by Ranjan Dailata
Notice Community nodes can only be installed on self-hosted instances of n8n. Who this is for The DNB Company Search & Extract workflow is designed for professionals who need to gather structured business intelligence from Dun & Bradstreet (DNB). It is ideal for: Market Researchers B2B Sales & Lead Generation Experts Business Analysts Investment Analysts AI Developers Building Financial Knowledge Graphs What problem is this workflow solving? Gathering business information from the DNB website usually involves manual browsing, copying company details, and organizing them in spreadsheets. This workflow automates the entire data collection pipeline — from searching DNB via Google, scraping relevant pages, to structuring the data and saving it in usable formats. What this workflow does This workflow performs automated search, scraping, and structured extraction of DNB company profiles using Bright Data’s MCP search agents and OpenAI’s 4o mini model. Here's what it includes: Set Input Fields: Provide search_query and webhook_notification_url. Bright Data MCP Client (Search): Performs Google search for the DNB company URL. Markdown Scrape from DNB: Scrapes the company page using Bright Data and returns it as markdown. OpenAI LLM Extraction: Transforms markdown into clean structured data. Extracts business information (company name, size, address, industry, etc.) Webhook Notification: Sends structured response to your provided webhook. Save to Disk: Persists the structured data locally for logging or auditing. Pre-conditions Knowledge of Model Context Protocol (MCP) is highly essential. Please read this blog post - model-context-protocol You need to have the Bright Data account and do the necessary setup as mentioned in the Setup section below. You need to have the Google Gemini API Key. Visit Google AI Studio You need to install the Bright Data MCP Server @brightdata/mcp You need to install the n8n-nodes-mcp Setup Please make sure to setup n8n locally with MCP Servers by navigating to n8n-nodes-mcp Please make sure to install the Bright Data MCP Server @brightdata/mcp on your local machine. Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. Create a Web Unlocker proxy zone called mcp_unlocker on Bright Data control panel. In n8n, configure the OpenAi account credentials. In n8n, configure the credentials to connect with MCP Client (STDIO) account with the Bright Data MCP Server as shown below. Make sure to copy the Bright Data API_TOKEN within the Environments textbox above as API_TOKEN=<your-token>. Update the Set input fields for search_query and webhook_notification_url. Update the file name and path to persist on disk. How to customize this workflow to your needs Search Engine**: Default is Google, but you can change the MCP client engine to Bing, or Yandex if needed. Company Scope**: Modify search query logic for niche filtering, e.g., "biotech startups site:dnb.com". Structured Fields**: Customize the LLM prompt to extract additional fields like CEO name, revenue, or ratings. Integrations**: Push output to Notion, Airtable, or CRMs like HubSpot using additional n8n nodes. Formatting**: Convert output to PDF or CSV using built-in File and Spreadsheet nodes.
by InfyOm Technologies
✅ What problem does this workflow solve? Automatically monitor multiple websites every 5 minutes, log downtime, notify your team instantly via multiple channels, and track uptime/downtime in a Google Sheet—without relying on expensive monitoring tools. ⚙️ What does this workflow do? Triggers every 5 minutes to monitor website health. Fetches a list of website URLs from a Google Sheet. Checks the status of each website one by one. Sends instant alerts if a website is down (Email, Slack, Telegram, Voice Call). Logs downtime events in Google Sheets. Tracks when websites are back up and updates the log. Sends recovery notifications when a site is live again (Email, Slack, Telegram). 🔧 Setup 📄 Google Sheets Setup Sheet 1: List of website URLs to monitor. Sheet 2: Log to store uptime/downtime records. Sample Format: https://docs.google.com/spreadsheets/d/1_VVpkIvpYQigw5q0KmPXUAC2aV2rk1nRQLQZ7YK2KwY/edit?usp=sharing ✉️ Gmail, Slack & Telegram Setup Connect Gmail, Slack, and Telegram to n8n. Configure each service with proper credentials or OAuth. 📞 Vapi (Voice Call) Setup Create a Vapi account. Generate an API key. Configure API Parameters (vapi_api_key, assistant_id, number, phone_number_id) on VAPI Node. Insert the First Message specified in the Workflow. 🧠 How it Works ⏱ 1. Scheduled Monitoring A Schedule Trigger runs the workflow every 5 minutes. It reads the list of URLs from the Google Sheet and loops through each one. 🌍 2. Website Health Check Each website is pinged to check if it’s online. 🔴 3. If Website is Down: It verifies if a downtime record already exists. If not, it: Adds a new row in the Google Sheet with the timestamp. Sends notifications via: 📧 Email 💬 Slack 📲 Telegram 📞 Voice Call via Vapi 🟢 4. If Website is Back Up: It fetches the matching downtime record. Updates the sheet with: ✅ Uptime timestamp ⏱ Total downtime duration Sends recovery notifications via: 📧 Email 💬 Slack 📲 Telegram (No phone call is made for uptime.) 👤 Who can use it? This is perfect for: 🚀 Startups 👨💻 Freelance Developers 🛠 SaaS Product Owners 🖥 IT/DevOps Teams If you're looking to replace tools like UptimeRobot, Pingdom, or StatusCake, this no-code solution gives you full control, customization, and cost-efficiency.
by Cecilia
Enable smart, real-time answers in your WhatsApp groups using a custom webhook, Pinecone vector database, and no Facebook Business setup. > 🟡 Note: This template uses a custom WhatsApp webhook. It does not use the official WhatsApp Business API. 👥 Who is this for? This workflow is designed for individuals and teams who want to enable smart WhatsApp group automation — without going through Meta’s official WhatsApp Business API. Ideal for small businesses, internal teams, communities, and personal power users. ❓ What problem is this solving? Setting up WhatsApp bots with intelligent responses often requires approval from Meta and a verified business account. This workflow removes those barriers by using a self-hosted webhook to handle incoming messages and respond using a document-trained AI via Pinecone. ⚙️ What this workflow does Connects a regular WhatsApp number to a custom webhook Adds the bot to any group chat (it stays silent unless mentioned) Indexes documents from Google Drive into Pinecone Responds with intelligent, context-aware answers from your custom knowledge base Auto-updates its knowledge every minute as the document changes 🛠️ Setup Step 1: Connect Google Drive Set up your Google Drive credentials in n8n Step 2: Configure Pinecone Create an index in Pinecone Dimension: 1536 Select this index in both Pinecone nodes Click Test Workflow to ingest your document into Pinecone Step 3: Get Access to the WhatsApp Webhook Fill out this form to request access You’ll receive a WhatsApp confirmation for linking Step 4: Test WhatsApp Integration ✅ One-on-one test: Send a message from another number 👥 Group test: Add the bot to a group; it will only respond when tagged 🧩 How to customize this workflow Modify the system prompt inside the AI agent node to control tone and behavior Update the connected Google Doc to match your specific domain (e.g. FAQs, SOPs, product manuals) Adjust the Pinecone sync frequency if you want updates more or less often 📚 Use cases Customer Support**: Instant, intelligent replies in WhatsApp without live agents Team Knowledge Bot**: Tag the bot for quick access to SOPs and internal docs Community Groups**: Automate common questions while keeping noise low Personal AI Assistant**: A WhatsApp chatbot trained on your notes and files 📝 Sticky Note Suggestion 💬 What this template does: > Enables an AI bot in your WhatsApp group that answers questions based on a Google Doc you provide. It uses a custom webhook, Google Drive, and Pinecone. 🔧 Requirements: > Google Drive account > Pinecone account with an index (dimension 1536) > Access to the custom WhatsApp webhook (see setup steps)
by KPendic
How it works This workflow simply exports all your CloudFlare domains to Google Sheet to get high overview of all of your settings. This could help for easy debugging, searching or similar needs. In flow simple pagging nodes are used to iterate over all your domains, because this list could be huge. For each host we are merging DNS & Settings and transforming them into columns for all our domains. Requirements For storing and processing of data in this flow you will need: CloudFlare.com API key/token - for retrieving your data (https://dash.cloudflare.com/:account/api-tokens) (need full access) Google Spreadsheet auth connected in your n8n Credentials Google Spreadsheet template - you can copy my sheet as starting point, start by copying it to your account Match Sheet ID in 'Export' node to your newly created. Official CloudFlare api Documentation For full details and specifications please use API documentation from: https://developers.cloudflare.com/api/ Potential API timeouts If you encounter CF API timeouts - I would suggest to only put somewhere in the loop simple sleep/wait node - for couple of seconds - and it should resolve timeouts. Google Sheet I've used simple Google Sheet feature conditional formatting to visually distinct my on|off toggles that was of my interest to easily get high overview for debuggint some of the settings on my hosts - but please use your own logic or change it completely.
by Praveena
Why Teachers now spend 3-4 hours per lesson creating materials and resources from scratch. With additional/special needs, this makes it difficult to create additional materials. This is unsustainable and takes their time away from teaching. Tailored for UK teachers but can be expanded globally with prompt and form enhancements. How it works I built a system with three specialized AI agents that create complete lesson packages and automatically uploads a document in Google drive and puts an appointment in calendar to review the document. Features Research agent to pull specific information including special education needs and curriculums. The scoring and assessment agent to generate tailored assessment plans, assignments, grading mechanism based on chosen requirements. The integration agent just provides ideas to expand to other tools. In nfuture there is opportunity to add on Kahoot or other tools to create quizzes. Finally the enriched document is emailed and a calendar invite is sent for review. What you need N8N Any LLM API Key (I used OpenAI) Google drive integration Google calendar integration Modify the email id from XXX@gmail.com to your Email id in email component. Support Watch this video for intro on how it works. Contact me on info@pankstr.com for any queries.
by Dr. Firas
AI-powered WhatsApp booking system with instant SMS confirmations Who is this for? This workflow is designed for solo entrepreneurs, consultants, coaches, clinics, or any business that handles client appointments and wants to automate the entire scheduling experience via WhatsApp — without the need for live agents. What problem is this workflow solving? Responding to inbound messages, collecting booking details, suggesting available times, and sending reminders can be a huge time drain. This workflow eliminates manual handling by: Automating WhatsApp conversations with an AI assistant Booking appointments directly into Cal.com Sending timely SMS reminders before appointments It ensures you never miss a lead or a follow-up — even while you sleep. What this workflow does From a single WhatsApp message, the workflow: Triggers via a WhatsApp webhook Uses GPT-4 to handle conversation flow and qualify the prospect Collects name, email, selected service Calls Cal.com API to fetch available time slots Books the appointment and stores it in Google Sheets Sends a confirmation message via WhatsApp Periodically scans for upcoming appointments Sends SMS reminders to clients 2 hours before their session Setup Connect your Webhook node to a WhatsApp API (e.g., 360dialog, Twilio, or Ultramsg) Add your OpenAI API key for the GPT-4 nodes Configure your Cal.com API key and set your calendar ID Link your Google Sheets with fields like: name, email, date, time, status, reminder_sent Connect your SMS service (e.g., sms77) with API credentials Adjust the schedule in the reminder node as needed How to customize this workflow to your needs Change the language or tone of the AI assistant** by editing the system prompt in the GPT node Filter available time slots** by service, team member, or duration Modify the reminder timing** (e.g., 1 hour before, 24h before, etc.) Add conditional logic** to route users to different booking flows based on their responses Integrate additional CRMs** or notification channels like email or Slack 📄 Documentation: Notion Guide Need help customizing? Contact me for consulting and support : Linkedin / Youtube
by Jimleuk
This n8n template demonstrates one approach to achieve a more natural and less frustration conversations with AI agents by reducing interrupts by predicting the end of user utterances. When we text or chat casually, it's not uncommon to break our sentences over multiple messages or when it comes to voice, break our speech with the odd pause or umms and ahhs. If an agent replies to every message, it's likely to interrupt us before we finish our thoughts and it can get very annoying! Previously, I demonstrated a simple technique for buffering each incoming message by 5 seconds but that approach still suffers in some scenarios when more time is needed. This technique has no arbitrary time limit and instead uses AI to figure out when its the agent's turn based on the user's message, allowing for the user to take all the time they need. How it works Telegram messages are received but no reply is generated for them by default. Instead they are sent to the prediction subworkflow to determine if a reply should be generated. The prediction subworkflow begins by checking Redis for the current user's prediction session state. If this is a new "utterance", it kicks off the "predict end of utterance" loop - the purpose of which is to buffer messages in a smart way! New users message can continue to be accepted by the workflow until enough is collected to allow our prediction classifier to determine the end of the utterance has been reached. The loop is then broken and the buffered chat messages are combined and sent to the AI agent to generate a response and sent to the user via the telegram node. The prediction session state is then deleted to signal the workflow is ready to start again with a new message. How to use This system sits between your preferred chat platform and the AI agent so all you need to do is replace the telegram nodes as required. Where LLM-only prediction isn't working well enough, consider more traditional code-based checking of heuristics to improve the detection. Ideally you'll want a fast but accurate LLM so your user isn't waiting longer than they have to - at time of writing Gemini-2.5-flash-lite was the fastest in testing but keep a look out for smaller and more powerful LLMs in the future. Requirements Gemini for LLM Redis for session management Telegram for chat platform
by Incrementors
🛒 Google Maps Business Phone Number Scraper Using Bright Data API & Google Sheets Integration This template requires a self-hosted n8n instance to run. An automated workflow that extracts business information including phone numbers from Google Maps using Bright Data's API and saves the data to Google Sheets for easy access and analysis. 📋 Overview This workflow provides an automated solution for extracting business contact information from Google Maps based on location and keyword searches. Perfect for lead generation, market research, competitor analysis, and business directory creation. ✨ Key Features 🎯 Form-Based Input: Easy-to-use form for location and keyword submission 🗺️ Google Maps Integration: Uses Bright Data's Google Maps dataset for accurate business data 📊 Comprehensive Data Extraction: Extracts business names, addresses, phone numbers, ratings, and more 📧 Automated Processing: Handles the entire scraping process automatically 📈 Google Sheets Storage: Automatically saves extracted data to organized spreadsheets 🔄 Smart Status Checking: Monitors scraping progress with automatic retry logic ⚡ Fast & Reliable: Professional scraping with built-in error handling 🎯 Customizable Output: Configurable data fields for specific business needs 🎯 What This Workflow Does Input Location:** Geographic area to search (city, state, country) Keywords:** Business type or industry keywords Processing Form Submission: User submits location and keywords through web form API Request: Sends scraping request to Bright Data's Google Maps dataset Status Monitoring: Continuously checks scraping progress Data Retrieval: Fetches completed business data when ready Data Storage: Saves extracted information to Google Sheets Error Handling: Implements retry logic for failed requests Output Data Points | Field | Description | Example | |-------|-------------|---------| | Business Name | Official business name from Google Maps | "Joe's Pizza Restaurant" | | Phone Number | Contact phone number | "+1-555-123-4567" | | Address | Complete business address | "123 Main St, New York, NY 10001" | | Rating | Google Maps rating score | 4.5 | | URL | Google Maps listing URL | "https://maps.google.com/..." | 🚀 Setup Instructions Prerequisites n8n instance (self-hosted or cloud) Google account with Sheets access Bright Data account with Google Maps dataset access 5-10 minutes for setup Step 1: Import the Workflow Copy the JSON workflow code from the provided file In n8n: Workflows → + Add workflow → Import from JSON Paste JSON and click Import Step 2: Configure Bright Data Set up Bright Data credentials: In n8n: Credentials → + Add credential → HTTP Request Auth Enter your Bright Data API key Test the connection Configure dataset: Ensure you have access to Google Maps dataset (gd_m8ebnr0q2qlklc02fz) Verify dataset permissions in Bright Data dashboard Step 3: Configure Google Sheets Integration Create a Google Sheet: Go to Google Sheets Create a new spreadsheet named "Business Data" or similar Copy the Sheet ID from URL: https://docs.google.com/spreadsheets/d/SHEET_ID_HERE/edit Set up Google Sheets credentials: In n8n: Credentials → + Add credential → Google Sheets OAuth2 API Complete OAuth setup and test connection Prepare your data sheet with columns: Column A: Name Column B: Address Column C: Rating Column D: Phone Number Column E: URL Step 4: Update Workflow Settings Update Google Sheets node: Open "Save to Google Sheets" node Replace the document ID with your Sheet ID Select your Google Sheets credential Choose the correct sheet/tab name Update Bright Data nodes: Open HTTP Request nodes Replace BRIGHT_DATA_API_KEY with your actual API key Verify dataset ID matches your subscription Step 5: Test & Activate Test the workflow: Activate workflow (toggle switch) Submit test form with location: "New York" and keywords: "restaurants" Verify data appears in Google Sheet Check for proper phone number extraction 📖 Usage Guide Submitting Search Requests Access the form URL provided by n8n Enter the desired location (city, state, or country) Enter relevant keywords (business type, industry, etc.) Submit the form and wait for processing Understanding the Results Your Google Sheet will populate with business data including: Complete business contact information Verified phone numbers from Google Maps Accurate addresses and ratings Direct links to Google Maps listings 🔧 Customization Options Adding More Data Points Edit the "Bright Data API - Request Business Data" node to capture additional fields: Business descriptions Operating hours Reviews count Website URLs Photos and videos Modifying Search Parameters Customize the search behavior: Adjust "limit_per_input" for more or fewer results Modify search type and discovery method Add geographical coordinates for precise targeting 🚨 Troubleshooting Common Issues & Solutions 1. "Bright Data connection failed" Cause:** Invalid API credentials or dataset access Solution:** Verify credentials in Bright Data dashboard, check dataset permissions 2. "No business data extracted" Cause:** Invalid search parameters or no results found Solution:** Try broader keywords or different locations, verify dataset availability 3. "Google Sheets permission denied" Cause:** Incorrect credentials or sheet permissions Solution:** Re-authenticate Google Sheets, check sheet sharing settings 4. "Workflow execution timeout" Cause:** Large search results or slow API response Solution:** Reduce search scope, increase timeout settings, check internet connection 📊 Use Cases & Examples 1. Lead Generation Goal:** Find potential customers in specific areas Search for businesses by industry and location Extract contact information for outreach campaigns Build targeted prospect lists 2. Market Research Goal:** Analyze local business landscape Study competitor density in target markets Identify market gaps and opportunities Gather business intelligence for strategic planning 3. Directory Creation Goal:** Build comprehensive business directories Create industry-specific business listings Maintain updated contact databases Support local business communities 📈 Performance & Limits Expected Performance Processing time:** 1-5 minutes per search depending on results Data accuracy:** 95%+ for active Google Maps listings Success rate:** 90%+ for accessible businesses Concurrent requests:** Depends on Bright Data plan limits Resource Usage Memory:** ~50MB per execution Storage:** Minimal (data stored in Google Sheets) API calls:** 2-3 Bright Data calls + 1 Google Sheets call per search Bandwidth:** ~1-2MB per search request Execution time:** 2-5 minutes for typical searches Scaling Considerations Rate limiting:** Respect Bright Data API limits Error handling:** Implement retry logic for failed requests Data validation:** Add checks for incomplete business data Cost optimization:** Monitor API usage to control expenses Batch processing:** Group multiple searches for efficiency 🤝 Support & Community Getting Help n8n Community Forum:** community.n8n.io Documentation:** docs.n8n.io Bright Data Support:** Contact through your dashboard GitHub Issues:** Report bugs and feature requests Contributing Share improvements with the community Report issues and suggest enhancements Create variations for specific use cases Document best practices and lessons learned 🎯 Ready to Use! This workflow provides a solid foundation for automated Google Maps business data extraction. Customize it to fit your specific needs and use cases. Your workflow URL: https://your-n8n-instance.com/workflow/google-maps-scraper For any questions or support, please contact: info@incrementors.com or fill out this form: https://www.incrementors.com/contact-us/
by Anurag Srivastava
🧠 AI Prompt Generator Workflow – n8n Documentation Who is this for? This workflow is for AI builders, prompt engineers, developers, marketers, and no-code creators who want to convert rough user input into structured, high-quality prompts for LLMs. It’s especially useful for tools that rely on precision prompting and want to automate the discovery of intent and constraints. What problem is this workflow solving? / Use case Many users struggle to write effective prompts due to vague ideas or unclear formatting needs. This workflow: Collects structured user input. Dynamically generates clarifying questions. Returns a well-formatted AI prompt based on the user's intent and context. This ensures the generated prompt is useful for downstream AI agents without requiring technical understanding from the end user. What this workflow does Start with a branded form UI The user is shown a styled form with questions like: What do you want to build? What tools can you access? What input can be expected? What output do you expect? Analyze and generate relevant follow-up questions The workflow sends the user's answers to Google Gemini (via LangChain) which outputs 1–3 clarifying questions. These questions are parsed into a dynamic form. Loop through and collect follow-up answers Each follow-up question is shown in a form one at a time to capture additional context. Merge all inputs The base intent and follow-up responses are merged into a single context block. Generate a final AI-ready prompt The prompt generator node formats everything into a clean, six-section structure: <constraints> <role> <inputs> <tools> <instructions> <conclusions> Display the final result The finished prompt is shown in a clean UI where users can easily copy and reuse it. Setup Credentials Required Google Gemini (PaLM) API credentials (already integrated as Google Gemini(PaLM) Api account 2). Form Trigger Ensure the On form submission trigger is exposed via a webhook or public endpoint (e.g. using ngrok or deployed server). Styling Custom CSS is included in all form nodes for a beautiful UI. You can modify this to match your branding. Environment This workflow is compatible with self-hosted n8n or n8n.cloud. Webhooks must be accessible to users who will fill out the form. How to customize this workflow to your needs Change the base questions** Update the BaseQuestions form node to add or remove fields depending on your use case. Modify Gemini prompts** You can edit the system prompt inside PromptGenerator to change tone, output structure, or AI instructions. Change prompt formatting** If you use a different AI agent (like GPT, Claude, or Mistral), adjust the section labels and formatting to suit that agent’s expected input. Send results elsewhere** Add integration nodes after PromptGenerator, such as: Google Docs / Notion (to log prompts) Gmail / Slack (to notify your team) Zapier / Make (to push to other automation flows) Skip follow-up questions (optional)** If your base form collects all needed info, you can bypass the RelevantQuestions form section by modifying conditional logic. Example Output Prompt (Structure) <role> You are an AI assistant that converts videos into LinkedIn posts with a witty tone. </role> <inputs> - A short video (max 5 minutes) - Desired tone: witty - Style: both summary and quotes - Audience: general network </inputs> <tools> You do not have access to APIs or web search. </tools> <instructions> 1. Parse transcript. 2. Extract insights and quotes. 3. Write an engaging, witty LinkedIn post under 3000 characters. </instructions> <constraints> Avoid technical jargon. No generic intros. Make it platform-native. </constraints> <conclusions> Return a LinkedIn-ready post that starts with a hook and ends with hashtags.
by InfyOm Technologies
✅ What problem does this workflow solve? Shopify and E-Commerce store owners often struggle to create engaging 3D videos from static product images. This workflow automates that entire process—from image upload to video delivery—so store owners can get professional-looking 3D videos without any manual editing or follow-up. ⚙️ What does this workflow do? Accepts a 2D product image and name via a public n8n form. Generates a unique slug and folder in Google Drive for the product. Uploads the original image to Google Drive and logs data in a spreadsheet. Removes the background from the image using remove.bg API. Uploads the cleaned image to Google Drive and updates the spreadsheet. Creates a 3D product video using the cleaned image via the Fal.ai API. Periodically checks the video creation status. Once completed, download the video, upload it to Google Drive, and log the link. Notifies the store owner via email with the video download link. 🔧 Setup 🟢 Google Services Google Drive**: Create and connect a folder where all product assets will be stored. Google Spreadsheet**: A spreadsheet to log the product name, original image link, cleaned image link, and final video URL. Gmail**: Connect Gmail to send the final notification email to the store owner. 🔑 API Keys Required Remove.bg**: Get an API key from remove.bg. Fal.ai**: Sign up at fal.ai and obtain your API key to use the image-to-video generation service. 🧠 How it Works 📝 1. Product Form Submission A store owner submits the product name and 2D image via a public n8n form. 🗂 2. Organize in Google Drive A unique slug is generated for the product. A new folder is created inside Google Drive using that slug. The original image is uploaded into the folder. 📊 3. Record in a Spreadsheet The product name and original image URL are stored in a Google Sheet. 🧹 4. Background Removal The uploaded image is processed through remove.bg API to eliminate noisy or cluttered backgrounds. The cleaned image is uploaded back into the product’s Drive folder. The cleaned image link is updated in the spreadsheet. 🎥 5. Create 3D Video (via Fal.ai) The cleaned image is passed to the Fal.ai video generation API. The workflow periodically checks the status until the video is ready. ☁️ 6. Store Final Video Once the video is ready, the file is downloaded. The final video is uploaded into the same Google Drive folder. Its link is saved in the spreadsheet next to the respective product entry. 📧 7. Notify the Store Owner An automated email is sent to the store owner with the video link, letting them know it's ready for use—no waiting, no manual follow-up needed. 👤 Who can use it? This workflow is ideal for: 🛍 Shopify Sellers 🧺 E-commerce Store Owners 📸 Product Photographers 🎬 Marketing Teams 🤖 Automation Enthusiasts If you want to automate 3D product video creation using AI—this is the no-code workflow you’ve been waiting for!
by Anandkumar C
🛠 Website Downtime Monitoring with Scheduled Checks and Email Alerts Easily monitor your website uptime and receive instant email alerts when it becomes unreachable — using this no-code template powered by n8n, a free and flexible workflow automation tool. This ready-to-use workflow periodically checks your website’s status and sends an alert email if it’s down. ⚙️ How it Works Schedule Website Check** Triggers the workflow at regular intervals (e.g., every 8 hours by default). Check Website Status** Sends an HTTP GET request to your site. Evaluate Response** Determines if the site is reachable (expects HTTP status 200). Send Downtime Alert** If the site is down, an alert email is sent to the specified address. 🔧 Steps to Customize 1. HTTP Request Node Replace https://yourdomain.com with your actual website URL. 2. Send Email Node Update the To Email and From Email fields with your addresses. 3. Adjust Monitoring Frequency Modify the Schedule Trigger node to run every 5 minutes, hourly, or as needed. ✅ SMTP Configuration Instructions Before emails can be sent, you need to configure SMTP credentials in n8n. 📨 Option 1: Gmail SMTP Setup > Note: Gmail requires App Passwords (not your regular Gmail password) and 2FA to be enabled. Steps: Go to Google Account Security Settings. Enable 2-Step Verification. Go to App Passwords. Create a new app password (choose Mail and Other, name it n8n). In n8n: Go to Credentials → Create New → SMTP. Use the following values: Host: smtp.gmail.com Port: 465 (SSL) or 587 (TLS) User: your Gmail address (e.g., you@gmail.com) Password: the App Password you generated ✉️ Option 2: Generic SMTP Setup Use this if you're using your hosting provider's or business email SMTP server. Example Values: Host**: smtp.yourdomain.com or provider-specific (e.g., smtp.sendgrid.net) Port**: 587 (TLS) or 465 (SSL) User**: your email address (e.g., alerts@yourdomain.com) Password**: your email/SMTP password Secure**: Yes (if using 465 or TLS-enabled 587) Then in the workflow's Send Email node, select the SMTP credentials you created. 📌 Requirements A running instance of n8n (self-hosted or n8n.cloud) SMTP credentials configured in n8n for email delivery Basic familiarity with the n8n visual editor 🧠 Pro Tips Rename Nodes**: Use clear, descriptive names for maintainability. Sticky Notes**: Use stickies on the canvas to help explain logic for others. Expand Alerts**: Integrate with Slack, Discord, or Telegram for multi-channel alerts.
by Incrementors
Google Play Review Intelligence with Bright Data & Telegram Alerts Overview This n8n workflow automates the process of scraping Google Play Store reviews, analyzing app performance, and sending alerts for low-rated applications. It integrates with Bright Data for web scraping, Google Sheets for data storage, and Telegram for notifications. Workflow Components 1. ✅ Trigger Input Form Type:** Form Trigger Purpose:** Initiates the workflow with user input Input Fields:** URL (Google Play Store app URL) Number of reviews to fetch Function:** Captures user requirements to start the scraping process 2. 🚀 Start Scraping Request Type:** HTTP Request (POST) Purpose:** Sends scraping request to Bright Data API Endpoint:** https://api.brightdata.com/datasets/v3/trigger Parameters:** Dataset ID: gd_m6zagkt024uwvvwuyu Include errors: true Limit multiple results: 5 Custom Output Fields:** url, review_id, reviewer_name, review_date review_rating, review, app_url, app_title app_developer, app_images, app_rating app_number_of_reviews, app_what_new app_content_rating, app_country, num_of_reviews 3. 🔄 Check Scrape Status Type:** HTTP Request (GET) Purpose:** Monitors the progress of the scraping job Endpoint:** https://api.brightdata.com/datasets/v3/progress/{snapshot_id} Function:** Checks if the dataset scraping is complete 4. ⏱️ Wait for Response 45 sec Type:** Wait Node Purpose:** Implements polling mechanism Duration:** 45 seconds Function:** Pauses workflow before checking status again 5. 🧩 Verify Completion Type:** IF Condition Purpose:** Evaluates scraping completion status Condition:** status === "ready" Logic:** True: Proceeds to fetch data False: Loops back to status check 6. 📥 Fetch Scraped Data Type:** HTTP Request (GET) Purpose:** Retrieves the final scraped data Endpoint:** https://api.brightdata.com/datasets/v3/snapshot/{snapshot_id} Format:** JSON Function:** Downloads completed review and app data 7. 📊 Save to Google Sheet Type:** Google Sheets Node Purpose:** Stores scraped data for analysis Operation:** Append rows Target:** Specified Google Sheet document Data Mapping:** URL, Review ID, Reviewer Name, Review Date Review Rating, Review Text, App Rating App Number of Reviews, App What's New, App Country 8. ⚠️ Check Low Ratings Type:** IF Condition Purpose:** Identifies poor-performing apps Condition:** review_rating < 4 Logic:** True: Triggers alert notification False: No action taken 9. 📣 Send Alert to Telegram Type:** Telegram Node Purpose:** Sends performance alerts Message Format:** ⚠️ Low App Performance Alert 📱 App: {app_title} 🧑💻 Developer: {app_developer} ⭐ Rating: {app_rating} 📝 Reviews: {app_number_of_reviews} 🔗 View on Play Store Workflow Flow Input Form → Start Scraping → Check Status → Wait 45s → Verify Completion ↑ ↓ └──── Loop ────┘ ↓ Fetch Data → Save to Sheet & Check Ratings ↓ Send Telegram Alert Configuration Requirements API Keys & Credentials Bright Data API Key:** Required for web scraping Google Sheets OAuth2:** For data storage access Telegram Bot Token:** For alert notifications Setup Parameters Google Sheet ID:** Target spreadsheet identifier Telegram Chat ID:** Destination for alerts N8N Instance ID:** Workflow instance identifier Key Features Data Collection Comprehensive app metadata extraction Review content and rating analysis Developer and country information App store performance metrics Quality Monitoring Automated low-rating detection Real-time performance alerts Continuous data archiving Integration Capabilities Bright Data web scraping service Google Sheets data persistence Telegram instant notifications Polling-based status monitoring Use Cases App Performance Monitoring Track rating trends over time Identify user sentiment patterns Monitor competitor performance Quality Assurance Early warning for rating drops Customer feedback analysis Market reputation management Business Intelligence Review sentiment analysis Performance benchmarking Strategic decision support Technical Notes Polling Interval:** 45-second status checks Rating Threshold:** Alerts triggered for ratings < 4 Data Format:** JSON with structured field mapping Error Handling:** Includes error tracking in dataset requests Result Limiting:** Maximum 5 multiple results per request For any questions or support, please contact: info@incrementors.com or fill out this form https://www.incrementors.com/contact-us/