Workflow Templates

Who Is This For This workflow is ideal for content creators, solo founders, marketers, and AI enthusiasts who want to automate the full process of blog content creation. It is especially useful for professionals in tech, AI, and automation who publish frequently and need SEO-ready content fast. What Problem Does This Workflow Solve Creating SEO-optimized blog content is time-consuming and requires consistency. Manually researching trending topics slows down the content pipeline. Formatting, publishing, and promoting across multiple platforms takes effort. This workflow automates the entire process from research to publication. What This Workflow Does Research: Uses Perplexity AI to gather up-to-date content ideas via form input. Content Generation: GPT-4 creates a short, SEO-optimized article (max 20 lines) with H1, H2 structure and meta-description. Publishing: Automatically posts the content to WordPress. Email Notification: Sends the article title and URL via Gmail. Slack Notification: Notifies a specified Slack channel when the article is live. Database Logging: Saves the article details to a Notion database. Setup Guide Prerequisites WordPress account with API access OpenAI API Key Perplexity API Key Slack Bot Token Notion integration (Database ID) Gmail API credentials (optional) Community Node Required: This workflow uses n8n-nodes-mcp, which only works on self-hosted instances of n8n. > To install: Go to Settings > Community Nodes > Install n8n-nodes-mcp Steps Import the workflow into your n8n instance Install the required community node (n8n-nodes-mcp) Set up API credentials for OpenAI, Perplexity, WordPress, Slack, Gmail, and Notion Customize the form trigger with your preferred prompt Run a test using a sample topic How to Customize This Workflow Modify the research prompt to match your niche or industry Adjust GPT-4 settings for tone, structure, or content length Customize Notion fields (e.g., add tags, categories, or labels) Add logic for generating or assigning featured images automatically

Automated Gmail Labeling and Brainstorming This template can be used to automatically label your incoming Gmail messages with AI and to build a knowledge graph from the emails tagged with a specific label to brainstorm new ideas based on them. You can also get notified about the emails with the most important labels via Telegram as well as receive new ideas as you are building a knowledge graph of incoming messages. The idea generation is based on the InfraNodus knowledge graph content gap detection algorithm, which builds a network from your content and then finds a blind spot and uses AI to generate an interesting research question or idea that can be used to bridge this gap. Why it works so well? Think of all the business emails you receive that bypass the spam filters. Probably, they are personalized to you already. Now imagine if you build a knowledge graph from them for over a month. You will then have a ideation device based on your interests and marketing profile. Now, if you identify the gaps inside and generate interesting research questions based on them, you will come up with new interesting ideas that will be relevant (because they touch on the topics that matter to you), but novel, because they bridge them in new ways. What is it useful for? Automate Gmail incoming message labeling** with the new Classifier n8n node — much more advanced than the default Gmail labeling rules. Get notified via Telegram (or a messenger of your choice) about the most important messages and be sure not to miss anything important. Keep the messages with a certain label saved into knowledge graph for brainstorming and ideation. Every time a new message of this category comes in, it's added into the graph, changing its structure, a new idea is generated. So instead of looking at each specific offer, you now use them to generate insights for you. How it works Step 1: This template can is triggered automatically when a new Gmail message arrives. Note: you need to connect your Gmail account here in this node Step 2: We use the new n8n AI Classifier Node to classify your email based on its content. You might need to update to n8n 1.94 version to make it work. Note: we like to use Gemini AI for that classifier as it's the same company as Gmail, so should be safe with data Step 3: After classifying the message, we label the message with the appropriate label. Note: you need to create the labels before in your Gmail account Step 4: For a certain category (e.g. "Business" you format the message and save it into your InfraNodus graph. *Note: specify your InfraNodus API here and choose the name of the graph. It will use the InfraNodus HTTP graphAndEntries endpoint and save your data to an InfraNodus graph. By default, we save the text knowledge graph using the contextSettings parameters (it will only build a text graph of the content), but you can take an alternative setting from this InfraNodus HTTP node's settings and create a social knowledge graph, that will also show email senders in the graph itself.* Step 5 (optional): Generate an interesting insight question with the graphAndAdvice endpoint) of InfraNodus. Step 6 (optional): Then send this insight via Telegram to a chat. Step 7 (optional): Link some important labels to the second Telegram notification node, so you receive important messages for specified labels. Step 8 (optional): Send a Telegram notification We use Telegram, because it takes only 30 seconds to set up a bot with an API (send /newbot to @botfather, unlike Discord or Slack, which is long and cumbersome to set up. You can also attach a Gmail send node and generate an email instead. How to use You need an InfraNodus GraphRAG API account and key to use this workflow. Create an InfraNodus account or log in. Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes. Add this Authorization code in Steps 4 and 5 of the workflow. Come up with the name of the graph and change it in the HTTP InfraNodus nodes in the steps 4 and 5 and also in the Telegram node in Step 6 that sends a link to the graph. For additional text processing / idea generation settings you can use in the HTTP InfraNodus nodes, see the InfraNodus access points page. For example, in Step 4 you can change the text processing settings to build a social knowledge graph (settings are available in the Node's Notes section) and in Step 5 you can change the requestMode from question to idea to receive business ideas instead. Authorize your Gmail account for Steps 2, 3, 7 and 8 Gmail nodes. The easiest way to set it up is to open a free Google Console API account and to create an OAuth access point for n8n. You can then reuse it with other Google services like Google Sheets, Drive, etc. So it's a useful thing to have in general. Set up the Gemini AI API key using the instructions in the Step 2 Gemini AI classification node. Set up the Telegram node bot for the Step 8. It takes only 30 seconds: just go to @botfather and type in /newbot and you'll have an API key ready. To get the conversation ID, follow the n8n / Telegram instructions in the node itself. Once everything is ready, try to run the default automated workflow to test if everything works well. Requirements An InfraNodus account and API key An Google Cloud API OAuth client and key for Gmail access A Gemini AI API key A Telegram bot API key n8n version 1.94 and higher (for Text Classification AI node to work) Customizing this workflow Check our other n8n workflows at https://n8n.io/creators/infranodus/ for useful content gap analysis, expert panel, and marketing, and research workflows that utilize GraphRAG for better AI generation. Finally, check out https://infranodus.com to learn more about our network analysis technology used to build knowledge graphs from text. For support, please, contact https://support.noduslabs.com

Description This workflow automatically generates personalized certificates in Google Slides and emails them to respondents only if they meet a minimum score threshold, using data submitted via Google Forms (stored in Google Sheets). Ideal for: Online courses Quizzes and workshops Event participation certificates Sheet Requirements Your connected Google Sheet (from the Google Form) must contain: Full Name – The name to appear on the certificate. Email – Recipient’s email address. Score – The test/quiz score used for threshold logic. Setup Instructions Connect Google Sheets – Make sure your Form responses are linked to a Sheet with the columns mentioned above. Set Score Threshold – Modify the If node to your desired minimum score (e.g., >= 80). Customize Certificate Template – Use a Google Slides file with text placeholders like {{Full Name}}. Connect Gmail & Google Drive – For sending emails and saving generated certificates. Update File IDs – Replace any placeholder Slide and Drive file IDs with your own. Services Used Google Sheets (Form responses) Google Slides (Certificate template) Google Drive (Storage) Gmail (Email delivery) Troubleshooting Issue: "Cannot read property 'Score'" → Ensure your column names match exactly (Score, Full Name, etc.). Slides not replacing placeholders → Double-check placeholder format ({{Full Name}}) and capitalization. Emails not sending → Verify Gmail authentication and make sure the If node is correctly filtering results.

Automatic lead enrichment in Slack: monitors your Slack channel for new lead emails posted there, extracts each company’s name or domain, sends it to the Extruct API for data enrichment, then posts back a structured Slack card with company name, website, LinkedIn profile, number of employees, industry, recent news, and key contacts. Who’s it for: Sales teams, SDRs, and marketing ops who capture new lead information in Slack and want instant enrichment without leaving the channel. How it works: When a lead email is posted into your designated Slack channel, the workflow: Monitors for any new message containing a company name or domain. Extracts that company identifier. Sends it to Extruct API for research. Waits for enrichment to complete. Posts back into the same Slack thread a formatted card with: Company name Website LinkedIn profile Number of employees Industry Recent news Key contacts How to set up: Sign up for Extruct AI Copy the Extruct table ID Create & install your Slack app Configure n8n credentials & channel Activate & use Requirements: Extruct account & API token Extruct table template Slack workspace with permission to install apps

This n8n workflow template uses uProc's "Get Email by Domain, Firstname and Lastname" tool to discover a professional email address, and then sends that email to a Telegram channel. > ⚠️ Note: You must set up your *uProc credentials (Email + API Key)* from the *Integration settings* before running this workflow. 🚀 What It Does Uses user-provided data: first name, last name, and company domain Calls uProc to discover the most likely email address for that person Sends the discovered email and confidence level to a Telegram group 🛠️ Step-by-Step Setup Add uProc Credentials Go to the uProc integration page and copy your email and API key. Add them as credentials in your n8n instance. Set Tool Parameters Use the Set node to define: firstname: First name of the person lastname: Last name of the person domain: Their company domain Replace the Set Node (Optional) You can dynamically fetch the firstname, lastname, and domain from other sources like: Google Sheets MySQL or Postgres Webhook or Form submissions Run the Workflow Trigger the flow manually or integrate it with a larger automation. 🔍 uProc Parameters Explained domain**: The company domain (e.g., uproc.io) firstname**: First name of the person lastname** (in parameter: language): Last name of the person mode**: verify: Verifies email in real-time with mail server guess: Guesses based on company format (e.g., firstname.lastname@domain.com) 📦 uProc Response Fields email: Discovered email address confidence: Indicates if the result is verified or risky (e.g., catch-all) score: Reliability score from 0 (unreliable) to 99 (highly reliable) 📬 Notification via Telegram After discovering the email, the result is sent to a specified Telegram channel with this format: User Miquel Colomer has next email on uproc.io: contact@uproc.io (verified - 99) Clicking the email allows you to send a message directly to the recipient. 🔐 Credentials Used uProc API** – For discovering email addresses Telegram API** – To send messages to a specific group/channel ✨ Customization Tips Loop over a list of people**: Replace the set node with a data source that contains multiple people. Filter by score or confidence** before sending. Add additional outputs**: You can send the data via Email, Slack, or save it to a database. Trigger automatically**: Combine with a webhook or time-based trigger for automation. ❓Questions? Template created by Miquel Colomer and n8nhackers.com. Need help customizing or deploying? Contact us for consulting and support.

Description This automation template is designed for content creators, social media managers, and influencers who want to streamline their video publishing workflow. It automatically detects new videos uploaded to a specific Google Drive folder, generates AI-powered descriptions based on video audio content, and simultaneously publishes them across Instagram, TikTok, and YouTube while tracking everything in Airtable. Note: This workflow uses upload-post.com API (free trial no credit card required) for multi-platform video distribution and requires API tokens for each service. The AI-generated descriptions are created using OpenAI's transcription and chat models to analyze video audio content.* Who Is This For? Content Creators & Influencers:** Automatically publish your videos across all major social platforms without manual work. Social Media Managers:** Maintain consistent posting schedules across multiple platforms with AI-generated, platform-optimized descriptions. Marketing Teams:** Scale video content distribution with automated workflows that include tracking and status monitoring. Video Producers:** Focus on creating content while the system handles the tedious task of multi-platform publishing and description generation. What Problem Does This Workflow Solve? Publishing the same video content across Instagram, TikTok, and YouTube is time-consuming and repetitive. You need to manually upload each video, write unique descriptions, and track publication status. This workflow addresses these challenges by: Automated Video Distribution:** Detects new videos in Google Drive and automatically uploads them to all three platforms simultaneously. AI-Powered Content Generation:** Uses OpenAI to transcribe video audio and generate engaging, platform-appropriate descriptions automatically. Centralized Tracking:** Maintains detailed records in Airtable including upload status, URLs, and metadata for each platform. Error Monitoring:** Provides real-time error notifications via Telegram to ensure you're always aware of any issues. How It Works Video Upload Detection: The workflow monitors a specific Google Drive folder for new video uploads using automated triggers. Content Analysis: Downloads the video, extracts audio, and uses OpenAI to transcribe and generate compelling descriptions. Airtable Integration: Creates and updates records to track video metadata, descriptions, and publication status. Multi-Platform Publishing: Simultaneously uploads the video to Instagram, TikTok, and YouTube using the upload-post.com API. Status Tracking: Updates Airtable records with publication status and platform-specific URLs for each successful upload. Setup Google Drive Configuration: Set up the Google Drive trigger to monitor your specific folder Configure OAuth2 credentials for Google Drive access OpenAI Integration: Add your OpenAI API key to enable audio transcription and description generation Airtable Setup: Create an Airtable base with fields for Video Name, Description, Platform Status, URLs, and Upload Date Add your Airtable API token and configure base/table IDs in the "Set Variables" node Upload-Post.com Account: Create an account at upload-post.com to get your API token Configure the token in the HTTP request nodes for each platform Set your user ID in the variables section Platform Accounts: Ensure your Instagram, TikTok, and YouTube accounts are connected to upload-post.com Error Notifications: (Optional) Configure Telegram bot credentials for error notifications Requirements Accounts:** Google Drive, OpenAI, Airtable, upload-post.com, Telegram (optional) API Keys & Credentials:** Google Drive OAuth2, OpenAI API Key, Airtable API Token, upload-post.com API Token Platform Setup:** Instagram, TikTok, and YouTube accounts connected to upload-post.com Transform your video publishing workflow from hours of manual work to a fully automated system that handles everything from content analysis to multi-platform distribution and tracking.

Build a Weekly AI Trend Alerter with arXiv and Weaviate Ditch the endless scroll for AI trends. Meet Archi, your personal AI research assistant that hits you up once a week with everyone you need to know. 🧑🏽‍🔬 This workflow scrapes AI and machine learning article abstracts from arXiv, enriches them with topic categories using a LLM, and embeds them in a Weaviate vector store. The vector store is then used as a tool for agentic RAG to write a concise, easy-to-read summary of the week in AI research. The final output is a short, weekly email sent to the address of your choice that summarizes key AI research trends and future research directions, with links directly to the most interesting and impactful arXiv papers of the week. Who it's for This workflow is for anyone who can't keep up with all the latest AI advances. Coding skills are not required. How it works This is a contiguous workflow that can be summarized in two main parts: a data pipeline that fetches and embeds articles in Weaviate, and an agentic workflow that generates a weekly email summary. Part 1: Automatically fetch newly published articles on a weekly basis Fetch article abstracts (and metadata) from arXiv's free API Pre-process abstract data Enrich each article with a primary topic, secondary topics, and estimated potential impact of the research using a LLM Post-process data Insert data and embeddings into Weaviate Part 2: Use an AI Agent and Weaviate to generate a weekly summary email Add Weaviate as a Tool to an AI agent node Query Weaviate, agentically, to generate a report on the most important research trends of the week Post-process data Send the summary via email Prerequisites An existing Weaviate cluster. You can view instructions for setting up a local cluster with Docker here or a Weaviate Cloud cluster here. API keys to generate embeddings and power chat models. We use a combination of OpenRouter and OpenAI models. Feel free to switch out the models as you like. An email address with STMP privileges. This is the address the email will come from. In this demo we use a personal Gmail address. You can create a new credential to link a STMP Account using these instructions. Self-hosted n8n instance. See this video for how to get set up in just three minutes. How to run the workflow Go through the prerequisites, creating a Weaviate cluster (can be local or cloud), downloading self-hosted n8n, creating STMP privileges for your email account, and adding your API keys and other credentials. Select the embedding and chat models you'd like to use. Enter the email addresses you want to send the email from and to. Let it rip. Workflow output The output for this workflow is a weekly email that summarizes key research trends and future research directions based on AI and ML papers published on arXiv. Here's an example of a summary email: Hey there, Here's a quick rundown of the key trends in Machine Learning research from the past week. * Key Research Trends This Week* This week saw significant advancements in retrieval-augmented systems, foundation models for specialized domains, and techniques balancing efficiency with performance. Advanced RAG Architectures**: Researchers are developing sophisticated RAG frameworks that go beyond simple document retrieval, with AdaPCR introducing passage combination retrieval and UrbanMind proposing a framework for urban intelligence with multilevel optimization. Foundation Models for Tabular Data**: The Real-TabPFN shows that targeted continued pre-training on real-world datasets can significantly boost the performance of foundation models for tabular data, outperforming models trained on broader, potentially noisier datasets. Efficiency-Focused Techniques**: Researchers are developing resourceful methods that maintain performance without expensive computations, like logit reweighting for topic-focused summarization and strategic querying for privacy-preserving personalization. * Future Research Directions* Based on current trends, we expect to see the following developments in the near future: Explainable RAG Systems**: Following the source attribution work in RAG systems, we can expect more research into making complex retrieval systems transparent and explainable for users. Cross-Domain and Cross-Modal Fusion**: The promising performance of vision-language and code-specialized LLMs in retrieval tasks points toward unified retrievers capable of handling text, code, images, and multimodal content. Data-Centric Synthetic Generation**: As shown by work on synthetic relational tabular data, we'll likely see more sophisticated approaches to generating high-quality synthetic data for pre-training foundation models in specialized domains. This week highlights how researchers are making AI more efficient, explainable, and applicable to specialized domains. Look out for more developments in RAG systems, tabular foundation models, and privacy-preserving AI techniques in the coming weeks. Until next week, Archi Want to make it better? Feel free to tweak, build on, or completely reconfigure this workflow. If you come up with something cool, let us know and we might just share it with our community! 💚

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 This workflow automates the collection and analysis of YouTube comments from a video and sends a summary report via email, using Google Sheets, the YouTube API, OpenAI (GPT-4o), and Gmail. Whether you're a content creator, brand manager, or social media analyst, this workflow helps you automate sentiment analysis and receive insights directly in your inbox — all triggered from a simple spreadsheet. 🎯 Use Case Ideal for: YouTubers** monitoring audience sentiment Marketing teams** analyzing campaign feedback Community managers** summarizing engagement Setup Instructions 1. Upload the Spreadsheet File name: Youtube_Video Sheet structure: | ID | Video Title | YouTube Video ID | Status | Add video IDs and set their Status as Pending 2. Configure Google Sheets Nodes Connect your Google account to: Pick Video IDs from Google Sheet Update Status on Google Sheet 3. Add API Credentials YouTube API Key** → for comment + video scraping nodes OpenAI API Key** → for analyzing comments Gmail Account** → for sending the summary email 4. Activate the Workflow Once live, the workflow will: Watch for new or updated rows in the spreadsheet Scrape comments using the YouTube API Analyze sentiment and key themes via GPT-4o Send a formatted HTML email with the summary Update the spreadsheet status to Mail sent 🔁 Workflow Logic Trigger: New/updated row in Google Sheet Retrieve: YouTube video metadata + comments Analyze: Comments using GPT-4o Email: Summary report via Gmail Update: Spreadsheet status to Mail sent 🧩 Node Descriptions | Node Name | Description | |-----------|-------------| | Pick Video IDs from Google Sheet | Watches the spreadsheet and retrieves pending video IDs | | If | Checks whether status is 'Pending' | | Limit | Restricts the number of processed rows | | Set Video Details | Prepares video info (e.g., title, channel) | | Get YouTube Video Details | Fetches metadata (title, channel, etc.) | | Get YouTube Video Comments | Pulls top-level comments using YouTube API | | Prepare Comments Data | Formats comment text for OpenAI | | AI Agent | Summarizes comments using OpenAI's GPT-4o | | Prepare HTML for Email | Converts summary into HTML for email body | | Gmail Account Configuration | Sends the email report via Gmail | | Update Status on Google Sheet | Marks the row as 'Mail sent' | 🛠️ Customization Tips Change the AI prompt for tone, length, or custom metrics Send results to Slack or Telegram instead of Gmail Export summaries to Notion, Airtable, or PDF Schedule it daily/weekly for recurring analysis 📒 Suggested Sticky Notes for Workflow | Node/Section | Sticky Note Content | |--------------|---------------------| | Pick Video IDs from Google Sheet | "Triggers on new YouTube videos in your spreadsheet" | | AI Agent | "Uses OpenAI to generate an analysis summary – customize prompt as needed" | | Gmail | "Sends summary report – you can update subject, recipients, or style" | | Update Status | "Marks video as processed to avoid duplicate runs" | 📎 Required Files | File Name | Purpose | |-----------|---------| | Youtube_Video | Google Sheet to hold YouTube video IDs and status | | Youtube_Comment_Scraper.json | Main n8n workflow export for this automation | 🧪 Testing Tips Add one test video with a valid YouTube video ID and status = Pending Monitor the workflow logs to confirm API responses Confirm summary delivery in your inbox Verify that status updates in the sheet 🏷 Suggested Tags & Categories #YouTube #OpenAI #Automation #Marketing #Email #Analytics

This n8n template captures every “Request a Demo” booking in Calendly, uses OpenAI to score and qualify leads in real time, routes them into the correct Saleshandy sequence, and logs all data in Google Sheets for full GTM visibility. Use cases include: Empowering SDR teams to focus on high-value demos Providing growth marketers with reliable funnel metrics Automating triage for B2B AE teams overwhelmed by demo requests Good to know OpenAI GPT-4 calls cost based on token usage—you can expect ~1,200 tokens per lead. Calendly API rate-limits at 180 requests/min; consider batching if volume spikes. Google Sheets writes are single-threaded; high-volume users may opt for Airtable or BigQuery. How it works Capture – Webhook node listens for every new “Request a Demo” form submission in Calendly. Score – AI Agent node sends job title, company size, domain quality, and custom questions to OpenAI; returns a 1–10 score plus label (Qualified/Semi-qualified/Unqualified). Verify meeting – HTTP Request node confirms via the Calendly API that a slot was actually scheduled. Route – Switch node selects the appropriate Saleshandy sequence ID (Qualified, Nurture, Disqualify). Send – HTTP Request nodes add each prospect to the chosen Saleshandy sequence. Log – Google Sheets nodes write to three tabs (Qualified, Semi-qualified, Unqualified) with lead data, score, routing path, and timestamp. Prerequisites n8n workspace Accounts & API credentials for: Calendly OpenAI (GPT-4 or GPT-3.5) Google Sheets Saleshandy Step-by-Step Setup 1. Import the n8n Template Upload the JSON file into your n8n workspace. 2. Add Required Credentials In n8n → Credentials, add: Calendly: Personal Access Token (PAT) OpenAI: API Key Google Sheets: OAuth2 connection Saleshandy: API Key 3. Calendly Setup Go to Calendly Webhook Docs Create a Routing Form in Calendly. Generate your access token. Use Postman or any API client to: Make a POST request to create a webhook subscription. Use your n8n webhook URL in the url field. Add your Authorization token and extract the Organization ID. Paste the webhook URL into the Calendly Routing Form. 4. Set Your Saleshandy Sequences In n8n, locate the Set: Sequence IDs node. Replace the placeholder text with: Your actual Qualified Semi-qualified and Unqualified Saleshandy sequence step IDs. 5. Configure Google Sheets Create a spreadsheet with the following tabs: Qualified Semi-qualified Unqualified In n8n, connect the three Google Sheets nodes to this file. Customising this workflow Adjust scoring logic – Modify the OpenAI prompt in the AI Agent node to weight ARR, industry, or headcount differently. Refine thresholds – Change the Switch node rules for score ranges (e.g., Qualified ≥8, Semi-qualified 5–7). Swap destinations – Edit HTTP Request nodes to integrate with your CRM or email platform instead of Saleshandy. Enhance logging – Replace Google Sheets with Airtable, BigQuery, or another analytics store. Add notifications – Insert Slack or Microsoft Teams nodes after routing to alert reps instantly.

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 workflow tracks week-over-week changes in Google Search Console performance and highlights the top movers across keyword segments like brand, nonbrand, and content categories. Instead of providing a routine check, it focuses on significant movements by: Sending a Slack alert only if a query crosses a defined movement threshold. Emailing a structured report with the Top 25 increases and Top 25 decreases for clicks, including % changes and linked URLs It’s designed to surface the most important shifts, helping SEO teams catch big wins, losses, or anomalies early. How it works Runs weekly (e.g. every Monday) to compare last week’s GSC data to the week prior. Segments traffic based on query and page (e.g. brand terms, category page URLs, etc.). Calculates delta and % change for clicks, CTR, impressions, and position. Filters and flags top movers with large shifts (default: ±200 clicks and ±30%). Sends Slack alerts only if meaningful changes are detected. Emails a full HTML table report showing the Top 25 up/down queries per segment. Setup steps Requires a connected Google Search Console account. Slack alert is included by default (can be replaced with email, webhook, or other tools). Customize your brand terms and URL filters to match your segments (e.g. recipes, blog, category pages). Typical setup time: 15–25 minutes depending on the number of segments and filters you want. Note: “Recipes” is used in the example to show how to segment by content type. You can update this to reflect your own site’s structure.