Workflow Templates

UTM Link Creator & QR Code Generator with Scheduled Google Analytics Reports This workflow enables marketers to generate UTM-tagged links, convert them into QR codes, and automate performance tracking in Google Analytics with scheduled reports every 7 days. This solution helps monitor traffic sources from different marketing channels and optimize campaign performance based on analytics data. Prerequisites Before implementing this workflow, ensure you have the following: Google Analytics 4 (GA4) Account & Access Ensure you have a GA4 property set up. Access to the GA4 Data API to schedule performance tracking. Refer to the Google Analytics Data API Overview for more information. Airtable Account & API Key Create an Airtable base to store UTM links, QR codes, and analytics data. Obtain an Airtable API key from your Account Settings. Detailed instructions are available in the Airtable API Authentication Guide. Step-by-Step Guide to Setting Up the Workflow 1. Generate UTM Links Create a form or interface to input: Base URL** (e.g., https://example.com) Campaign Name** (utm_campaign) Source** (utm_source) Medium** (utm_medium) Term** (Optional: utm_term) Content** (Optional: utm_content) Append UTM parameters to generate a trackable URL. 2. Store UTM Links & QR Codes in Airtable Set up an Airtable base with the following columns: UTM Link** QR Code** Campaign Name** Source** Medium** Date Created** Adjust as needed based on your tracking requirements. For guidance on setting up your Airtable base and using the API, refer to the Airtable Web API Documentation. 3. Convert UTM Links to QR Codes Use a QR code generator API (e.g., goqr.me, qrserver.com) to generate QR codes for each UTM link and store them in Airtable. 4. Schedule Google Analytics Performance Reports (Every 7 Days) Use the Google Analytics Data API to pull weekly performance reports based on UTM parameters. Extract key metrics such as: Sessions Users Bounce Rate Conversions Revenue (if applicable) Store the data in Airtable for tracking and analysis. Adjust timeframe as needed For more details on accessing and using the Google Analytics Data API, consult the Google Analytics Data API Overview. Benefits of This Workflow ✅ Track Marketing Campaigns: Easily monitor which channels drive traffic. ✅ Automate QR Code Creation: Seamless integration of UTM links with QR codes. ✅ Scheduled Google Analytics Reports: No manual reporting—everything runs automatically. ✅ Improve Data-Driven Decisions: Optimize ad spend and marketing strategies based on performance insights. This version ensures proper Markdown structure, includes relevant documentation links, and improves readability. Let me know if you need any further refinements! 🚀

Telegram AI Assistant: Summarize Links & Generate Images On Demand This workflow turns any Telegram chat into a smart assistant. By typing simple commands like /summary or /img, users can trigger powerful AI actions—directly from Telegram. ✨ What It Does This automation listens for specific commands in Telegram messages: /help: Sends a help menu explaining available commands. /summary <link>: Fetches a webpage, extracts its content, and summarizes it using OpenAI into 10–12 bullet points. /img <prompt>: Sends the image prompt to OpenAI and replies that the request has been received (designed for future integration with image APIs). 📦 Features ✅ Works instantly in Telegram 🧠 Uses OpenAI for text summarization and image prompt processing 🌐 Scrapes and cleans raw article text before summarizing 📤 Replies directly to the same Telegram thread 🔧 Easily expandable to support more commands 🔧 Use Cases Research Summaries**: Quickly condense articles or reports shared in chat. Content Review**: Get team-friendly TL;DRs of long blog posts or product pages. Creative Brainstorming**: Share visual ideas via /img and get quick prompts logged. Customer Support**: Offer instant answers in group chats (with further extension). Daily Digest Bot**: Connect to news feeds and auto-summarize updates. 🚀 Getting Started Clone this workflow and connect your Telegram Bot. Insert your OpenAI credentials. Deploy and test by messaging /summary https://example.com in your Telegram group or DM. Expand with new commands or connect Stability.ai or other services for real image generation. 🔗 Author & Resources Built by Yaron Been Follow more automations at nofluff.online

Tags: Supply Chain, Logistics, AI Agents Context Hey! I’m Samir, a Supply Chain Data Scientist from Paris, and the founder of LogiGreen Consulting. We design tools to help companies improve their logistics processes using data analytics, AI, and automation—to reduce costs and minimize environmental impacts. >Let’s use N8N to improve logistics operations! 📬 For business inquiries, you can add me on LinkedIn Who is this template for? This workflow template is designed for logistics or manufacturing operations that receive orders by email. The example above illustrate the challenge we want to tackle using an AI Agent to parse the information and load them in a Google sheet. If you want to understand how I built this workflow, check my detailed tutorial: 🎥 Step-by-Step Tutorial How does it work? The workflow is connected to a Gmail Trigger to open all the emails that include Inbound Order in their subject. The email is parsed by an AI Agent equipped with OpenAI's GPT to collect all the information. The results are pulled in a Google Sheet. These orderlines can then be transferred to warehouse teams to prepare *order receiving. What do I need to get started? You’ll need: Gmail and Google Drive Accounts** with the API credentials to access it via n8n An OpenAI API key (GPT-4o) for the chat model. A Google Sheet with these columns: PO_NUMBER, EXPECTED_DELIVERY DATE, SKU_ID, QUANTITY Next Steps Follow the sticky notes in the workflow to configure each node and start using AI to support your logistic operations. 🚀 Curious how N8N can transform your logistics operations? 📬 Let’s connect on LinkedIn Notes An example of email is included in the template so you can try it with your mailbox. This workflow was built using N8N version 1.82.1 Submitted: March 28, 2025

Replace manual task prioritization with intelligent AI reasoning that thinks like a Chief Operating Officer. This workflow automatically fetches your Asana tasks every morning, analyzes them using advanced AI models, and delivers the single most critical task with detailed reasoning - ensuring your team always focuses on what matters most. ✨ What This Workflow Does: 📋 Automated Task Collection**: Fetches all assigned Asana tasks daily at 9 AM 🤖 AI-Powered Analysis**: Uses OpenAI GPT-4 to evaluate urgency, impact, and strategic importance 🎯 Smart Prioritization**: Identifies the #1 most critical task with detailed reasoning 🧠 Contextual Memory**: Leverages vector database for historical context and pattern recognition 💾 Structured Storage**: Saves prioritized tasks to PostgreSQL with full audit trail 🔄 Continuous Learning**: Builds organizational knowledge over time for better decisions 🔧 Key Features: Daily automation** with zero manual intervention Context-aware AI** that learns from past prioritization decisions Strategic reasoning** explaining why each task is prioritized Vector-powered memory** using Pinecone for intelligent context retrieval Clean structured output** with task names, priority levels, and detailed justifications Database integration** for reporting and historical analysis 📋 Prerequisites: Asana account with API access OpenAI API key (GPT-4 recommended) PostgreSQL database Pinecone account (for vector storage and context) 🎯 Perfect For: Operations teams managing multiple competing priorities Startups needing systematic task management Project managers juggling complex workflows Leadership teams requiring strategic focus Any organization wanting AI-driven operational intelligence 💡 How It Works: Morning Automation: Triggers every day at 9 AM Data Collection: Pulls all relevant tasks from Asana AI Analysis: Evaluates each task using COO-level strategic thinking Context Retrieval: Searches vector database for similar past tasks Smart Prioritization: Identifies the single most important task Structured Output: Delivers priority level with detailed reasoning Data Storage: Saves results for reporting and continuous improvement 📦 What You Get: Complete n8n workflow with all AI components configured PostgreSQL database schema for task storage Vector database setup for contextual intelligence Comprehensive documentation and setup guide Sample task data and output examples 💡 Need Help or Want to Learn More? Created by Yaron Been - Automation & AI Specialist 📧 Support: Yaron@nofluff.online 🎥 YouTube Tutorials: https://www.youtube.com/@YaronBeen/videos 💼 LinkedIn: https://www.linkedin.com/in/yaronbeen/ Discover more advanced automation workflows and AI integration tutorials on my channels! 🏷️ Tags: AI, OpenAI, Asana, Task Management, COO, Prioritization, Automation, Vector Database, Operations, GPT-4

This workflow demonstrates how to enrich data from a list of companies in a spreadsheet. While this workflow is production-ready if all steps are followed, adding error handling would enhance its robustness. Important notes Check legal regulations**: This workflow involves scraping, so make sure to check the legal regulations around scraping in your country before getting started. Better safe than sorry! Mind those tokens**: OpenAI tokens can add up fast, so keep an eye on usage unless you want a surprising bill that could knock your socks off! 💸 Main Workflow Node 1 - Webhook This node triggers the workflow via a webhook call. You can replace it with any other trigger of your choice, such as form submission, a new row added in Google Sheets, or a manual trigger. Node 2 - Get Rows from Google Sheet This node retrieves the list of companies from your spreadsheet. here is the Google Sheet Template you can use. The columns in this Google Sheet are: Company**: The name of the company Website**: The website URL of the company These two fields are required at this step. Business Area**: The business area deduced by OpenAI from the scraped data Offer**: The offer deduced by OpenAI from the scraped data Value Proposition**: The value proposition deduced by OpenAI from the scraped data Business Model**: The business model deduced by OpenAI from the scraped data ICP**: The Ideal Customer Profile deduced by OpenAI from the scraped data Additional Information**: Information related to the scraped data, including: Information Sufficiency: Description: Indicates if the information was sufficient to provide a full analysis. Options: "Sufficient" or "Insufficient" Insufficient Details: Description: If labeled "Insufficient," specifies what information was missing or needed to complete the analysis. Mismatched Content: Description: Indicates whether the page content aligns with that of a typical company page. Suggested Actions: Description: Provides recommendations if the page content is insufficient or mismatched, such as verifying the URL or searching for alternative sources. Node 3 - Loop Over Items This node ensures that, in subsequent steps, the website in "extra workflow input" corresponds to the row being processed. You can delete this node, but you'll need to ensure that the "query" sent to the scraping workflow corresponds to the website of the specific company being scraped (rather than just the first row). Node 4 - AI Agent This AI agent is configured with a prompt to extract data from the content it receives. The node has three sub-nodes: OpenAI Chat Model: The model used is currently gpt4-o-mini. Call n8n Workflow: This sub-node calls the workflow to use ScrapingBee and retrieves the scraped data. Structured Output Parser: This parser structures the output for clarity and ease of use, and then adds rows to the Google Sheet. Node 5 - Update Company Row in Google Sheet This node updates the specific company's row in Google Sheets with the enriched data. Scraper Agent Workflow Node 1 - Tool Called from Agent This is the trigger for when the AI Agent calls the Scraper. A query is sent with: Company name Website (the URL of the website) Node 2 - Set Company URL This node renames a field, which may seem trivial but is useful for performing transformations on data received from the AI Agent. Node 3 - ScrapingBee: Scrape Company's Website This node scrapes data from the URL provided using ScrapingBee. You can use any scraper of your choice, but ScrapingBee is recommended, as it allows you to configure scraper behavior directly. Once configured, copy the provided "curl" command and import it into n8n. Node 4 - HTML to Markdown This node converts the scraped HTML data to Markdown, which is then sent to OpenAI. The Markdown format generally uses fewer tokens than HTML. Improving the Workflow It's always a pleasure to share workflows, but creators sometimes want to keep some magic to themselves ✨. Here are some ways you can enhance this workflow: Handle potential errors Configure the scraper tool to scrape other pages on the website. Although this will cost more tokens, it can be useful (e.g., scraping "Pricing" or "About Us" pages in addition to the homepage). Instead of Google Sheets, connect directly to your CRM to enrich company data. Trigger the workflow from form submissions on your website and send the scraped data about the lead to a Slack or Teams channel.

Unleashing Creativity: Transforming Children's English Storytelling with Automation and AI Check this example: https://t.me/st0ries95 Summary In the realm of children's storytelling, automation is revolutionizing the way captivating tales are created and shared. This article highlights the transformative power of setting up a workflow for AI-powered children's English storytelling on Telegram. By delving into the use cases and steps involved, we uncover how this innovative approach is inspiring young minds and fostering a love for storytelling in children. Usecase The workflow for children's stories is a game-changer for content creators, educators, and parents seeking to engage children through imaginative and educational storytelling. Here's how this workflow is making a difference: Streamlined Content Creation: By providing a structured framework and automation for story generation, audio creation, and image production, the workflow simplifies the process of crafting captivating children's stories. Enhanced Educational Resources: Teachers can leverage this workflow to develop interactive educational materials that incorporate storytelling, making learning more engaging for students. Personalized Parental Engagement: Parents can share personalized stories with their children, nurturing a passion for reading and creativity while strengthening family bonds through shared storytelling experiences. Community Connection: Organizations and community groups can use the workflow to connect with their audience and promote literacy and creativity by creating and sharing children's stories. Inspiring Imagination: Through automated creation and sharing of enchanting stories, the workflow aims to spark imagination, inspire young minds, and instill a love for storytelling in children. Node Explanation OpenAI Chat Model: Utilizes the OpenAI Chat Model to generate text for the children's stories. Schedule Trigger: Triggers the workflow at set intervals (every 12 hours) to generate new stories. Recursive Character Text Splitter: Splits text into smaller chunks for processing. OpenAI Chat Model2: Another OpenAI Chat Model node for generating prompts for image creation. Send Story Text: Sends the generated story text to a specified Telegram chat. Send Audio for the Story: Sends audio files of the stories to the Telegram chat. Send Story Picture: Shares images related to the stories on Telegram. Create a Kids Stories: Generates captivating short tales for kids using prompts provided. Generate Audio for the Story: Converts generated text into audio files for storytelling. Create a Prompt for DALL-E: Creates prompts for generating images related to the stories. Generate a Picture for the Story: Generates pictures based on the prompts for visual storytelling. By embracing automation in children's storytelling, we unleash creativity, inspire young minds, and create magical experiences that resonate with both storytellers and listeners alike.

This workflow allows you to recognize a folder with receipts or invoices (make sure your files are in .pdf, .png, or .jpg format). The workflow can be triggered via the "Test workflow" button, and it also monitors the folder for new files, automatically recognizing them. Video Demo https://youtu.be/mGPt7fqGQD8 1. n8n import glitch After import, the trigger node "When clicking 'Test workflow'" might be disconnected. You need to connect it via 2 arrows to "Google Sheets1" and "Google Drive" nodes. So, the workflow has 2 triggers - via button, and via Google Sheets "new file" event - both of these triggers should be connected to 2 nodes. Here is how it should look like: https://ocr.oakpdf.com/n8n_fix.png 2. Set up RapidAPI HTTP auth key Create new "HTTP header" n8n credential and paste your RapidAPI key from https://rapidapi.com/restyler/api/receipt-and-invoice-ocr-api into it. https://ocr.oakpdf.com/n8n_api_key.png Make sure "HTTP Request" node uses this credential. 3. Set up your Google Auth You need a Google connection to work with your Google Sheets and Google Drive accounts: https://docs.n8n.io/integrations/builtin/credentials/google/oauth-generic/#finish-your-n8n-credential 4. Set up Google Sheets Copy this Google Sheets document: https://docs.google.com/spreadsheets/d/1G0w-OMdFRrtvzOLPpfFJpsBVNqJ9cfRLMKCVWfrTQBg/edit?usp=sharing Custom document formats and advanced usage Email: contact@scrapeninja.net Linkedin: https://www.linkedin.com/in/anthony-sidashin/

This workflow automatically pulls articles from an RSS feed, translates the content and title from English to Hindi using OpenAI, extracts the featured image from the HTML content, and publishes the translated post as a draft on a connected WordPress site. 🔧 Key Features: Polls RSS feed every 10 minutes for new articles Extracts and parses the featured image from custom HTML tags Translates content and title from English to Hindi using OpenAI Assistant Uploads the featured image to WordPress media library Associates the image with the new draft post Publishes the translated article as a draft for review 🎯 Use Case: Ideal for multi-language blog automation or content localization workflows where original content is in English and needs to be localized into Hindi before publishing.

When you fill out the form with business challenges and requirements GPT-4 analyzes the input and generates a customized proposal using your template System automatically creates a Google Slides presentation with personalized content Professional proposal email is sent directly to the prospect with the presentation link Set up steps Estimated time: 15-20 minutes Connect your OpenAI API key for GPT-4 access Link your Google account for Slides and Gmail integration Create your proposal template in Google Slides with placeholder variables Customize the AI prompt and email template with your branding Test with sample data and activate the workflow

Tags: Sustainability, CSRD, Reporting, ESG, Compliance, Automation Context Hey! I'm Samir, a Supply Chain Engineer and Data Scientist from Paris, founder of LogiGreen Consulting We help companies automate sustainability workflows using AI, Data Analytics, and No-Code tools like N8N. > Sustainability Reporting meets Automation with n8n! 📬 For business inquiries, you can add me on Here What is a CSRD XHTML Report? Under the Corporate Sustainability Reporting Directive (CSRD), companies must publish their ESG disclosures in a machine-readable XHTML format, embedding XBRL tags that make the report structured and standardized. These files must follow strict formatting and tagging rules to ensure compliance, traceability, and accessibility for both regulators and analysts. Who is this template for? This workflow is designed for sustainability teams, ESG consultants, or developers who want to automatically check the structure and format of CSRD reports submitted in XHTML. How does it work? This N8N workflow automates the audit process: 📤 Input Node → Uploads or fetches the XHTML file via URL or Webhook. 🧪 Validates Structure → Uses a custom code node to parse HTML and identify required tags (e.g., <ix:nonNumeric>, namespaces). 📋 Outputs a Report → Returns a summary report of errors, warnings, and key metadata (like entity name, reporting period). 📤 Export Option → Save the results in Google Sheets or send via email. Prerequisite A sample XHTML file that you can find in my GitHub Repository Google Sheets API* and *OpenAI API** credentials Next Steps Follow the sticky notes inside each node to adjust parsing rules or extend validation to specific XBRL tags relevant to your sector (e.g., GHG emissions, water usage). *📺 Check my complete tutorial to understand how to use it: * 🎥 Check My Tutorial 🚀 Interested in combining CSRD compliance with automation and analytics? Let’s connect on LinkedIn Notes This workflow includes an example XHTML file to test the validator. You can plug this into your internal systems or even extend it with AI to auto-summarize the sustainability report. This workflow has been created with N8N 1.82.1 Submitted: April 3rd, 2025

This workflow is designed for content creators or AI artists who want to automate posting unique AI-generated images to their Facebook Page multiple times a day. It uses Google Gemini via LangChain to generate imaginative image prompts, and Pollinations AI to generate the images. Posts are published with hashtags and a clean caption. Who Is It For AI artists Facebook page managers Digital marketers looking for automated creative content What It Does Triggers 3x daily at 7:00, 11:00, and 17:00 (local time) Generates random AI image prompts in a retro-futuristic, cinematic, or surreal style using Google Gemini Fetches images from Pollinations AI using custom prompts Posts images automatically to your Facebook Page with hashtags Requirements n8n self-hosted or desktop (workflow uses schedule trigger) Pollinations API (no auth needed) Facebook Page with Facebook Graph API token: Required scopes: pages_manage_posts, pages_read_engagement, pages_show_list Google Gemini API Key (used via LangChain node) How to Customize Change the prompt style in the Basic LLM Chain node (promptType: define) to suit your theme. Adjust Set The Generator Image node if you want: Different image sizes (width / height) Different seed randomness Other Pollinations models (&model=kontext) Add Telegram/Twitter nodes if you want cross-posting Use Set node to allow easy user-level configuration of models, hashtags, times, etc.

This workflow allows you to add positive feedback messages to a table in Notion. Prerequisites Create a Typeform that contains Long Text filed question type to accepts feedback from users. Get your Typeform credentials by following the steps mentioned in the documentation. Follow the steps mentioned in the documentation to create credentials for Google Cloud Natural Language. Create a page on Notion similar to this page. Create credentials for the Notion node by following the steps in the documentation. Follow the steps mentioned in the documentation to create credentials for Slack. Follow the steps mentioned in the documentation to create credentials for Trello. Typeform Trigger node: Whenever a user submits a response to the Typeform, the Typeform Trigger node will trigger the workflow. The node returns the response that the user has submitted in the form. Google Cloud Natural Language node: This node analyses the sentiment of the response the user has provided and gives a score. IF node: The IF node uses the score provided by the Google Cloud Natural Language node and checks if the score is positive (larger than 0). If the score is positive we get the result as True, otherwise False. Notion node: This node gets connected to the true branch of the IF node. It adds the positive feedback shared by the user in a table in Notion. Slack node: This node will share the positive feedback along with the score and username to a channel in Slack. Trello node: If the score is negative, the Trello node is executed. This node will create a card on Trello with the feedback from the user.