branching logic in your own workflows. Set up steps Setup time: 0 minutes! This template is a self-contained tutorial and requires zero setup. There are no credentials or external services to configure. Simply click the "Execute Workflow" button. Follow the flow from left to right, clicking on each node to see its output and reading the detailed sticky notes to understand what's happening at each stage.

📊 Google Sheets MCP Workflow – AI Meets Spreadsheets! 😄 ✨ What It Does This n8n workflow lets you chat with your spreadsheets using AI + MCP! From reading and updating data to creating sheets, it’s your smart assistant for Google Sheets 📈🤖 🚀 Cool Features 💬 Natural language commands (e.g. "Add a new lead: John Doe") ✏️ Full CRUD (Create, Read, Update, Delete) 🧠 AI-powered analysis & smart workflows 🗂️ Multi-sheet support 🔗 Works with ChatGPT, Claude, and more (via MCP) 💡 Use Cases Data Tasks: “Update status to 'Done' in row 3” Sheet Ops: “Create a ‘Marketing 2024’ sheet” Business Flows: “Summarize top sales from Q2” 🛠️ Quick Setup Import Workflow into n8n Copy the JSON In n8n → Import JSON → Paste & Save ✅ Connect Google Sheets Create a project in Google Cloud Enable Sheets & Drive APIs Create OAuth2 credentials In n8n → Add Google Sheets OAuth2 credential → Connect 🔐 Add Your Credentials Get your credential ID Open each Google Sheets node → Update with your new credential ID Link to AI (Optional 😊) MCP webhook is pre-set Plug it into your AI tool (like ChatGPT) Send test command → Watch the magic happen ✨ ✅ Test It Out Try these fun commands: 🆕 "Add entry: Jane Doe, janed@example.com" 🔍 "Read data from Sales 2024" 🧹 "Clear data from A1:C5" ➕ "Create sheet 'Budget 2025'" ❌ "Delete sheet 'Test'" 🧠 MCP Command List (AI-Callable Functions) These are the tasks the AI can perform via MCP: Add a new entry to a sheet Read data from a sheet Update a row in a sheet Delete a row from a sheet Create a new sheet Delete an existing sheet Clear data from a specific range Summarize data from a sheet using AI ⚙️ Tips & Fixes OAuth2 Errors? Re-authenticate and check scopes Confirm redirect URI is exact Permissions? Spreadsheet must be shared with edit access Use service accounts for production Webhook Not Firing? Double-check the URL Trigger it manually to test

This workflow digests mentions of n8n on Reddit that can be sent as an single email or Slack summary each week. We use OpenAI to classify if a specific Reddit post is really about n8n or not, and then the summarise it into a bullet point sentence. How it works Get posts from Reddit that might be about n8n; Filter for the most relevant posts (posted in last 7 days and more than 5 upvotes and is original content); Check if the post is actually about n8n; If it is, categorise with OpenAI. Bear in mind: Workflow only considers first 500 characters of each reddit post. So if n8n is mentioned after this amount, it won't register as being a post about n8n.io. Next steps Improve OpenAI Summary node prompt to return cleaner summaries; Extend to more platforms/sources - e.g. it would be really cool to monitor larger Slack communities in this way; Do some classification on type of user to highlight users likely to be in our ICP; Separate a list of data sources (reddit, twitter, slack, discord etc.), extract messages from there and have them go to a sub workflow for classification and summarisation.

What problem does it solve? Manual candidate screening is time-consuming and inconsistent. This workflow automates initial interviews, providing 24/7 availability, consistent questioning, and objective assessments for every candidate. Who is it for? HR teams handling high-volume recruiting Small businesses without dedicated recruiters Companies scaling their hiring process Remote-first organizations needing asynchronous screening What this workflow does Creates AI interviewers from job descriptions that conduct natural conversations with candidates via BeyondPresence Agents. Automatically analyzes interviews and saves structured assessments to Google Sheets. Setup Copy template sheet: BeyondPresence HR Interview System Template Add credentials: BeyondPresence API Key OpenAI API Google Sheets Configure webhook in BeyondPresence dashboard: https://[your-n8n-instance]/webhook/beyondpresence-hr-interviews Paste job description and run setup Share generated link with candidates How it works Agent Creation: Converts job description into conversational AI interviewer Interview Conduct: Candidates chat naturally with AI via shared link Webhook Trigger: Completed interviews sent to n8n AI Analysis: OpenAI evaluates responses against job requirements Results Storage: Assessments saved to Google Sheets with scores and recommendations Resources Google Sheets Template BeyondPresence Documentation Webhook Setup Guide Example Use Case Tech startup screens 200 applicants for engineering role. Creates AI interviewer in 2 minutes, sends link to all candidates. Receives structured assessments within 24 hours, identifying top 20 candidates for human interviews. Reduces initial screening time from 2 weeks to 2 days.

Introduction The Content SEO Audit Workflow is a powerful automated solution that generates comprehensive SEO audit reports for websites. By combining the crawling capabilities of DataForSEO with the search performance metrics from Google Search Console, this workflow delivers actionable insights into content quality, technical SEO issues, and performance optimization opportunities. The workflow crawls up to 1,000 pages of a website, analyzes various SEO factors including metadata, content quality, internal linking, and search performance, and then generates a professional, branded HTML report that can be shared directly with clients. The entire process is automated, transforming what would typically be hours of manual analysis into a streamlined workflow that produces consistent, thorough results. This workflow bridges the gap between technical SEO auditing and practical, client-ready deliverables, making it an invaluable tool for SEO professionals and digital marketing agencies. Who is this for? This workflow is designed for SEO consultants, digital marketing agencies, and content strategists who need to perform comprehensive content audits for clients or their own websites. It's particularly valuable for professionals who: Regularly conduct SEO audits as part of their service offerings Need to provide branded, professional reports to clients Want to automate the time-consuming process of content analysis Require data-driven insights to inform content strategy decisions Users should have basic familiarity with SEO concepts and metrics, as well as a basic understanding of how to set up API credentials in n8n. While no coding knowledge is required to run the workflow, users should be comfortable with configuring workflow parameters and following setup instructions. What problem is this workflow solving? Content audits are essential for SEO strategy but are traditionally labor-intensive and time-consuming. This workflow addresses several key challenges: Manual Data Collection: Gathering data from multiple sources (crawlers, Google Search Console, etc.) typically requires hours of work. This workflow automates the entire data collection process. Inconsistent Analysis: Manual audits can suffer from inconsistency in methodology. This workflow applies the same comprehensive analysis criteria to every page, ensuring thorough and consistent results. Report Generation: Creating professional, client-ready reports often requires additional design work after the analysis is complete. This workflow generates a fully branded HTML report automatically. Data Integration: Correlating technical SEO issues with actual search performance metrics is difficult when working with separate tools. This workflow seamlessly integrates crawl data with Google Search Console metrics. Scale Limitations: Manual audits become increasingly difficult with larger websites. This workflow can efficiently process up to 1,000 pages without additional effort. What this workflow does Overview The Content SEO Audit Workflow crawls a specified website, analyzes its content for various SEO issues, retrieves performance data from Google Search Console, and generates a comprehensive HTML report. The workflow identifies issues in five key categories: status issues (404 errors, redirects), content quality (thin content, readability), metadata SEO (title/description issues), internal linking (orphan pages, excessive click depth), and performance (underperforming content). The final report includes executive summaries, detailed issue breakdowns, and actionable recommendations, all branded with your company's colors and logo. Process Initial Configuration: The workflow begins by setting parameters including the target domain, crawl limits, company information, and branding colors. Website Crawling: The workflow creates a crawl task in DataForSEO and periodically checks its status until completion. Data Collection: Once crawling is complete, the workflow: Retrieves the raw audit data from DataForSEO Extracts all URLs with status code 200 (successful pages) Queries Google Search Console API for each URL to get clicks and impressions data Identifies 404 and 301 pages and retrieves their source links Data Analysis: The workflow analyzes the collected data to identify issues including: Technical issues: 404 errors, redirects, canonicalization problems Content issues: thin content, outdated content, readability problems SEO metadata issues: missing/duplicate titles and descriptions, H1 problems Internal linking issues: orphan pages, excessive click depth, low internal links Performance issues: underperforming pages based on GSC data Report Generation: Finally, the workflow: Calculates a health score based on the severity and quantity of issues Generates prioritized recommendations Creates a comprehensive HTML report with interactive tables and visualizations Customizes the report with your company's branding Provides the report as a downloadable HTML file Setup To set up this workflow, follow these steps: Import the workflow: Download the JSON file and import it into your n8n instance. Configure DataForSEO credentials: Create a DataForSEO account at https://app.dataforseo.com/api-access (they offer a free $1 credit for testing) Add a new "Basic Auth" credential in n8n following the HTTP Request Authentication guide Assign this credential to the "Create Task", "Check Task Status", "Get Raw Audit Data", and "Get Source URLs Data" nodes Configure Google Search Console credentials: Add a new "Google OAuth2 API" credential following the Google OAuth guide Ensure your Google account has access to the Google Search Console property you want to analyze Assign this credential to the "Query GSC API" node Update the "Set Fields" node with: dfs_domain: The website domain you want to audit dfs_max_crawl_pages: Maximum number of pages to crawl (default: 1000) dfs_enable_javascript: Whether to enable JavaScript rendering (default: false) company_name: Your company name for the report branding company_website: Your company website URL company_logo_url: URL to your company logo brand_primary_color: Your primary brand color (hex code) brand_secondary_color: Your secondary brand color (hex code) gsc_property_type: Set to "domain" or "url" depending on your Google Search Console property type Run the workflow: Click "Start" and wait for it to complete (approximately 20 minutes for 500 pages). Download the report: Once complete, download the HTML file from the "Download Report" node. How to customize this workflow to your needs This workflow can be adapted in several ways to better suit your specific requirements: Adjust crawl parameters: Modify the "Set Fields" node to change: The maximum number of pages to crawl (dfs_max_crawl_pages). This workflow supports up to 1000 pages. Whether to enable JavaScript rendering for JavaScript-heavy sites (dfs_enable_javascript) Customize issue detection thresholds: In the "Build Report Structure" code node, you can modify: Word count thresholds for thin content detection (currently 1500 words) Click depth thresholds (currently flags pages deeper than 4 clicks) Title and description length parameters (currently 40-60 chars for titles, 70-155 for descriptions) Readability score thresholds (currently flags Flesch-Kincaid scores below 55) Modify the report design: In the "Generate HTML Report" code node, you can: Adjust the HTML/CSS to change the report layout and styling Add or remove sections from the report Change the recommendations logic Modify the health score calculation algorithm Add additional data sources: You could extend the workflow by: Adding Pagespeed Insights data for performance metrics Incorporating backlink data from other APIs Adding keyword ranking data from rank tracking APIs Implement automated delivery: Add nodes after the "Download Report" to: Send the report directly to clients via email Upload it to cloud storage Create a PDF version of the report

Keep your Hostinger VPS servers secure with automated backups! This n8n (self-hosted) workflow for is designed to create daily snapshots and send server metrics effortlessly, ensuring you always have an up-to-date recovery copy. Key Features: ✅ Automated Snapshots: Daily execution with zero manual intervention. ✅ Smart Replacement: Hostinger allows only 1 snapshot per VPS—the workflow automatically replaces the previous one. ✅ Notifications: Alerts via WhatsApp (Evolution API) or other configurable channels for execution confirmation. Quick Setup: Prerequisites: Install the Community Node n8n-nodes-hostinger-api and n8n-nodes-evolution-api in your n8n instance. Generate a Hostinger API Key in their dashboard: hpanel.hostinger.com/profile/api. Workflow Configuration: Add the Hostinger API credential in the first node and reuse it across the workflow. Customize the schedule (e.g., daily at 2 AM) and notification method (Evolution API for WhatsApp, email, etc.). Important Note: Hostinger overwrites the previous snapshot with each new execution, keeping only the latest version. VPS Metrics avaliables (send in messages): 🔹Status: snapshot status 🔹Date: snapshot date time 🔹Server: server name 🔹IP: external server IP ⚙️ Métrics: 🔹 Number of vCPUs 🔹 Ram usage / avaliable 🔹 Hard Disk usage / avaliable 🔹 Operational Sys and version 🔹 Uptime time (days, hours)

This template processes webhooks received from amoCRM in a URL-encoded format and transforms the data into a structured array that n8n can easily interpret. By default, n8n does not automatically parse URL-encoded webhook payloads into usable JSON. This template bridges that gap, enabling seamless data manipulation and integration with subsequent processing nodes. Key Features: Input Handling: Processes URL-encoded data received from amoCRM webhooks. Data Transformation: Converts complex, nested keys into a structured JSON array. Ease of Use: Simplifies access to specific fields for further workflow automation. Setup Guide: Webhook Trigger Node: Configure the Webhook Trigger node to receive data from amoCRM. URL-Encoding Parsing: Use the provided nodes to transform the input URL-encoded data into a structured array. Access Transformed Data: Use the resulting JSON structure for subsequent nodes in your workflow, such as filtering, updating records, or triggering external systems. Example Data Transformation: Sample Input (URL-Encoded): The following input format is typically received from amoCRM: $json.body'leads[updatecustom_fields[id]'] Output (Structured JSON): After processing, the data is transformed into an easily accessible JSON array format: {{ $json.leads.update[‘0’].id }} This output allows you to work with clean, structured JSON, simplifying field extraction and workflow continuation. Code Explanation: This workflow parses URL-encoded key-value pairs using n8n nodes to restructure the data into a nested JSON object. By doing so, the template improves transparency, ensures data integrity, and makes further automation tasks straightforward.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow scrapes job listings on indeed via Apify, automatically gets that dataset, extracts information about the listing filters jobs off relevance, finds a decision maker at the company and updates a database (google sheets) with that info for outreach. All you need to do is run Apify actor then the database will update with the processed data. Benefits: Complete Job search Automation - A webhook monitors the Apify actor which sends a integration and starts the process AI-Powered Filter - Uses ChatGPT to analyze content/context, identify company goals, and filters based on job description Smart Duplicate Prevention - Automatically tracks processed job listings in a database to avoid redundancy Multi-Platform Intelligence - Combines Indeed scraping, web research via Tavily, and enriches each listing Niche Focus - Process content from multiple niches 6 currently (hardcoded) but can be changed to fit other niches (just prompt the "job filter" node) How It Works: Indeed Job Discovery: Search and apply filter for relevant job listings, copy and use URL in Apify Uses Apify's Indeed job scraper to scrape job listings from the URL of interest Automatically scrapes the information, stores it in a dataset and initiates a integration Oncoming Data Processing: Loops over 500 items (can be changed) with a batch size of 55 items (can be changed) to avoid running into API timeouts. Multiple filters to ensure all fields are scrapped with our required metrics (website must exist and number of employees < 250) Duplicate job listings are removed from oncoming batch to be processed Job Analysis & Filter: An additional filter to remove any job listing from the oncoming batch if it already exists in the google sheets database Then all new job listings gets pasted to chatGPT which uses information about the job post/description to determine if it is relevant to us All relevant jobs get a new field "verdict" which is either true or false and we keep the ones where verdict is true Enrich & Update Database: Uses Tavily to search for a decision maker (doesn't always finds one) and populate a row in google sheet with information about the job listing, the company and a decision maker at that company. Waits for 1 minute and 30 seconds to avoid google sheets and chatGPT API timeouts then loops back to the next batch to start filtering again until all job listings are processed Required Google Sheets Database Setup: Before running this workflow, create a Google Sheets database with these exact column headers: Essential Columns: jobUrl - Unique identifier for job listings title - Position Title descriptionText - Description of job listing hiringDemand/isHighVolumeHiring - Are they hiring at high volume? hiringDemand/isUrgentHire - Are they hiring at high urgency? isRemote - Is this job remote? jobType/0 - Job type: In person, Remote, Part-time, etc. companyCeo/name - CEO name collected from Tavily's search icebreaker - Column for holding custom icebreakers for each job listing (Not completed in the workflow. I will upload another that does this called "Personalized IJSFE") scrapedCeo - CEO name collected from Apify Scraper email - Email listed on for job listing companyName - Name of company that posted the job companyDescription - Description of the company that posted the job companyLinks/corporateWebsite - Website of the company that posted the job companyNumEmployees - Number of employees the company listed that they have location/country - Location of where the job is to take place salary/salaryText - Salary on job listing Setup Instructions: Create a new Google Sheet with these column headers in the first row Name the sheet whatever you please Connect your Google Sheets OAuth credentials in n8n Update the document ID in the workflow nodes The merge logic relies on the id column to prevent duplicate processing, so this structure is essential for the workflow to function correctly. Feel free to reach out for additional help or clarification at my gmail: terflix45@gmail.com and I'll get back to you as soon as I can. Set Up Steps: Configure Apify Integration: Sign up for an Apify account and obtain API key Get indeed job scraper actor and use Apify's integration to send a HTTP request to your n8n webhook (if test URL doesn't work use production URL) Use Apify node with Resource: Dataset, Operation: Get items and use your Api key as your credentials Set Up AI Services: Add OpenAI API credentials for job filtering Add Tavily API credentials for company research Set up appropriate rate limiting for cost control Database Configuration: Create Google Sheets database with provided column structure Connect Google Sheets OAuth credentials Configure the merge logic for duplicate detection Content Filtering Setup: Customize the AI prompts for your specific niche, requirements or interest Adjust the filtering criteria to fit your needs

How it works This template is a hands-on tutorial for one of n8n's most powerful data tools: the Compare Datasets node. It's the perfect next step after learning basic logic, showing you how to build robust data synchronization workflows. We use a simple Warehouse Audit analogy to make the concept crystal clear: Warehouse A:* Our main, "source of truth" database. This is the master list of what our inventory *should be. Warehouse B:** A second, remote database (like a Notion page or Google Sheet) that we need to keep in sync. The Compare Datasets Node:* This is our *Auditor**. It takes both inventory lists and meticulously compares them to find any discrepancies. The Auditor then sorts every item into one of four categories, which correspond to the node's four outputs: In A only: New products found in our main warehouse that need to be added to Warehouse B. Same: Products that match perfectly in both warehouses. No action needed! Different: Products that exist in both places but have different details (e.g., stock count). These need to be updated in Warehouse B. In B only: Extra products found in Warehouse B that aren't in our master list. These need to be deleted. This pattern is the foundation for any two-way data sync you'll ever need to build. Set up steps Setup time: 0 minutes! This workflow is a self-contained tutorial and requires no setup or credentials. Click "Execute Workflow" to start the audit. Explore the two Set nodes ("Warehouse A" and "Warehouse B") to see the initial data we are comparing. Click on "The Auditor" (Compare Datasets node) to see how it's configured to use product_id as the matching key. Follow the outputs to the four NoOp nodes to see which products were sorted into each category. Read the sticky notes next to each output—they explain exactly why each item ended up there.