Workflow Templates

Overview The n8n Workflow Cloner is a powerful automation tool designed to copy, sync, and migrate workflows across different n8n instances or projects. Whether you're managing multiple environments (development, staging, production) or organizing workflows within a team, this workflow automates the transfer process, ensuring seamless workflow deployment with minimal manual effort. By automatically detecting and copying only the missing workflows, this tool helps maintain consistency, improve collaboration, and streamline workflow migration between projects or instances. How to Use 1️⃣ Set Up API Credentials Configure API credentials for both source and destination n8n instances. Ensure the credentials have read and write access to manage workflows. 2️⃣ Select Source & Destination Update the "GET - Workflows" node to define the source instance. Set the "CREATE - Workflow" node to specify the destination instance. 3️⃣ Run the Workflow Click "Test Workflow" to start the transfer. The system will fetch all workflows from the source, compare them with the destination, and copy any missing workflows. 4️⃣ Change the Destination Project (Optional) By default, workflows are moved to the "KBB Workflows" project. Modify the "Filter" node to transfer workflows to a different project. 5️⃣ Monitor & Verify The Loop Over Items node ensures batch processing for multiple workflows. Log outputs provide details on transferred workflows and statuses. Key Benefits ✅ Automate Workflow Transfers – No more manual exports/imports. ✅ Sync Workflows Across Environments – Keep workflows up to date in dev, staging, and production. ✅ Effortless Team Collaboration – Share workflows across projects seamlessly. ✅ Backup & Migration Ready – Easily move workflows between n8n instances. Use Cases 🔹 CI/CD for Workflows – Deploy workflows between development and production environments. 🔹 Team Workflow Sharing – Share workflows across multiple n8n projects. 🔹 Workflow Backup Solution – Store copies of workflows in a dedicated backup project. Tags 🚀 Workflow Migration 🚀 n8n Automation 🚀 Sync Workflows 🚀 Backup & Deployment

Automate Feature Request Collection & Analysis from Reviews to Jira with AI

by Yaron Been

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically gathers and analyzes feature requests from multiple sources including support tickets, user forums, and feedback platforms to help prioritize product development. It saves you time by eliminating the need to manually monitor various channels and provides intelligent feature request analysis. Overview This workflow automatically scrapes support systems, user forums, social media, and feedback platforms to collect feature requests from customers. It uses Bright Data to access various platforms without being blocked and AI to intelligently categorize, prioritize, and analyze feature requests based on frequency and user impact. Tools Used n8n**: The automation platform that orchestrates the workflow Bright Data**: For scraping support platforms and user forums without being blocked OpenAI**: AI agent for intelligent feature request categorization and analysis Google Sheets**: For storing feature requests and generating prioritization reports How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Bright Data: Add your Bright Data credentials to the MCP Client node Set Up OpenAI: Configure your OpenAI API credentials Configure Google Sheets: Connect your Google Sheets account and set up your feature request tracking spreadsheet Customize: Define feedback sources and feature request identification parameters Use Cases Product Management**: Prioritize roadmap items based on customer demand Development Teams**: Understand which features users need most Customer Success**: Track and respond to feature requests proactively Strategy Teams**: Make data-driven decisions about product direction Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Bright Data**: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #featurerequests #productmanagement #brightdata #webscraping #productdevelopment #n8nworkflow #workflow #nocode #roadmapping #customervoice #productinsights #featureanalysis #productfeedback #userresearch #productdata #featuretracking #productplanning #customerneeds #featurediscovery #productprioritization #featurebacklog #uservoice #productintelligence #developmentplanning #featuremonitoring #productdecisions #feedbackgathering #productautomation

intermediate

6 nodes1 views

Test Webhooks in n8n Without Changing WEBHOOK_URL (PostBin & BambooHR Example)

by Ludwig

Using PostBin to Test Webhooks Without Changing WEBHOOK_URL How it Works Many new n8n users struggle with testing webhooks when running n8n on localhost, as external services cannot reach localhost. This workflow introduces a technique using PostBin, which provides a temporary, publicly accessible URL to receive webhook requests. Generates a temporary webhook endpoint via PostBin. Uses this endpoint in place of localhost to test webhooks. Captures and displays the incoming webhook request data. Enables debugging and iterating without modifying the WEBHOOK_URL environment variable. Set Up Steps Estimated time:** ~5–10 minutes Create a PostBin instance to generate a publicly accessible webhook URL. Copy the PostBin URL and use it as the webhook destination in n8n. Trigger the webhook from an external service or manually. Inspect the request payload in PostBin to verify data reception. (EXAMPLE) Using PostBin for Webhook Testing in a BambooHR Integration How it Works In this example, we apply the PostBin technique to a BambooHR integration. Instead of manually configuring a webhook in BambooHR, this workflow automates webhook registration using the BambooHR API. The workflow: Uses the BambooHR API to programmatically register the PostBin URL as a webhook. Retrieves the most recent webhook calls made by BambooHR to the PostBin URL. (Optional) Sends a personalized Slack message for new employees using OpenAI. Set Up Steps Estimated time:** ~15–20 minutes Set up PostBin using the steps from the first section. Log into BambooHR to generate an API key for authentication. Run the workflow to register the PostBin URL as a webhook in BambooHR via the API. Retrieve recent webhook calls from PostBin to validate data reception. (Optional) Send a Slack notification using the processed data.

Vector Database as a Big Data Analysis Tool for AI Agents [2/2 KNN]

by Jenny

Vector Database as a Big Data Analysis Tool for AI Agents Workflows from the webinar "Build production-ready AI Agents with Qdrant and n8n". This series of workflows shows how to build big data analysis tools for production-ready AI agents with the help of vector databases. These pipelines are adaptable to any dataset of images, hence, many production use cases. Uploading (image) datasets to Qdrant Set up meta-variables for anomaly detection in Qdrant Anomaly detection tool KNN classifier tool For anomaly detection The first pipeline to upload an image dataset to Qdrant. The second pipeline is to set up cluster (class) centres & cluster (class) threshold scores needed for anomaly detection. The third is the anomaly detection tool, which takes any image as input and uses all preparatory work done with Qdrant to detect if it's an anomaly to the uploaded dataset. For KNN (k nearest neighbours) classification The first pipeline to upload an image dataset to Qdrant. This pipeline is the KNN classifier tool, which takes any image as input and classifies it on the uploaded to Qdrant dataset. To recreate both You'll have to upload crops and lands datasets from Kaggle to your own Google Storage bucket, and re-create APIs/connections to Qdrant Cloud (you can use Free Tier cluster), Voyage AI API & Google Cloud Storage. [This workflow] KNN classification tool This tool takes any image URL, and as output, it returns a class of the object on the image based on the image uploaded to the Qdrant dataset (lands). An image URL is received via the Execute Workflow Trigger, which is then sent to the Voyage AI Multimodal Embeddings API to fetch its embedding. The image's embedding vector is then used to query Qdrant, returning a set of X similar images with pre-labeled classes. Majority voting is done for classes of neighbouring images. A loop is used to resolve scenarios where there is a tie in Majority Voting, and we increase the number of neighbours to retrieve. When the loop finally resolves, the identified class is returned to the calling workflow.

Youtube Outlier Detector (Find trending content based on your competitors)

by Leonardo Grigorio

Video explanation This n8n workflow helps you identify trending videos within your niche by detecting outlier videos that significantly outperform a channel's average views. It automates the process of monitoring competitor channels, saving time and streamlining content research. Included in the Workflow Automated Competitor Video Tracking Monitors videos from specified competitor channels, fetching data directly from the YouTube API. Outlier Detection Based on Channel Averages Compares each video’s performance against the channel’s historical average to identify significant spikes in viewership. Historical Video Data Management Stores video statistics in a PostgreSQL database, allowing the workflow to only fetch new videos and optimize API usage. Short Video Filtering Automatically removes short videos based on duration thresholds. Flexible Video Retrieval Fetches up to 3 months of historical data on the first run and only new videos on subsequent runs. PostgreSQL Database Integration Includes SQL queries for database setup, video insertion, and performance analysis. Configurable Outlier Threshold Focuses on videos published within the last two weeks with view counts at least twice the channel's average. Data Output for Analysis Outputs best-performing videos along with their engagement metrics, making it easier to identify trending topics. Requirements n8n installed on your machine or server A valid YouTube Data API key Access to a PostgreSQL database This workflow is intended for educational and research purposes, helping content creators gain insights into what topics resonate with audiences without manual daily monitoring.

Automate Travel Business Operations with Postgres, Google Sheets and Voice API

by Oneclick AI Squad

This comprehensive n8n workflow automates the entire travel business call management process, from initial customer inquiries to trip bookings and marketing outreach. The system handles incoming calls, validates trip details, processes bookings, captures leads, and manages outbound marketing campaigns to promote trip organizer services. It streamlines the complete sales cycle while maintaining organized data records for business intelligence. Essential Information The system operates across four distinct workflows to handle different aspects of travel call management. All call data is automatically captured and stored in organized spreadsheets for analysis and follow-up. The workflow validates trip details before processing to ensure data accuracy and prevent booking errors. Outbound marketing campaigns are automatically triggered based on lead detection and formatting. System Architecture Call Handling Pipeline**: The Detect Incoming Call node captures all incoming customer calls, followed by the Validate Trip Details node which verifies and processes trip information, and the Deliver Organizer Info node that provides relevant trip organizer details to callers. Booking Management Flow**: The Capture Voice Input node records customer booking requests, the Update Booking Record node processes and stores booking information, and the Send Booking Confirmation node delivers confirmation details to customers. Lead Generation Process**: The Detect New Lead node identifies potential customers from call data, the Format Lead Information node structures the lead data for marketing use, and the Initiate Marketing Outreach node launches targeted marketing campaigns. Data Management System**: The Receive Call Response node collects call interaction data, the Log User Input node records customer information in spreadsheets, and the Relay Response to System node ensures data synchronization across all components. Implementation Guide Import the workflow into n8n and configure phone system integration for call detection and voice capture. Set up spreadsheet connections for booking records, lead management, and call logging. Configure marketing automation tools for outbound campaign management. Test each workflow section independently before enabling the complete system. Monitor call handling accuracy and adjust validation rules as needed. Technical Dependencies Phone system API or telephony service for call detection and voice processing Spreadsheet service (Google Sheets, Excel Online) for data storage and management Marketing automation platform for outbound campaign execution Voice recognition service for capturing and processing customer input CRM integration for lead management and customer tracking Database & Sheet Structure Call Tracking Sheet**: Columns should include Call_ID, Customer_Phone, Call_Time, Call_Duration, Call_Status, Trip_Interest, Organizer_Assigned Booking Records Sheet**: Required columns are Booking_ID, Customer_Name, Customer_Phone, Destination, Travel_Dates, Group_Size, Booking_Status, Confirmation_Sent Lead Management Sheet**: Essential columns include Lead_ID, Customer_Name, Phone_Number, Email, Trip_Preference, Lead_Source, Lead_Status, Marketing_Campaign_Sent Trip Organizer Database**: Contains Organizer_ID, Organizer_Name, Specialization, Contact_Info, Availability_Status, Performance_Rating Marketing Outreach Log**: Tracks Campaign_ID, Lead_ID, Campaign_Type, Send_Date, Response_Status, Follow_up_Required Customization Possibilities Adjust the Validate Trip Details node to include specific travel validation rules or partner requirements. Modify the Format Lead Information node to match your CRM system's data structure and marketing campaign formats. Configure the Initiate Marketing Outreach node to integrate with your preferred marketing platforms and campaign templates. Customize the data logging structure in the Log User Input node to capture additional customer information or booking details. Add additional validation steps or approval workflows between booking capture and confirmation sending.

⚙️Business Automation

beginner

3 nodes2 views

💡🌐 Essential Multipage Website Scraper with Jina.ai

by Joseph LePage

💡🌐 Essential Multipage Website Scraper with Jina.ai Use responsibly and follow local rules and regulations This N8N workflow enables automated multi-page website scraping using Jina.ai's powerful web scraping capabilities, with seamless integration to Google Drive for content storage. Here's how it works: Main Features The workflow automatically scrapes multiple pages from a website's sitemap and saves each page's content as a separate Google Drive document. Key Components Input Configuration Starts with a sitemap URL (default: https://ai.pydantic.dev/sitemap.xml)** Processes the sitemap to extract individual page URLs Includes filtering options to target specific topics or pages Scraping Process Uses Jina.ai's web scraper to extract content from each URL Converts webpage content into clean markdown format Extracts page titles automatically for document naming Storage Integration Creates individual Google Drive documents for each scraped page Names documents using the format "URL - Page Title" Saves content in markdown format for better readability Usage Instructions Set your target website's sitemap URL in the "Set Website URL" node Configure the "Filter By Topics or Pages" node to select specific content Adjust the "Limit" node (default: 20 pages) to control batch size Connect your Google Drive account Run the workflow to begin automated scraping Additional Features Built-in rate limiting through the Wait node to prevent overloading servers Batch processing capability for handling large sitemaps The workflow requires no API key for Jina.ai, making it accessible for immediate use while maintaining responsible scraping practices.

Monitor Competitor Financial Performance with Bright Data MCP, OpenAI & Google Sheets

by Yaron Been

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically monitors publicly available competitor financial data—funding rounds, earnings, and SEC filings—and alerts your team to significant changes. Gain an edge by reacting to financial moves faster. Overview Using Bright Data, the automation scrapes Crunchbase, press releases, and SEC Edgar filings. OpenAI extracts key figures (revenue, funding amount, valuation) and assesses the potential impact. Highlights are posted to Slack and stored in Airtable for long-term tracking. Tools Used n8n** – Drives the automation Bright Data** – Scrapes financial disclosure sites OpenAI** – Extracts numbers and generates insights Slack** – Sends real-time alerts Airtable** – Maintains a financial timeline database How to Install Import the Workflow into n8n. Configure Bright Data credentials. Set Up OpenAI API key. Authorize Slack & Airtable. Customize Competitor List & Thresholds in the Set node. Use Cases Competitive Intelligence**: Track rivals’ financial health. Investor Relations**: Benchmark against peers. Strategic Planning**: Identify acquisition targets. Sales Enablement**: Time outreach after funding events. Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Bright Data**: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #financialmonitoring #competitoranalysis #brightdata #openai #secfilings #fundingrounds #n8nworkflow #nocode

intermediate

7 nodes

CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync

by Angel Menendez

CallForge - AI Sales Call Processing & Insights Extraction Automate sales call analysis with AI-powered insights for sales, marketing, and product teams. Who is This For? This workflow is designed for: ✅ Sales teams looking to extract structured insights from Gong call transcripts. ✅ Marketing professionals seeking AI-driven customer pain points & content strategy. ✅ Product teams needing feedback from sales calls to prioritize feature development. 🔍 What Problem Does This Workflow Solve? Manually analyzing Gong.io sales call transcripts is slow, inconsistent, and lacks structured insights. With CallForge, you can: ✔ Extract AI-powered insights about use cases, objections, competitors, and next steps. ✔ Provide structured marketing & product intelligence to enhance strategy. ✔ Automatically store call insights in Notion and Salesforce for easy access. ✔ Ensure resilience with automated reruns on failed workflows (handling Notion API limits). ✔ Improve decision-making with AI-powered competitor and sentiment analysis. 📌 Key Workflow Features 🎤 AI-Powered Transcript Analysis Uses AI to identify use cases, objections, competitors, and customer pain points. Categorizes insights for sales, marketing, and product teams. 📌 AI Agent Breakdown 🔹 Sales AI Agent – Extracts customer objections, pain points, competitors, and next steps. 🔹 Marketing AI Agent – Identifies recurring topics, keyword trends, and content opportunities. 🔹 Product AI Agent – Captures feature requests and AI/ML-related references. 📊 Structured Output Processing Sales Data Processor* → Stores insights in *Notion & Salesforce** for sales tracking. Marketing Data Processor* → Extracts *SEO & content strategy insights** for marketing teams. Product AI Data Processor* → Logs *customer feedback* to prioritize *feature development**. 💡 Competitor & Integration Analysis Tracks competing products mentioned in calls**. Identifies integration needs**, flagging workarounds used by prospects. 📢 Real-Time Slack Notifications Alerts teams on workflow progress** and completed call analyses. 🔄 Failure Resilience & Automated Re-Runs If a Notion API limit is reached, the process resumes automatically. 🚀 How This Works 🛠 1. Trigger & Call Data Processing The workflow retrieves Gong call transcripts and metadata. Normalizes data**, correcting common mispronunciations like "n8n." 🤖 2. AI Agents Analyze the Call Sales Agent** – Extracts actionable insights for sales follow-ups. Marketing Agent* – Identifies *recurring themes* and *keyword trends**. Product Agent* – Captures *feature requests and AI/ML usage mentions**. 📡 3. Data is Stored in Notion & Salesforce Logs AI-extracted insights* in *Notion** for structured tracking. Pushes sales-related data* to *Salesforce** for team accessibility. 🔔 4. Slack Alerts for Teams Notifies sales, marketing, and product teams** about extracted insights. CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization CallForge - 03 - Gong Transcript Processor and Salesforce Enricher CallForge - 04 - AI Workflow for Gong.io Sales Calls CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync CallForge - 06 - Automate Sales Insights with Gong.io, Notion & AI CallForge - 07 - AI Marketing Data Processing with Gong & Notion CallForge - 08 - AI Product Insights from Sales Calls with Notion 📊 Sample Output Data 1️⃣ Sales Insights { "UseCases": [ { "Summary": "A manufacturing company wants to automate inventory tracking and reduce manual entry delays.", "DepartmentTags": ["Operations"], "IndustryTags": ["Manufacturing"], "ImplementationStatus": "Evaluating" } ], "Objection": { "ObjectionTags": ["Feature Limitation"], "Nature": "The prospect wanted a deeper integration with their ERP system, which n8n currently lacks." }, "CallSummary": "The call focused on automation for supply chain processes. The prospect expressed interest but wanted confirmation on ERP integration capabilities.", "NextSteps": ["Schedule a follow-up demo for ERP integration."] } 2️⃣ Marketing Insights { "MarketingInsights": [ { "Tag": "Workflow Template Request", "Summary": "The prospect requested a template for automating CRM lead tracking." } ], "RecurringTopics": [ { "Topic": "CRM Integration", "Mentions": 3, "Context": "Discussed how n8n could sync CRM data automatically." } ], "ActionableInsights": [ { "RecommendationType": "Tutorial", "Title": "How to Automate CRM Lead Tracking with n8n", "Topic": "CRM Integration", "Rationale": "The prospect expressed a need for CRM automation templates." } ] } 3️⃣ Product Feedback { "ProductFeedback": [ { "Sentiment": "Positive", "Feedback": "The external speaker praised the simplicity of n8n's UI, making it easier for non-developers to automate tasks." }, { "Sentiment": "Negative", "Feedback": "The external speaker mentioned frustration over the lack of a dedicated ERP integration node." } ], "AI_ML_References": { "Exist": true, "Context": "The external speaker mentioned using AI for automating customer ticket categorization.", "Details": { "DevelopmentStatus": "Building", "Department": "Support", "RequiresAgents": true, "RequiresRAG": false, "RequiresChat": "Yes: External App (e.g., Slack)" } } } 🔧 How to Customize This Workflow 💡 🔗 Change Data Storage – Swap Notion for Airtable, HubSpot, or another CRM. 💡 📩 Customize Slack Notifications – Send alerts via email, webhook, or another channel. 💡 🛠 Modify AI Processing – Adjust AI models or processing prompts. 💡 📊 Add More Integrations – Sync insights with Pipedrive, HubSpot, or another CRM. 🚀 Why Use This Workflow? ✔ Automates Gong call transcript analysis, eliminating manual work. ✔ Improves collaboration by structuring insights for sales, marketing, and product teams. ✔ Boosts sales conversions by identifying objections and next steps. ✔ Enhances marketing and SEO strategy with AI-driven insights. ✔ Optimizes product roadmap decisions based on customer feedback. This workflow scales AI-powered sales intelligence for better decision-making, content strategy, and sales enablement. 🚀

beginner

3 nodes3416 views

Summarize YouTube Transcripts in Any Language with Google Gemini & Google Docs

by Sk developer

YouTube Transcript Summarization in Any Language for Social Media This n8n workflow automates the process of: Retrieving YouTube Video Transcripts: It fetches the transcript for any YouTube video URL provided using the YouTube Transcript API from RapidAPI. Generating a Concise Summary in Any Language: The workflow uses Google Gemini (PaLM) to create a concise summary of the transcript in the language specified by the user (e.g., English, Spanish, etc.). Storing the Summary in Google Docs: The generated summary is inserted into a predefined Google Document, making it easy for users to share or edit. Features: Language Flexibility:** Summaries are created in the desired language. Fully Automated:** From fetching the transcript to updating Google Docs, the process is fully automated. Social Media Ready:** The summary is formatted and stored in a Google Doc, ready for use in social media posts. This workflow integrates with YouTube Transcript API via RapidAPI, allowing you to easily fetch video transcripts and summarize them with AI. The entire process is automated and seamless. Powered by RapidAPI: API Used:* YouTube Transcript API via *RapidAPI** to get the transcript data. Benefits: Saves Time:** Automates the transcript summarization process, eliminating the need for manual content extraction and summarization. Customizable Language Support:** Provides summaries in any language, enabling accessibility and engagement for a global audience. Streamlined Content Creation:** Automatically generates concise, engaging summaries that are ready for social media use. Google Docs Integration:** Saves summaries directly into a Google Doc for easy sharing, editing, and content management. Challenges Addressed: Manual Transcript Extraction:** Problem: Manually transcribing and summarizing YouTube videos for social media can be time-consuming and error-prone. Solution: This workflow fully automates the process, saving hours of manual work using the YouTube Transcript API. Lack of Language Support in Summaries:** Problem: Many automated tools only summarize content in a single language, limiting their accessibility. Solution: With language flexibility, the workflow creates summaries in the language of your choice, helping you cater to diverse audiences. Inconsistent Video Quality & Transcript Accuracy:** Problem: Not all YouTube videos have well-structured or accurate transcripts, leading to incomplete or inaccurate summaries. Solution: The workflow can process and format even imperfect transcripts, ensuring that the generated summaries are still accurate and useful. Managing Content Across Platforms:** Problem: Transcripts and summaries often need to be stored in multiple locations for social media posts, which can be cumbersome. Solution: The workflow integrates with Google Docs to automatically store and manage summaries in one place, making it easier to share and reuse content.

intermediate

5 nodes5 views

Build Custom Workflows Automatically with GPT-4o, RAG, and Web Search

by Franz