Workflow Templates

Description: Turn raw customer feedback into actionable insights with this intelligent n8n workflow template! Automatically capture reviews from Google Sheets, run AI-driven sentiment and intent analysis, and enrich your dataset with structured insights—no manual review required. This automation connects to your feedback form responses, processes reviews with an AI model, classifies intent, evaluates sentiment, assigns a score, and generates concise summaries. The results are then parsed, merged with original customer details, and stored in a structured Google Sheet for easy tracking. Perfect for sales, product, and customer success teams looking to streamline lead qualification and feedback analysis. What This Template Does: 📊 Captures new customer feedback from Google Sheets in real time 🧠 Uses AI to classify intent (praise, complaint, suggestion, etc.) 😊 Detects sentiment (positive, neutral, negative, or mixed) 🔢 Assigns a review score (1–10) for quick lead qualification 📝 Generates short, meaningful summaries of customer reviews 📂 Saves enriched data into a structured destination sheet 🌟 100% hands-free: just let AI process and organize your feedback Built-in Logic Ensures: ✔️ Clean JSON-based AI output (intent, sentiment, score, summary) ✔️ Customer details remain tied to their feedback and insights ✔️ Final dataset is ready for reporting, CRM import, or dashboards Requirements: Google Sheets with customer feedback form responses Google Sheets account for storing enriched data Azure OpenAI (or compatible) account for AI analysis n8n instance (self-hosted or cloud) Perfect For: Sales teams qualifying leads based on review sentiment Product managers analyzing user feedback at scale Customer success teams identifying risks and opportunities Analysts turning unstructured reviews into actionable insights

📸 Instagram Post Automation Workflow ℹ️ What is this workflow This workflow automatically produces daily Instagram posts based on a user-provided prompt and sends them to your email inbox. Social media creators can use it to generate content periodically and save time. The email includes: Picture Title Caption Relevant hashtags You can simply copy and paste the content from the email into Instagram, or go further by connecting it to the Facebook API for full automation. 💼 Business Cases Generating social media posts primarily for Instagram. Integrating with other workflows (trend research, market studies, news feeds) to produce images, statistics, text, or data comparisons for social media. 💰 Business Value If you produce daily posts and each Instagram post takes around 1 hour to find a quote, create an image, caption, and hashtags, this workflow does it in less than 1 minute. This saves you: Weekly: 7 hours (1 hour × 7 days) Monthly: 30 hours (1 hour × 30 days) Yearly: 360 hours (12 months × 30 hours) At a cost of $20/hour, this workflow saves: $7,200 annually (360 hours × $20). In total, you're saving 360 hours + $7,200 per year, allowing you to focus on other valuable activities. ⚙️ How Does It Work The workflow runs periodically according to your schedule settings. Generates a new quote, avoiding duplicates of previously created ones. Creates an image. Sends all content by email. 🔗 Integrated Services Local file storage on the hosted platform OpenAI GPT model (customizable to any AI model you prefer) Gemini model for image generation (replaceable with your preferred tool) Email sending via SMTP 🛠 How to Set Up Install the workflow template. Configure AI models and set up SMTP credentials. Create a file on your local installation (/home/node/instagram_posts.txt). Set up the scheduler. Test and enjoy.

🧩 What Problem Does It Solve? Meta’s ad forms often generate unqualified leads from casual scrollers. This workflow uses WhatsApp and AI to automatically verify, qualify, and prioritize real leads — saving time and boosting sales efficiency. 📝 Description This workflow automates lead qualification for businesses using Meta Ads (Facebook/Instagram Lead Ads) to filter out irrelevant leads. It ensures only confirmed prospects enter your CRM by: Collecting new Facebook leads Verifying via WhatsApp confirmation Classifying responses with AI Updating CRM status based on intent When a new Facebook lead arrives: Lead details are extracted (name/phone/email) Zoho CRM is checked for existing contacts WhatsApp confirmation request is sent AI classifies the response (confirmed/declined/human/invalid) CRM status is updated automatically Sales team receives only verified leads 🎯 Key Advantages for Meta Ads ✅ Blocks 60%+ irrelevant leads based on WhatsApp non-response ✅ Reduces fake submissions by requiring active confirmation ✅ Prevents CRM bloat through duplicate checking ✅ Identifies hot leads via instant "human_requested" escalation ✅ Saves sales team hours by auto-declining "no" responses 🛠️ Features Facebook Lead Ads integration via Graph API WhatsApp messaging via Twilio AI response classification (Gemini) Zoho CRM synchronization Duplicate lead prevention Customizable confirmation flow Error-resistant JSON parsing CRM owner assignment Status-based routing 🔧 Requirements Facebook Access Token with ads_management & leads_retrieval permissions Twilio Account with WhatsApp-enabled number Zoho CRM with custom "Status" field Gemini API Key (or alternative LLM) n8n credentials configured for: Twilio (API SID/token) Zoho CRM (OAuth2) Google Gemini (or alternative LLM) ⚙️ Customization Tips 1-Adjust Classification Criteria Modify the AI prompt in Classify Response (AI) node 2-Customize CRM Status Values Update field IDs in Zoho nodes 3-Modify Messaging Edit WhatsApp templates in Send WhatsApp Confirmation 4-Set Owner Assignment Replace owner ID in Prepare Owner ID node 🧠 Use Case Examples Real Estate Agencies: Filter speculative inquiries from serious buyers Medical Clinics: Verify appointment requests before scheduling SAAS Companies: Qualify free trial sign-ups Education Providers: Confirm course interest before counselor assignment Auto Dealerships: Screen test drive requests from tire-kickers If you need help get in touch on Linkedin

This automated n8n workflow monitors API uptime by periodically checking API availability and sending instant WhatsApp alerts if any service goes down. It retrieves API details from a Google Sheet and includes retry logic for failed requests. Good to Know Checks API status every 15 minutes Integrates with Google Sheets for API list management Implements a retry mechanism with up to 4 attempts Sends WhatsApp alerts for downtime Supports customizable API request configurations How It Works Schedule Trigger** - Triggers every 15 minutes Read API List** - Fetches all API URLs from a Google Sheet Process Each API1** - Loops through each API entry Init Retry Counter** - Initializes retryCount = 0 Test API** - Sends the first request to the API Check Response** - Checks if a valid response was received If No Response** - Branches into retry flow if down Wait 10 Min → Increment Retry → Retry API → Check Retry Response** - Wait and retry API call once If Still No Response** - Verifies if retry also failed If Still No Retry > 4** - Checks if retry limit is reached (≥ 4) Format Down Alert** - Formats the WhatsApp alert with API details Send WhatsApp Alert** - Sends API down alert to the configured number Continue Next API** - Moves to the next API in the list How to Use Import workflow into n8n Configure Google Sheets API for API list access Set up WhatsApp API for alerts Define API details in Google Sheet Test with sample APIs and verify alerts Adjust retry limits or schedule as needed Requirements Access to Google Sheets API WhatsApp API configuration Scheduled trigger setup in n8n Sheet Structure | Sheet Column | Example Data | | -------------------- | ------------------------------------------------------------ | | name | Timeout Test | | method | GET | | url | https://httpbin.org/delay/15 | | headers | {"Content-Type": "application/json"} | | body | {"key": "value"} | | expectedField | status | | expectedValue | success | | expectedStatusCode | 200 | Customizing This Workflow Modify trigger interval Adjust retry limits or wait times Customize WhatsApp alert format Add additional API headers or body data Integrate with other notification services

Stay informed about the latest n8n updates automatically! This workflow monitors the n8n GitHub repository for new pull requests, filters updates from today, generates an AI-powered summary, and sends notifications to your Telegram channel. Who's it for n8n users who want to stay up-to-date with platform changes Development teams tracking n8n updates Anyone managing n8n workflows who needs to know about breaking changes or new features How it works Daily scheduled check at 10 AM for new pull requests Fetches latest PR from n8n GitHub repository Filters to only process today's updates Extracts the pull request summary AI generates a clear, technical summary in English Sends notification to your Telegram channel

How It Works Automates daily tenant analytics, churn risk evaluation, and proactive retention by unifying tenant data from multiple sources, applying GPT-4–based risk scoring, detecting early churn indicators, routing high-risk tenants to retention specialists, and initiating targeted engagement campaigns. It retrieves tenant profiles, service requests, and feedback data, performs GPT-4 analysis with detailed churn risk insights, assesses engagement levels, escalates high-risk tenants to dedicated communication teams, delivers personalized loyalty incentives and engagement emails, and updates CRM systems and retention dashboards. Designed for property management companies and SaaS providers. Setup Steps Configure tenant data sources. Connect OpenAI GPT-4 API for risk analysis and churn prediction. Set up Gmail, Slack, and CRM credentials for communication and tracking. Define churn risk thresholds, retention messaging templates, and reward programs. Prerequisites Tenant/customer data source; service request system; feedback collection tool; Use Cases Property management automating tenant retention across portfolios; Customization Adjust churn risk algorithms and thresholds, Benefits Predicts churn before it happens, enables proactive retention

Apple App Store Connect: Featuring Nominations Report This workflow automates the process of tracking and reporting app nominations submitted to Apple for App Store featuring consideration. It connects to the App Store Connect API to fetch your list of apps and submitted nominations, stores the data in a MySQL database, and generates a report of all nominations. The report is then exported as a CSV file and can be automatically shared via Google Drive and Slack. Key features Authenticates with App Store Connect using JWT. Fetches all apps and submitted nominations, including details and related in-app events (API documentation: https://developer.apple.com/documentation/appstoreconnectapi/featuring-nominations) Stores and updates app and nomination data in MySQL tables. Generates a comprehensive nominations report with app and nomination details. Exports the report as a CSV file. Shares the report automatically to Google Drive and Slack. Runs on a weekly schedule, but can be triggered manually as well. Setup Instructions Obtain your App Store Connect API credentials (Issuer ID, Key ID, and private key) from your Apple Developer account. Set up a MySQL database and configure the connection details in the workflow’s MySQL node(s). (Optional) Connect your Google Drive and Slack accounts using the respective n8n nodes if you want to share the report automatically. Update any credentials in the workflow to match your setup. Activate the workflow and set the schedule as needed. This template is ideal for teams who regularly submit apps or updates for featuring on the App Store and want to keep track of their nomination history and status in a structured, automated way.

This template adapts Andrej Karpathy’s LLM Council concept for use in n8n, creating a workflow that collects, evaluates, and synthesizes multiple large language model (LLM) responses to reduce individual model bias and improve answer quality. 🎯 The gist This LLM Council workflow acts as a moderation board for multiple LLM “opinions”: The same question is answered independently by several models. All answers are anonymized. Each model then evaluates and ranks all responses. A designated Council Chairman model synthesizes a final verdict based on these evaluations. The final output includes: The original query The Chairman’s verdict The ranking of each response by each model The original responses from all models The goal is to reduce single‑model bias and arrive at more balanced, objective answers. 🧰 Use cases This workflow enables several practical applications: Receiving more balanced answers by combining multiple model perspectives Benchmarking and comparing LLM responses Exploring diverse viewpoints on complex or controversial questions ⚙️ How it works The workflow leverages OpenRouter, allowing access to many LLMs through a single API credential. In the Initialization node, you define: Council member models: Models that answer the query and later evaluate all responses Chairman model: The model responsible for synthesizing the final verdict Any OpenRouter-supported model can be used: https://openrouter.ai/models For simplicity: Input is provided via a Chat Input trigger Output is sent via an email node with a structured summary of the council’s results 👷 How to use Select the LLMs to include in your council: Council member models: Models that independently answer and evaluate the query. The default template uses: openai/gpt-4o google/gemini-2.5-flash anthropic/claude-sonnet-4.5 perplexity/sonar-pro-search Chairman model: Choose a model with a sufficiently large context window to process all evaluations and rankings. Start the Chat Input trigger. Observe the workflow execution and review the synthesized result in your chosen output channel. ⚠️ Avoid using too many models simultaneously. The total context size grows quickly (n responses + n² evaluations), which may exceed the Chairman model’s context window. 🚦 Requirements OpenRouter API access** configured in n8n credentials SMTP credentials** for sending the final council output by email (or replace with another output method) 🤡 Customizing this workflow Replace the Chat Input trigger with alternatives such as Telegram, email, or WhatsApp. Redirect output to other channels instead of email. Modify council member and chairman models directly in the Initialization node by updating their OpenRouter model names.

How it works Every day at 6:00 AM, the workflow pulls all events from your Google Calendar scheduled for that day. It extracts each event’s ID, title, and start time, aggregates them into one list, and converts them into a text string. This text is passed to an AI-powered Information Extractor (using Claude 3.5 Sonnet) to format the events into a clear daily summary. Finally, the summary is sent as a Telegram message to your chosen chat ID, giving you a ready-to-read daily to-do list. How to use Connect your Google Calendar account to the Get many events node. Set the correct calendar in the calendar field. Link your Telegram account and set your chatId in the Send a text message node. Adjust the Schedule Trigger node if you want a different reminder time. Activate the workflow — it will run daily and send your event summary to Telegram automatically. Customising this workflow Reminder time: Change triggerAtHour in the Schedule Trigger node for morning, evening, or multiple reminders per day. Calendar source: Switch to another Google Calendar or add multiple Get many events nodes for different calendars. Message style: Edit the Information Extractor system prompt to change language, formatting, or level of detail in your summary. Delivery channel: Replace or add another messaging node (e.g., Email, Slack, WhatsApp) if you want your to-do list in different apps. Event filtering: Add a filter before aggregation to include only certain event types or keywords (e.g., “Meeting”, “Deadline”).

How It Works Trigger Watches for new emails with attachments in a Gmail label. Extract Data Extracts job code from the email subject (e.g., FN-001) Extracts raw text from the attached CV (PDF) AI Parsing Uses Google Gemini to parse the CV and extract: Name Email Years of experience Skills Job Lookup Uses the extracted job code to retrieve job details from Airtable. AI Scoring Compares applicant data with job requirements Scores from 1–100 Generates a brief reasoning summary (in Bahasa Indonesia) Log to Airtable Saves applicant data, score, and AI notes to the "Applications" table. Setup Instructions Prepare Airtable Base Job Posts Table Columns: Job Code, Job Title, Required Skills, Minimum Experience, Job Description Applications Table Columns: Applicant Name, Email, Score, Notes Include a linked field to the Job Posts table Add Credentials in n8n Gmail Google AI (Gemini) Airtable Configure Nodes Trigger: Set Gmail filter (e.g., label:job-applications) Extract Job Code: Verify regex format, default is ([A-Z]{2}-\d{3}) Airtable Nodes: Select your base and table in: "Find Job Post..." "Save Applicant..." Activate Workflow Save and enable the workflow New applications will be processed automatically

How it works This workflow automatically discovers and analyzes backlinks for any website, providing comprehensive SEO insights and competitive intelligence using AI-powered analysis. Key Steps Website Input - Accepts target URLs via webhook or manual input for backlink analysis. Backlink Discovery - Scrapes and crawls the web to find all backlinks pointing to the target website. AI-Powered Analysis - Uses GPT-4 to analyze backlink quality, relevance, and SEO impact. Data Processing & Categorization - Cleans, validates, and automatically categorizes backlinks by type, authority, and relevance. Database Storage - Saves processed backlink data to PostgreSQL database for ongoing analysis and reporting. API Response - Returns structured summary with backlink counts, domain authority scores, and SEO insights. Set up steps Setup time: 8-12 minutes Configure OpenAI credentials - Add your OpenAI API key for AI-powered backlink analysis. Set up PostgreSQL database - Connect your PostgreSQL database and create the required table structure. Configure webhook endpoint - The workflow provides a /analyze-backlinks endpoint for URL submissions. Customize analysis parameters - Modify the AI prompt to include your preferred SEO metrics and analysis criteria. Test the workflow - Submit a sample website URL to verify the backlink discovery and analysis process. Set up database table - Ensure your PostgreSQL database has a backlinks table with appropriate columns. Features Comprehensive backlink discovery**: Finds all backlinks pointing to target websites AI-powered analysis**: GPT-4 analyzes backlink quality, relevance, and SEO impact Automatic categorization**: Backlinks categorized by type (dofollow/nofollow), authority level, and relevance Data validation**: Cleans and validates backlink data with error handling Database storage**: PostgreSQL integration for data persistence and historical tracking API responses**: Clean JSON responses with backlink summaries and SEO insights Competitive intelligence**: Analyzes competitor backlink profiles and identifies link building opportunities Authority scoring**: Calculates domain authority and page authority metrics for each backlink

Scanning Email Inbox for Delivery Errors Prerequisite: Automate Personalized Email Campaigns with Google Docs, Sheets, and SMTP. How It Works After running your email campaign, some messages may fail to deliver. This workflow scans your email inbox for delivery errors (e.g., bounced messages), flags problematic email addresses in the Google Sheet and ensures future campaigns skip them. How to Use Ensure Prerequisite Workflow: You should have the Email Campaign Workflow configured and running. Google Sheet Setup: Use the Google Sheet Template. Identify your document’s ID (the string after /d/ and before /edit in the URL). Configure Workflow: Enter your Google Sheet ID in the settings node. Connect your Google credentials to n8n. Email Inbox: Set up the readspamfolder node to search for bounce/error messages in your mail (e.g., in the Spam or Inbox folders—adjust label/folder if emails land elsewhere). Google Sheet Update: Configure the lookupemail and update_err nodes Requirements Google Credentials** to access Gmail and sheets. Gmail Account** (bounce/error messages must be accessible here). n8n Version:** Tested with 1.105.2 (Ubuntu). Need Help? Comment this post or contact me on LinkedIn Ask in the n8n Community Forum!