Workflow Templates

This workflow converts Notion pages to markdown, and then converts that markdown back to Notion blocks. It will triple the content of the last updated page it finds. This is useless by itself, but you can copy-paste from this workflow to create your own. Prerequisites A notion account with some pages or databases Setup instructions Create a notion credential and share some pages as described here: https://docs.n8n.io/integrations/builtin/credentials/notion/ How it works The HTTP Request gets notion child blocks from a page, because the default n8n block only gets plain text and no links. The first code block converts it to markdown. The second code block converts it back to Notion blocks The last HTTP block appends everything to the original Notion page, essentially duplicating it for the purpose of demoing the script. I hope in the future we get official n8n blocks that extract markdown, or use markdown to write to Notion. There is community block that also does this, but this template is easier: you can simply copy-paste the blocks from this workflow.

Quickly transform any LinkedIn profile URL into a concise, AI‑generated professional summary — perfect for recruiters, sales teams, and hiring managers who need instant insights into prospects or candidates without manual research. How it works The workflow polls a Google Sheet for new or updated rows containing LinkedIn profile URLs. For each URL, the Real‑Time LinkedIn Scraper API (via RapidAPI) pulls experience and education sections. Extracted profile data is sent to OpenAI’s GPT model, which generates a clean, structured summary highlighting key strengths, career trajectory, and differentiators. The generated summary is written back into a new column in the same row of your Google Sheet for easy review and sharing. Set up steps Connect your Google account and select the spreadsheet + worksheet containing your list of LinkedIn URLs. Sign up for the Real‑Time LinkedIn Scraper API on RapidAPI, copy your API key, and add it to the workflow’s HTTP Request node. Insert your OpenAI API key credentials. Ensure your Google Sheet has one column for “linkedin_url” and create two empty columns named “full_name” and "summary" (or customize them based on your needs). Run a single row through the workflow to verify scraping accuracy and summary formatting, then turn on the workflow for continuous automation. With this template, eliminate hours of manual profile review — instantly gain actionable insights and focus on what really matters: building relationships and closing deals.

Auto-Categorize Outlook Emails with AI in n8n How It Works Trigger: The workflow starts with the Microsoft Outlook Trigger node, polling your inbox every minute for new emails. Extract & Clean Email Content: The email’s key fields (from, subject, isRead, body) are extracted. The body is converted from HTML to Markdown, then sanitized to plain text for reliable AI processing. Node Setup Details: Microsoft Outlook Trigger Resource: Message Operation: Trigger on new email Fields to Output: from, subject, isRead(optional), body Folders to Include: (Set to your Inbox or specific folder IDs) Markdown Node Input: {{$json"body"}} (HTML email body) Output Key: Email Body Markdown Purpose: Converts HTML to Markdown for easier downstream processing. Sanitize Node (Code Node) Input: Email Body Markdown from previous node Purpose: Cleans up Markdown, strips images, links, HTML tags, table formatting, and truncates to 4000 characters. Sample JS Code: // Get the markdown content from the previous node const markdownContent = $input.item.json["Email Body Markdown"]; Setup AI tools Move message and Get Folders Outlook tools are required, get contacts is optional. Set each field in the tools to "defined automatically by the model" and describe each field so the model understands how to use it. OpenRouter or other LLM models tool: You can use any client for this, but make sure to use a model that does well with tool calls (Claude, GPT-4.1, Gemini 2.5 Pro, etc.). Best Practices & Notes AI Prompt Engineering:** The AI is instructed to be conservative—never move emails from real people or saved contacts, and always explain its reasoning if it doesn’t move a message. This automation only works for NEW incoming messages. Inbox Zero:** This system is designed to help you achieve and maintain Inbox Zero by keeping only actionable items in your main inbox. Customization:** You can adjust the folder logic, add more categories, or tweak the AI prompt for your specific needs. Privacy:** All processing happens within your n8n instance; no email data is stored outside your environment except for the AI call (which only receives sanitized, minimal content).

How it works creates a new page in Confluence based on a page template also defined in Confluence replaces any number of placeholders with data from your workflow generic implementation for maximum flexibility Set up steps All parameters you need to change are defined in the Set node Set your Atlassian-domain Set the template id you want to use as the basis for new pages Set the target space and parent page for new pages added based on that template. 🎥 Explainer video has all the details. =) Feedback Any feedback is welcome. If you have ideas for improvements, let me know.

📄 What this workflow does This workflow helps you analyze Google reviews of any business to generate powerful marketing insights. By simply submitting a business name and its Google Place ID, it fetches the top 30 reviews and uses GPT-4 (via LangChain Agent) to extract valuable customer insights such as marketing angles, customer motivations, product pain points, and voice of customer (VOC) quotes. The output is stored automatically in a connected Google Sheet. 👤 Who is this for Marketing teams looking for messaging inspiration Founders or product managers exploring customer feedback Brand strategists gathering real-world insights Agencies running VOC or sentiment analysis 🛠️ Requirements Dumpling AI API key** OpenAI GPT-4 or GPT-4o access** Google Sheets connection** A form or manual input with: Business Name Google Place ID ⚙️ How to set up Connect Credentials Dumpling AI (via HTTP Header Auth) OpenAI (GPT-4) Google Sheets (OAuth2) Prepare your Google Sheet Create columns: Business Name, Place ID, Marketing Angles, Customer Motivations, Frictions and Barriers, Product Opportunities, VOC Snippets Update Nodes Replace the Google Sheets Document ID and Tab Name with yours Check that the Dumpling API node is linked to your credential Optional: tweak the prompt in the LangChain Agent node to fit your tone or goals 🤖 How it works (Workflow Steps) User submits business name + Google Place ID Dumpling AI fetches top 30 reviews Workflow aggregates review text GPT-4 via LangChain analyzes the reviews Insights are parsed and logged to Google Sheets 💡 Customization Ideas Push output to Notion, Airtable, or Slack Add sentiment scoring to prioritize themes Create summaries for each insight category Schedule insights to be emailed weekly This is a plug-and-play VOC research workflow — great for founders, marketers, and product teams who want actionable data from real customers without doing manual review scraping or summarizing.

This workflow analyzes images submitted via a form using OpenAI Vision, then delivers the analysis result directly to your Telegram chat. ✅ Use case examples: • Users submit screenshots for instant AI interpretation • Automated document or receipt analysis with Telegram delivery • Quick OCR or image classification workflows ⸻ ⚙️ Setup Guide Form Submission Trigger • Connect your form app (e.g. Typeform, Tally, or n8n’s own webhook form) to the On form submission trigger node. • Ensure it sends the image file or URL as input. OpenAI Vision Analysis • In the OpenAI node, select Analyze Image operation. • Provide your OpenAI API key and configure the prompt to instruct the model on what to analyze (e.g. “Describe this receipt in detail”). Set Telegram Chat ID • Use this manual node to input your Telegram Chat ID for delivery. • Alternatively, automate this with a database lookup or user session if building for multiple users. Telegram Delivery Node • Connect your Telegram Bot to n8n using your bot token. • Set up the sendMessage operation, using the analysis result from the previous node as the message text. Testing • Click Execute workflow. • Submit an image via your form and confirm it delivers to your Telegram as expected.

Automate Customer Feedback Analysis with Google Sheets, WhatsApp, and Email Introduction: Drowning in Data, Starving for Insight? Imagine this: Your team launches a new feature. Feedback starts pouring in emails, support tickets, social media mentions, and survey responses. You know gold is buried in there, but manually reading, tagging, and summarising hundreds, maybe thousands, of comments? It takes days, maybe weeks. By the time you have a clear picture, the moment might have passed. Sounds exhausting, right? What if you could have an AI assistant tirelessly working 24/7, instantly analysing every piece of feedback the moment it arrives? This isn't science fiction anymore. AI-powered automation can transform this slow, manual chore into a real-time insight engine, giving you the pulse of your customer base almost instantly. Let's explore how. What's the Goal? Understanding the Workflow Objective The core challenge is transforming raw, unstructured customer feedback into actionable intelligence quickly and efficiently. The Problem: Manual Overload: Sifting through vast amounts of feedback manually is incredibly time-consuming and prone to human error or bias. Delayed Insights: The lag between receiving feedback and understanding it means missed opportunities and slow responses to critical issues. Inconsistent Analysis: Different team members might interpret or categorize feedback differently, leading to unreliable trend spotting. The AI Solution: Automated Data Collection: Connects directly to feedback sources (surveys, social media, review sites, helpdesks). AI-Powered Analysis: Uses Large Language Models (LLMs) like GPT-4 or Claude to analyze sentiment, extract key topics, and summarize comments. Intelligent Categorization: Automatically tags feedback based on predefined or dynamically identified themes (e.g., "bug report," "feature request," "pricing issue"). Real-time Reporting: Pushes structured insights into dashboards, databases, or triggers notifications for immediate awareness. Outcome: You move from reactive problem-solving based on stale data to proactive, strategic decisions driven by a near real-time understanding of customer sentiment and needs. Why Does It Matter? Achieving 100X Productivity and Efficiency Look, automating feedback isn't just about saving time; it's about scaling your ability to listen and respond smarter, not harder. When you leverage AI, the gains aren't incremental - they're exponential. Here’s why this is a game changer: Blazing Speed: Analyse feedback 100x Faster (or more!) than manual methods. Insights appear in minutes or hours, not days or weeks. Unhuman Scalability: Process virtually unlimited volumes of feedback without needing to scale your human team proportionally. AI doesn't get tired or bored. Consistent Accuracy: AI applies analysis rules consistently, reducing human bias and ensuring reliable categorisation and sentiment scoring over time. Proactive Trend Spotting: Identify emerging issues or popular requests much earlier by analysing aggregated data automatically. Spot patterns humans might miss. Free Up Your Team: Let your talented team focus on acting on insights – improving products, fixing issues, engaging customers – instead of drowning in data entry. How It Works: AI Automation Step by Step Getting this set up is more straightforward than you might think, especially with tools like n8n acting as the central hub. Automated Feedback Triggering CRM/Website Event Node Trigger feedback requests after: Purchases (eCommerce) Support ticket resolution Feature usage (SaaS) Time-Based Node Schedule recurring NPS surveys Customer health check-ups Chat App Node (WhatsApp/Telegram/Messenger) Send conversational feedback prompts: "How was your recent experience with [specific interaction]?" Multi-Channel Feedback Collection Email Node (SendGrid/Mailchimp) Send personalized feedback requests Embed 1-5 rating widgets SMS Node (Twilio) Short mobile surveys: "Reply 1-5: How satisfied with your purchase?" Webhook Node Capture in-app feedback Process chatbot responses Social Media Node Monitor Twitter/X, Instagram mentions Analyze comments for unsolicited feedback AI-Powered Real-Time Analysis OpenAI/ChatGPT Node (Sentiment Analysis) Prompt: "Analyze sentiment (positive/neutral/negative) and key themes from: [customer feedback]" Output fields: Sentiment score (1-5) Urgency flag (high/medium/low) Key topics (billing, support, product, etc.) Translation Node (Optional) Convert multilingual feedback into a consistent language Instant AI Response System Conditional Node (Routing Logic) Positive feedback → Send thank-you + referral ask Neutral feedback → Follow-up question for details Negative feedback → Escalate to the human team AI Response Generator Node Prompt: "Create a personalized response to [feedback type] about [topic] with sentiment [score]" Adjust tone (professional/friendly/empathetic) Escalation Node Route critical issues to the support team with full context Automated Insights & Alerts Dashboard Node Real-time sentiment tracking Emerging issue detection Alert Node (Slack/Teams/Email) Notify teams of negative trends: "3+ complaints about checkout flow in the past hour!" Report Node Auto-generate weekly/monthly summaries: "Top 5 customer pain points this week" Product Board Integration Auto-create feature requests Prioritize based on feedback volume Tools of the Trade: AI & Automation Tech Stack You don't need a massive, complex tech stack. Focus on a few core, powerful tools: n8n: The workflow automation platform. This is the 'glue' that connects everything and orchestrates the process without needing deep coding knowledge. Honestly, it's incredibly versatile. OpenAI (GPT-4/GPT-4o): State-of-the-art LLM for high-quality text analysis, summarization, and classification. Great for complex understanding. Anthropic (Claude 3 Sonnet/Opus): Another top-tier LLM, known for strong performance in analysis and handling large contexts. Often, a great alternative or complement to GPT models. Feedback Sources APIs: Connectors for where your feedback lives (e.g., Typeform, SurveyMonkey, Twitter API, Zendesk API, Google Play/App Store review APIs). Data Storage/Destination: Where the processed insights go (e.g., Google Sheets, Airtable, Notion, PostgreSQL database, BigQuery). (Optional) Visualization Tool: Tools like Metabase, Grafana, Looker Studio, or Power BI to create dashboards from your structured feedback data. What's the Cost? Estimated Budget Let's talk investment. You're mainly looking at: Setup Costs: Primarily your time (or a consultant's) to design and build the initial workflow in n8n. Depending on complexity, this could range from a few hours to a few days. No major software licenses are usually needed upfront if using self-hosted n8n or starting with free/low-tier cloud plans. AI API Calls: You pay per usage to OpenAI/Anthropic. Costs depend heavily on volume but can start from $20-$50/month for moderate usage and scale up. Newer models are getting more cost-effective. n8n Hosting: Free if self-hosted (requires a server), or tiered cloud pricing starting around $20/month. Feedback Source APIs: Some platforms might have API access costs or rate limits on free tiers. Total Estimated Monthly Cost: For many businesses, ongoing costs can range from $50 - $500+ per month, highly dependent on feedback volume and AI model choice. The Return on Investment (ROI) is typically rapid. Consider the hours saved from manual analysis, the value of faster issue resolution, preventing churn, and the benefits of making product decisions based on real-time data. It often pays for itself very quickly. Who Benefits? Target Users and Industries This automated feedback loop isn't niche; it's valuable across many sectors and roles: Top Industries: SaaS (Software as a Service): Understanding user friction, feature requests, bug reports. E-commerce & Retail: Analyzing product reviews, post-purchase surveys, and support chats. Hospitality & Travel: Processing guest reviews, survey feedback. Mobile Apps: Monitoring app store reviews, in-app feedback. Financial Services: Gauging customer satisfaction with services, identifying pain points. Key Roles: Product Managers: Prioritizing features, understanding user needs, tracking launch reception. Customer Experience (CX) / Success Managers: Monitoring customer health, identifying churn risks, and improving support processes. Marketing Teams: Understanding brand perception, campaign feedback, and voice of the customer. Support Leads: Identifying recurring issues, measuring support quality, spotting training needs. This approach works for businesses of all sizes, from startups wanting to stay lean and agile to large enterprises needing to manage massive feedback volumes. How to use workflow? Importing a workflow in n8n is a straightforward process that allows you to use pre-built or shared workflows to save time. Below is a step-by-step guide to import a workflow in n8n, based on the official documentation and community resources. Steps to Import a Workflow in n8n 1. Obtain the Workflow JSON Source the Workflow:** Workflows are typically shared as JSON files or code snippets. You might receive them from: The n8n community (e.g., n8n.io workflows page). A colleague or tutorial (e.g., a .json file or copied JSON code). Exported from another n8n instance (see export instructions below if needed). Format:** Ensure you have the workflow in JSON format, either as a file (e.g., workflow.json) or as text copied to your clipboard. 2. Access the n8n Workflow Editor Log in to n8n:** Open your n8n instance (via n8n Cloud or your - self-hosted instance). Navigate to the Workflows tab in the n8n dashboard. Open a New Workflow:** Click Add Workflow to create a blank workflow, or open an existing workflow if you want to merge the imported workflow. 3. Import the Workflow Option 1: Import via JSON Code (Clipboard): In the n8n editor, click the three dots (⋯) in the top-right corner to open the menu. Select Import from Clipboard. Paste the JSON code of the workflow into the provided text box. Click Import to load the workflow into the editor. Option 2: Import via JSON File: In the n8n editor, click the three dots (⋯) in the top-right corner. Select Import from File. Choose the .json file from your computer. Click Open to import the workflow. Note: If the workflow includes nodes for apps requiring credentials (e.g., Google Sheets), you’ll need to configure those credentials separately after importing.

Guidebook: How the Website ChatBot Template Works Chapter 1: Introduction & Objectives This guidebook provides a comprehensive walkthrough of the Website ChatBot developed using n8n and OpenAI. The chatbot is designed to qualify real estate leads and encourage site visits for the Alcove New Kolkata Sangam project through personalized, intelligent conversations. Chapter 2: Tools Required 1. n8n Workflow Automation Tool An open-source workflow builder to automate data flows between services. 2. OpenAI Account with GPT-4o-mini Access For generating AI-based chatbot responses. 3. Web Chat Widget Frontend integration that sends messages via webhook to the chatbot. Chapter 3: Workflow Breakdown Step 1: Webhook Receives POST requests from the chat widget. Endpoint: /webhook/chatbot-webhook Step 2: Set User Message Extracts message from the JSON body. Stores it as user_message. Step 3: Memory Setup Uses session ID to track conversation across messages. Step 4: OpenAI Chat Model GPT-4o-mini processes queries using the defined agent prompt. Step 5: AI Agent (Khusboo) Persona of a pre-sales agent. Uses AIDA + BANT + SPIN + PAS frameworks. Shares videos, responds in Hinglish, schedules site visits. Step 6: Respond to Webhook Formats the chatbot's reply into a JSON response. Chapter 4: Strategy & Psychology Behind Responses | Framework | Purpose | | --------- | ---------------------------------------------------- | | AIDA | Capture attention, interest, desire, action | | BANT | Qualify Budget, Authority, Need, Timing | | SPIN | Understand user's Situation, Problems, Implications | | PAS | Tackle objections using Problem, Agitation, Solution | The chatbot aims to qualify leads and gently move them toward booking a site visit without pushing or over-informing. Chapter 5: Setup Instructions A. n8n Workflow Setup Import the JSON workflow. Ensure OpenAI credentials are set up. Enable webhook at /webhook/chatbot-webhook. B. Frontend Widget Integration Send message as POST to the webhook with structure: { "message": "Looking for 2 BHK", "session_id": "user123" } Chapter 6: Testing & Troubleshooting Test via Postman Send sample request to verify AI response. Common Issues | Issue | Fix | | ---------------- | ----------------------------------- | | No response | Check webhook URL or credentials | | Repeated replies | Ensure memory node is active | | Wrong language | Check system message language rules | Chapter 7: Sample Conversations User: Hi, I’m looking for a home near the Ganga. Bot: Namaste! Main Khusboo hoon, Alcove New Kolkata Sangam se. Aapka naam kya hai? User: Rajat. Bot: Great Rajat! Kya aap apne family ke saath shift hone ka plan kar rahe ho? ... (continues using frameworks) Chapter 8: FAQs & Maintenance Tips Q: Can I update the AI agent persona? A: Yes, by modifying the system message inside the AI Agent node. Q: How do I share new videos or links? A: Add them in the sharingVideos or UserRequests section in the system message. Q: How to scale this for multiple projects? A: Duplicate the workflow and update the aboutProject and links accordingly. End of Guidebook.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Automatically transform audio files into professional transcription reports with AI-powered speech recognition, timestamp generation, and formatted Google Docs output. What this workflow does Monitors Gmail for incoming audio attachments Downloads and processes audio files using VLM Run AI transcription Generates accurate transcriptions with precise timestamps and segmentation Creates professional reports in Google Docs with formatted output Handles asynchronous processing for long audio files without timeouts Setup Prerequisites: Gmail account, VLM Run API credentials, Google Docs access, self-hosted n8n. You need to install VLM Run community node Quick Setup: Configure Gmail OAuth2 for email monitoring Add VLM Run API credentials for audio transcription Set up Google Docs OAuth2 for report generation Create target Google Doc for transcription reports Update document URL in workflow nodes Test with sample audio file and activate Perfect for Meeting recordings and conference calls Voice memos and dictation workflows Interview transcriptions and journalism Podcast episode documentation Accessibility compliance and documentation Legal proceedings and court recordings Educational content and lecture notes Customer service call analysis Key Benefits Human-level accuracy** - Advanced AI speech recognition with automatic punctuation Timestamp precision** - Segmented transcriptions with exact time markers Multi-format support** - Handles MP3, WAV, M4A, AAC, OGG, FLAC files Asynchronous processing** - No timeouts for long audio files Professional formatting** - Beautifully structured Google Docs reports Automatic workflow** - Zero manual intervention required Saves hours per recording** - Transforms manual transcription into instant results Searchable documentation** - Google Docs integration enables easy content discovery How to customize Extend by adding: Speaker identification and diarization Integration with project management tools (Notion, Asana, Trello) Automatic summary generation from transcripts Translation to multiple languages Slack notifications for completed transcriptions Integration with CRM systems for call logging Audio quality enhancement preprocessing Custom formatting templates for different use cases Automatic keyword extraction and tagging Integration with calendar systems for meeting context This workflow revolutionizes audio documentation by combining cutting-edge AI transcription with professional report generation, making spoken content instantly accessible, searchable, and shareable across your organization.

This n8n workflow demonstrates how to transform natural language date and time expressions into structured data with 96%+ accuracy. Parse complex expressions like "early next July", "2 weeks after project launch", or "end of Q3" into precise datetime objects with confidence scoring, timezone intelligence, and business rules validation for any automation workflow. Good to know Achieves 96%+ accuracy on complex natural language date expressions At time of writing, this is the most advanced open-source date parser available Includes AI learning that improves over time with user corrections Supports 6 languages with auto-detection (English, Spanish, French, German, Italian, Portuguese) Sub-millisecond response times with intelligent caching Enterprise-grade with business intelligence and timezone handling How it works Natural Language Input**: Receives date expressions via webhook, form, email, or chat AI-Powered Parsing**: Your world-class date parser processes the text through: 50+ custom rule patterns for complex expressions Multi-language auto-detection and smart translation Confidence scoring (0.0-1.0) for AI decision-making Ambiguity detection with helpful suggestions Business Intelligence**: Applies enterprise rules automatically: Holiday calendar awareness (US + International) Working hours validation and warnings Business day auto-adjustment Timezone normalization (IANA format) Smart Scheduling**: Creates calendar events with: Structured datetime objects (start/end times) Confidence metadata for workflow decisions Alternative interpretations for ambiguous inputs Rich context for follow-up actions Integration Ready**: Outputs connect seamlessly to: Google Calendar, Outlook, Apple Calendar CRM systems (HubSpot, Salesforce) Project management tools (Notion, Asana) Communication platforms (Slack, Teams) How to use The webhook trigger receives natural language date requests from any source Replace the MCP server URL with your deployed date parser endpoint Configure timezone preferences for your organization Customize business rules (working hours, holidays) in the parser settings Connect calendar integration nodes for automatic event creation Add notification workflows for scheduling confirmations Use Cases Meeting Scheduling**: "Schedule our quarterly review for early Q3" Project Management**: "Set deadline 2 weeks after product launch" Event Planning**: "Book venue for the weekend before Labor Day" Personal Assistant**: "Remind me about dentist appointment next Tuesday morning" International Teams**: "Team standup tomorrow morning" (auto-timezone conversion) Seasonal Planning**: "Launch campaign in late spring 2025" Requirements Natural Language Date Parser MCP server (provided code) Webhook endpoint or form trigger Calendar integration (Google Calendar, Outlook, etc.) Optional: Slack/Teams for notifications Optional: Database for learning pattern storage Customizing this workflow Multi-language Support**: Enable auto-detection for global teams Business Rules**: Configure company holidays and working hours Learning System**: Enable AI learning from user corrections Integration Depth**: Connect to your existing calendar and CRM systems Confidence Thresholds**: Set minimum confidence levels for auto-scheduling Ambiguity Handling**: Route unclear dates to human review or clarification requests Sample Input/Output Input Examples: "early next July" "2 weeks after Thanksgiving" "next Wednesday evening" "Q3 2025" "mañana por la mañana" (Spanish) "first thing Monday" Rich Output: { "parsed": [{ "start": "2025-07-01T00:00:00Z", "end": "2025-07-10T23:59:59Z", "timezone": "America/New_York" }], "confidence": 0.95, "method": "custom_rules", "business_insights": [{ "type": "business_warning", "message": "Selected date range includes July 4th holiday" }], "predictions": [{ "type": "time_preference", "suggestion": "You usually schedule meetings at 10 AM" }], "ambiguities": [], "alternatives": [{ "interpretation": "Early July 2026", "confidence": 0.15 }], "performance": { "cache_hit": true, "response_time": "0.8ms" } } Why This Workflow is Unique World-Class Accuracy**: 96%+ success rate on complex expressions AI Learning**: Improves over time with user feedback Global Ready**: Multi-language and timezone intelligence Business Smart**: Enterprise rules and holiday awareness Performance Optimized**: Sub-millisecond cached responses Context Aware**: Provides confidence scores and alternatives for AI decision-making Transform your scheduling workflows from rigid form inputs to natural, conversational date requests that your users will love!

Overview In cold email campaigns, the lead's company name is the 2nd most frequently inserted variable after their first name. They're critical for effective cold email personalization. However, company names are often messy and can contain taglines, legal suffixes (e.g. LLC, Inc.), and other variations that would never be written out by a human in an email. If your email starts with "I came across Techwave Solutions LLC on LinkedIn...", it's a dead giveaway that you're sending a tempalted email and a response is much less likely. This simple workflow uses AI to clean up messy company names in a Google Sheet so that your cold email campaigns can achieve better results. How It Works A form is submitted with a Google Sheet url The workflow grabs the leads and uses an LLM node to clean the company names The updated leads are saved back in a new sheet within the original spreadsheet Setup Steps Add your Google Sheets and OpenAI (or your AI model provider of choice) credentials to n8n Create a Google Sheet with your list of leads. IMPORTANT: the sheet MUST have a column called "Company" (Optional). The AI workflow has a highly optimized system prompt. However, you may achieve better results by updating the list of examples in the prompt with companies (real or fake) in the industry you're targeting. If you have any questions or feedback about this workflow, or would like me to build custom workflows for your business, email me at n8n@paperjam.agency.

Who is this for? This workflow is designed for YouTubers who want to update their video descriptions in bulk without manually editing each one. It's especially useful for creators who include a standard set of links in their descriptions and need to insert a new link between existing ones across multiple videos. What problem does this workflow solve? Manually updating video descriptions for multiple videos can be tedious and time-consuming. If you have a section in your video descriptions that contains important links, adding a new one in a specific position (e.g., between two existing links) can be a challenge. This workflow automates that process, allowing you to insert a specific string between two predefined rows in all of your video descriptions at once. What this workflow does Fetches all videos from your YouTube channel. Iterates through each video to retrieve its existing description. Identifies two predefined rows in the description. Inserts a new row between the two specified rows. Updates the video description with the modified text. Setup Connect your YouTube account to n8n and grant necessary permissions. Define your variables in the "Set String to Insert" node: rowBefore: The existing row after which the new row will be inserted. rowToInsert: The new text or link to insert. rowAfter: The existing row before which the new row will be inserted. Run the workflow using the manual trigger. Review the updated descriptions to ensure accuracy. How to customize this workflow to your needs Change the insertion criteria** by modifying the rowBefore and rowAfter values. Insert multiple rows** by adjusting the JavaScript code in the Code node. Extend the workflow** by adding conditions (e.g., only updating descriptions of videos with certain tags). Filter specific** videos instead of updating all by modifying the "Get All Videos" node. This workflow ensures that all your YouTube descriptions stay updated and consistent with minimal effort.