Workflow Templates

About This Template This workflow automatically generates and sends AI-powered responses to user inquiries from a LINE Official Account. It uses RAG (Retrieval-Augmented Generation) technology to produce natural, context-aware answers based on your FAQ database (Supabase/PostgreSQL). How It Works Receive Questions: An n8n webhook receives messages from your LINE Official Account. FAQ Search: The n8n LangChain Agent analyzes the user’s question and performs a vector search on your Supabase FAQ database. It can also fetch user-specific data (e.g., reservation info) from PostgreSQL. AI Generation: The OpenAI GPT model generates a context-aware answer based on the retrieved information and conversation history. Reply: The response is sent back to the user via the LINE Messaging API. Admin Notifications: (Optional) If the AI cannot answer, the workflow can notify admins (e.g., via LINE WORKS or Slack). Who It’s For Businesses wanting to automate customer support on LINE. Developers building intelligent chatbots with existing FAQ data. Organizations aiming for 24/7 customer service. Requirements An n8n account (cloud or self-hosted) An OpenAI API key A Supabase account (for FAQ data) A PostgreSQL database (for conversation history) A LINE Official Account & Messaging API access token Setup Steps Configure Credentials: Register credentials for OpenAI, Supabase, PostgreSQL, and LINE Messaging API in n8n. Prepare Databases: Create your tables in Supabase (for FAQs) and PostgreSQL (for conversation history). Customize the Prompt: In the "RAG AI Agent" node, edit the system prompt to fit your business and tone. Set Environment Variables: Update URLs, Channel IDs, and API endpoints in the nodes to match your environment. Customization Options Change AI Model:** Select a different model (e.g., gpt-4o) in the "OpenAI Chat Model" node. Add Data Sources:** Add new "Tool" nodes (like an HTTP Request) to the "RAG AI Agent" to access other APIs (e.g., booking systems). Change Notifications:** Replace the "LINE Works" nodes with a Slack or Email node to change the admin notification channel.

Weekly Timesheet Report + Pending Submissions Workflow Overview This workflow automates the entire weekly timesheet reporting cycle by integrating Salesforce, OpenAI, Gmail, and n8n. It retrieves employee timesheets for the previous week, identifies which were submitted or not, summarizes all line-item activities using OpenAI, and delivers a consolidated, manager-ready summary that mirrors the final email output. The workflow eliminates manual checking, reduces repeated follow-ups, and ensures leadership receives an accurate, structured, and consistent weekly report. Workflow Structure Data Source: Salesforce DBT Timesheet App This workflow requires the Digital Biz Tech – Simple Timesheet managed package to be installed in Salesforce. Install the Timesheet App: https://appexchange.salesforce.com/appxListingDetail?listingId=a077704c-2e99-4653-8bde-d32e1fafd8c6 The workflow retrieves: dbt__Timesheet__c — weekly timesheet records dbt__Timesheet_Line_Item__c — project and activity entries dbt__Employee__c — employee reference and metadata Billable, non-billable, and absence hour details Attendance information These combined objects form the complete dataset used for both submitted and pending sections. Trigger Weekly n8n Schedule Trigger — runs once every week. Submitted Path Retrieve submitted timesheets → Fetch line items → Convert to HTML → OpenAI summary → Merge with employee details. Pending Path Identify “New” timesheets → Fetch employee details → Generate pending submission list. Final Output Merge both paths → Build formatted report → Gmail sends weekly email to managers. Detailed Node-by-Node Explanation 1. Schedule Trigger Runs weekly without manual intervention and targets the previous full week. 2. Timesheet – Salesforce GetAll Fetches all dbt__Timesheet__c records matching: Timesheet for <week-start> to <week-end> Extracted fields include: Employee reference Status Billable, non-billable, absence hours Total hours Reporting period Feeds both processing paths. Processing Path A — Submitted Timesheets 3. Filter Submitted Filters timesheets where dbt__Status__c == "Submitted". 4. Loop Through Each Submitted Record Each employee’s timesheet is processed individually. 5. Retrieve Line Items Fetches all dbt__Timesheet_Line_Item__c entries: Project / Client Activity Duration Work description Billable category 6. Convert Line Items to HTML (Code Node) Transforms line items into well-structured HTML tables for clean LLM input. 7. OpenAI — Weekly Activity Summary OpenAI receives the HTML + Employee ID and returns a 4-point activity summary avoiding: Hours Dates Repeated or irrelevant metadata 8. Fetch Employee Details Retrieves employee name, email, and additional fields if needed. 9. Merge Employee + Summary Combines: Timesheet data Employee details OpenAI summary Creates a unified object. 10. Prepare Submitted Section (Code Node) Produces the formatted block used in the final email: Employee: Name Period: Start → End Status: Submitted Total Hours: ... Timesheet Line Items Breakdown: summary point summary point summary point summary point Processing Path B — Not Submitted Timesheets 11. Identify Not Submitted Timesheets still in dbt__Status__c == "New" are flagged. 12. Retrieve Employee Information Fetches employee name and email. 13. Merge Pending Information Maps each missing submission with its reporting period. 14. Prepare Pending Reporting Block Creates formatted pending entries: TIMESHEET NOT SUBMITTED Employee Name Email: user@example.com Final Assembly & Report Delivery 15. Merge Submitted + Pending Sections Combines all processed data. 16. Create Final Email (Code Node) Builds: Subject HTML body Section headers Manager recipient group Matches the final email layout. 17. Send Email via Gmail Automatically delivers the weekly summary to managers via Gmail OAuth. No manual involvement required. What Managers Receive Each Week 👤 Employee: Name 📅 Period: Start Date → End Date 📌 Status: Submitted 🕒 Total Hours: XX hrs Billable: XX hrs Non-Billable: XX hrs Absence: XX hrs Weekly Requirement Met: ✔️ / ❌ 📂 Timesheet Line Items Breakdown: • Summary point 1 • Summary point 2 • Summary point 3 • Summary point 4 🟥 TIMESHEET NOT SUBMITTED 🟥 Employee Name 📧 Email: user@example.com Data Flow Summary Salesforce → Filter Submitted / Not Submitted ↳ Submitted → Line Items → HTML → OpenAI Summary → Merge ↳ Not Submitted → Employee Lookup → Merge → Code Node formats unified report → Gmail sends professional weekly summary Technologies & Integrations | System | Purpose | Authentication | |------------|----------------------------------|----------------| | Salesforce | Timesheets, Employees, Timesheet Line Items | Salesforce OAuth | | OpenAI | Weekly activity summarization | API Key | | Gmail | Automated email delivery | Gmail OAuth | | n8n | Workflow automation & scheduling | Native | Agent System Prompt Summary > You are an AI assistant that extracts and summarizes weekly timesheet line items. Produce a clean, structured summary of work done for each employee. Focus only on project activities, tasks, accomplishments, and notable positives or negatives. Follow a strict JSON-only output format with four short points and no extra text or symbols. Key Features AI-driven extraction: Converts raw line items into clean weekly summaries. Strict formatting: Always returns controlled 4-point JSON summaries. Error-tolerant: Works even when timesheet entries are incomplete or messy. Seamless integration: Works smoothly with Salesforce, n8n, Gmail, or OpenAI. Setup Checklist Install DBT Timesheet App from Salesforce AppExchange Configure Salesforce OAuth Configure Gmail OAuth Set OpenAI model for summarization Update manager recipient list Activate the weekly schedule Summary This unified workflow delivers a complete, automated weekly reporting system that: Eliminates manual timesheet checking Identifies missing submissions instantly Generates high-quality AI summaries Improves visibility into employee productivity Ensures accurate billable/non-billable tracking Automates end-to-end weekly reporting Need Help or More Workflows? We can integrate this into your environment, tune the agent prompt, or extend it for more automation. We can also help you set it up for free — from connecting credentials to deployment. Contact: shilpa.raju@digitalbiz.tech Website: https://www.digitalbiz.tech LinkedIn: https://www.linkedin.com/company/digital-biz-tech/ You can also DM us on LinkedIn for any help.

Description Automatically triage Product UAT feedback using AI, route it to the right tools and teams, and close the feedback loop with testers, all in one workflow. This workflow analyzes raw UAT feedback, classifies it (critical bug, feature request, UX improvement, or noise), validates AI confidence, escalates when human review is needed, and synchronizes everything across Jira, Slack, Notion, Google Sheets, and email. Context Product teams often receive unstructured UAT feedback from multiple sources (forms, Slack, internal tools), making triage slow, inconsistent, and error-prone. This workflow ensures: Faster bug detection Consistent categorization Zero feedback lost Clear accountability between Product, Engineering, and Design It combines AI automation with human-in-the-loop control, making it safe for real production environments. Who is this for? Product Managers running UAT or beta programs Project Managers coordinating QA and release validation Product Ops / PMO teams Engineering teams who want faster, cleaner bug escalation Any team managing high-volume UAT feedback Perfect for teams that want speed without sacrificing control. Requirements Webhook trigger (form, internal tool, Slack integration, etc.) OpenAI account (for AI triage) Jira (bug tracking) Slack (team notifications) Notion (product roadmap / UX backlog) Google Sheets (UAT feedback log) Gmail (tester & manual review notifications) How it works Trigger The workflow starts when UAT feedback is submitted via a webhook (form, Slack, or internal tool). Normalize & Clean Incoming data is normalized into a consistent structure (tester, build, page, message) and cleaned to be AI-ready. AI Triage An AI model analyzes the feedback and returns: Type (Critical Bug, Feature Request, UX Improvement, Noise) Severity & sentiment Summary and suggested title Confidence score Quality Control If the AI output is unreliable (low confidence or parsing error), the feedback is automatically routed to manual review via email and Slack. Routing & Actions If confidence is sufficient: Critical Bugs → Jira issue + Engineering Slack alert Feature Requests → Notion roadmap UX Improvements → Design / UX tracking Noise → Archived but traceable Closed Loop The tester is notified via Slack or email, and the workflow responds to the original webhook with a structured status payload. What you get One unified UAT triage system Faster bug escalation Clean product and UX backlogs Full traceability of every feedback Automatic tester communication Safe AI usage with human fallback About me : I’m Yassin a Product Manager Scaling tech products with a data-driven mindset. 📬 Feel free to connect with me on Linkedin

🧾 AI Proposal Generator Engine An n8n-based automation that generates client proposals from a form, lets you review everything in one place, and sends the proposal only when you approve it. ⚙️ What It Does The AI Proposal Generator Engine creates proposals directly from an n8n Form. All proposal content and a draft email are generated automatically using OpenAI. Google Sheets is used only as a database, where you: Review the generated proposal Review the draft email Control when the proposal is sent by updating the status No proposal is sent until it is manually marked as READY. 💡 Use Cases | Use Case | Description | | --------------------- | ---------------------------------------------------------- | | Sales Calls | Generate proposals immediately after a call using the form | | Freelancers | Create clean, repeatable proposals without manual writing | | Agencies | Standardize proposals while keeping them client-specific | | Approval Flow | Review proposal and email before sending | | Fast Turnaround Deals | Reduce proposal creation time from hours to minutes | | Team Workflows | Use Sheets as a simple approval and tracking layer | 🔧 Setup 1️⃣ Google Credentials Go to Google Cloud Console and create a Web App (OAuth). Enable these APIs: Google Sheets Google Drive Gmail In n8n, select this Google credential inside: Google Sheets nodes Google Drive nodes Gmail nodes Use the same credential everywhere. 2️⃣ Google Drive Structure Create this folder setup in Google Drive. You can use the provided templates or your own. Proposal Generator Engine/ ├── Template 1 (Slides) ├── Template 2 (Slides) ├── Template 3 (Slides) ├── Proposal Generation Tracker (Sheets) └── Generated Proposals/ 3️⃣ Google Sheets Node Open the Proposal Generation Tracker and copy the Sheet ID from the URL. Paste this ID into the Google Sheets node in n8n. This sheet is used only to: Store generated proposal links Store email drafts Control send status 4️⃣ Slides and Drive Nodes Copy the Slides template ID you want to use and paste it into the Copy Template node. Copy the folder ID of Generated Proposals and paste it into the Move File / Folder field. 5️⃣ OpenAI Key Create an OpenAI credential in n8n using your API key. Select this credential in all GPT nodes. You can edit prompts to match your proposal style and tone. 🔁 Workflow Summary Proposal details are collected using an n8n Form OpenAI generates structured proposal content A Google Slides template is copied and filled A proposal email draft is generated Proposal link and email draft are saved in Google Sheets with status WAITING You review the proposal and email Status is changed to READY Proposal is converted to PDF and sent via Gmail Proposal is stored in Google Drive and status is updated to SENT 📞 Support & Contact 📧 Email: atharvapj5@gmail.com 🔗 LinkedIn: https://www.linkedin.com/in/atharva-jaiswal/ 📅 Book a support call: https://calendly.com/atharvapj5/30min

ETL Monitoring & Alert Automation: Jira & Slack Integration This workflow automatically processes ETL errors, extracts important details, generates a preview, creates a log URL, classifies the issue using AI and saves the processed data into Google Sheets. If the issue is important or needs attention, it also creates a Jira ticket automatically. The workflow reduces manual debugging effort, improves visibility and ensures high-severity issues are escalated instantly without human intervention. Quick Start – Implementation Steps Connect your webhook or ETL platform to trigger the workflow. Add your OpenAI, Google Sheets and Jira credentials. Enable the workflow. Send a sample error to verify Sheets logging and Jira ticket creation. Deploy and let the workflow monitor ETL pipelines automatically. What It Does This workflow handles ETL errors end-to-end by: Extracting key information from ETL error logs. Creating a short preview for quick understanding. Generating a URL to open the full context log. Asking AI to identify root cause and severity. Parsing the AI output into clean fields. Saving the processed error to Google Sheets. Creating a Jira ticket for medium/high-severity issues. This creates a complete automated system for error tracking, analysis and escalation. Who’s It For DevOps & engineering teams monitoring data pipelines. ETL developers who want automated error reporting. QA teams verifying daily pipeline jobs. Companies using Jira for issue tracking. Teams needing visibility into ETL failures without manual log inspection. Requirements to Use This Workflow n8n account or self-hosted instance. ETL platform capable of sending error payloads (via webhook). OpenAI API Key. Google Sheets credentials. Jira Cloud API credentials. Optional: log storage URL (S3, Supabase, server logs). How It Works & Setup Steps 1. Get ETL Error (Webhook Trigger) Receives ETL error payload and starts the workflow. 2. Prepare ETL Logs (Code Node) Extracts important fields and makes a clean version of the error.Generates a direct link to open the full ETL log. 3. AI Severity Classification (OpenAI / AI Agent) AI analyzes the issue, identifies cause and assigns severity. 4. Parse AI Output (Code Node) Formats AI results into clean fields: severity, cause, summary, recommended action. 5. Prepare Data for Logging (Set / Edit Fields) Combines all extracted info into one final structured record. 6. Save ETL Logs (Google Sheets Node) Logs each processed ETL error in a spreadsheet for tracking. 7. Create Jira Ticket (Jira Node) Automatically creates a Jira issue when severity is Medium, High or Critical. 8. ETL Failure Alert (Slack Node) Sends a Slack message to notify the team about the issue. 9. ETL Failure Notify (Gmail Node) Sends an email with full error details to the team. How to Customize Nodes ETL Log Extractor Add/remove fields based on your ETL log structure. AI Classification Modify the OpenAI prompt for custom severity levels or deep-dive analysis. Google Sheets Logging Adjust columns for environment, job name or log ID. Jira Fields Customize issue type, labels, priority and assignees. Add-Ons (Extend the Workflow) Send Slack or Teams alerts for high severity issues Store full logs in cloud storage (S3, Supabase, GCS) Add daily/weekly error summary reports Connect monitoring tools like Datadog or Grafana Trigger automated remediation workflows Use Case Examples Logging all ETL failures to Google Sheets Auto-creating Jira tickets with AI-driven severity Summarizing large logs with AI for quick analysis Centralized monitoring of multiple ETL pipelines Reducing manual debugging effort across teams Troubleshooting Guide | Issue | Possible Cause | Solution | |-------|----------------|----------| | Sheets not updating | Wrong Sheet ID or missing permission | Reconnect and reselect the sheet | | Jira ticket fails | Missing required fields or invalid project key | Update Jira mapping | | AI output empty | Invalid OpenAI key or exceeded usage | Check API key or usage limits | | Severity always “low” | Prompt too broad | Adjust AI prompt with stronger rules | | Log preview empty | Incorrect error field mapping | Verify the structure of the ETL error JSON | Need Help? For assistance setting up this workflow, customizing nodes or adding additional features, feel free to contact our n8n developers at WeblineIndia. We can help configure, scale or build similar automation workflows tailored to your ETL and business requirements.

This workflow automates the initial screening process for new job applications, freeing up your recruitment team to focus on qualified candidates. It receives applications from a webhook, uses OpenAI (GPT-4) to analyze resumes for skill and culture fit, generates interview questions, logs the results to Google Sheets, sends interview invitations via Gmail, and notifies your team on Slack. 🚀 Who is this for? HR and Recruitment Teams** looking to automate repetitive screening tasks. Hiring Managers** who want a consistent, data-driven first pass on applicants. Startups and SMBs** aiming to build an efficient, scalable hiring pipeline without a large HR team. 💡 How it works Receive Application: The workflow triggers when a new application is submitted via a webhook from your job board or application form. Extract & Analyze: It downloads the resume/CV, extracts the text, and sends it to OpenAI (GPT-4) with a custom prompt. Score & Generate: The AI scores the candidate on skill match and culture fit, provides a summary, and generates tailored interview questions based on their experience. Log Data: The evaluation scores, AI summary, and candidate information are appended to a new row in a Google Sheet for tracking. Schedule Interview: A personalized email is sent to the candidate via Gmail with a link to schedule their interview. Notify Team: A summary card with the AI evaluation and links to the full report is posted in a Slack channel to keep the hiring team informed. ⚙️ How to set up Configure Credentials: Set up your credentials for OpenAI, Google (for both Sheets and Gmail), and Slack in n8n. Webhook URL: Copy the "Production URL" from the "Webhook: New Application" node and set it as the destination in your job board's webhook settings (e.g., Greenhouse, Lever, Ashby, or a web form). Google Sheet: Create a Google Sheet to track applicants. Update the "G Sheets: Save Evaluation" node with your Spreadsheet ID and Sheet Name. Ensure the columns in your sheet match the data you want to save. Customize Prompts & Email: Modify the prompts in the two OpenAI nodes to match your company's values and the specific job requirements. Update the Gmail node with your email content and the logic for your scheduling link (e.g., Calendly, SavvyCal). 📋 Requirements An n8n instance (Cloud or self-hosted). An OpenAI API key. A Google account for Google Sheets and Gmail. A Slack workspace. A job application source capable of sending webhooks.

Description Automatically generate and distribute detailed End-of-Day (EOD) reports combining task progress from ClickUp and opportunity data from GoHighLevel. This workflow uses AI to analyze daily performance, summarize key metrics, identify blockers, and deliver polished reports directly to Slack, Email, and Google Drive. ⚙️📊💬 What This Template Does Triggers automatically every weekday at 6:00 PM (Mon–Fri). ⏰ Fetches all completed ClickUp tasks and won GoHighLevel opportunities for the day. 📥 Merges and transforms both datasets into a unified structure. 🔄 Uses Azure OpenAI GPT-4 to analyze performance and generate structured summaries. 🤖 Formats three output versions — Slack (Markdown), Email (HTML), and Google Drive (Text). 🧾 Routes and sends reports automatically to connected channels. 📤 Uploads the generated text report to Google Drive with timestamped filenames. ☁️ Key Benefits ✅ Saves time by automating daily performance reporting. ✅ Unifies task and deal data into a single AI-generated summary. ✅ Provides real-time visibility into productivity and outcomes. ✅ Delivers beautifully formatted, channel-specific reports. ✅ Maintains historical reports in Google Drive for reference. ✅ Helps managers identify wins, blockers, and next steps quickly. Features Automated scheduling via cron (Mon–Fri, 6 PM). ClickUp task and GHL opportunity integration for daily data sync. AI-powered analysis for contextual, actionable summaries. Dynamic formatting for Slack, Email, and Drive outputs. Parallel routing for simultaneous delivery across platforms. No manual steps — runs fully hands-free after setup. Requirements ClickUp OAuth2 credentials for task retrieval. GoHighLevel OAuth2 credentials for deal data. Azure OpenAI GPT-4 API credentials. Slack Bot credentials for message posting. SMTP (Gmail/Outlook) credentials for email reports. Google Drive OAuth2 credentials for report upload. Target Audience 🎯 Sales, marketing, and operations teams tracking daily performance. 📈 Project managers monitoring team productivity and blockers. 🤝 Client success teams summarizing EOD outcomes for leadership. 🧠 Business automation teams seeking end-of-day visibility. Step-by-Step Setup Instructions Connect ClickUp, GoHighLevel, Slack, Gmail/SMTP, and Google Drive credentials. 🔑 Set your team, space, folder, and list IDs in the ClickUp node. 📋 Update your Slack channel ID in the Slack node configuration. 💬 Configure your email sender and recipients in the email node. 📧 (Optional) Modify the cron expression for different reporting times. ⏰ Test the workflow manually once, then activate for automated EOD execution. ✅

How It Works Telegram Trigger** receives incoming messages (text, voice, photo, document). Switch** routes by message type to appropriate processors: Text → forwarded as-is. Voice → downloaded and sent to Transcribe a recording. Photo → downloaded, converted to base64, then sent to Analyze image. Document → routed to document handler. Merge* collects the processed input and passes a unified prompt to *Manager Agent**. Manager Agent (LM: Google Gemini)** orchestrates specialized agents/tools: memory_base (Airtable) → saving & retrieving personal/company memory todo_and_task_manager (Todoist / Google Sheets) → tasks email_agent (Gmail) → composing/sending emails calendar_agent (Google Calendar) → scheduling research_agent (SerpAPI / Wikipedia / Wolfram) → web research project_management (Google Sheets) → project updates Manager Agent** updates memory windows and sends the final reply back to Telegram. Setup Steps Create and configure Telegram bot; set bot token/webhook in Telegram Trigger and Telegram nodes. Update chatId placeholders. Add Google Gemini (PaLM) credentials in the Gemini model nodes. Configure Airtable knowledge-base: set base ID & table IDs used by memory_base nodes. Connect Google APIs: Sheets, Calendar, Gmail credentials and set document/sheet IDs. Configure Todoist, SerpAPI, WolframAlpha credentials and any other tool API keys. Verify Window Buffer Memory sessionKey values (match user sessions). Check schedule triggers (cron expressions) and adjust times/timezone. Run quick tests: send text, voice, image, and confirm replies and memory writes. Estimated Setup Time 30–60 minutes** → if credentials & IDs are ready. 2–4 hours** → full setup (API keys, spreadsheets, Airtable, detailed permissions). 4–8 hours** → complex deployment (team permissions, multiple calendars, advanced tool tuning, production testing).

This workflow is a complete, production-ready solution for recovering abandoned carts in Shopify stores using a multi-channel, multi-touch approach. It automates personalized follow-ups via Email, SMS, and WhatsApp, tracks every customer interaction for multi-touch attribution, and enables advanced retargeting and analytics. Key features: Multi-step, timed recovery sequence (Email → SMS → Email → WhatsApp) Customer segmentation (new, returning, VIP) and A/B testing Dynamic discounting and personalized messaging Touchpoint logging to Google Sheets for attribution analysis Facebook Custom Audience retargeting for unrecovered carts Slack notifications for high-value cart recoveries What does this workflow do? Listens for abandoned cart events from Shopify (or any e-commerce platform) via webhook. Normalizes and enriches cart data by fetching full cart details and customer purchase history. Predicts the likely reason for abandonment (e.g., price sensitivity, checkout complexity, technical issues) using rule-based logic. Segments the customer (new, returning, VIP), assigns an A/B test group, and generates a personalized discount and checkout URL. Runs a timed, multi-channel recovery sequence: 1 hour after abandonment: Checks if the order is completed. If not, sends a personalized Email #1 and logs the touchpoint. 4 hours after abandonment: Checks again. If not recovered, sends an SMS with a discount code and logs the touchpoint. 24 hours after abandonment: Checks again. If not recovered, sends Email #2 (with social proof/urgency) and logs the touchpoint. 48 hours after abandonment: Final check. If not recovered, sends a WhatsApp reminder and logs the touchpoint. If the cart is still not recovered: Hashes customer identifiers and adds them to a Facebook Custom Audience for retargeting. Logs every touchpoint (email, SMS, WhatsApp) to a Google Sheet for multi-touch attribution analysis. Sends a Slack notification if a high-value cart is recovered. Why is this workflow useful? Boosts recovery rates:** By using multiple channels and personalized timing, you maximize the chance of recovering lost sales. Improves attribution:** Every customer interaction is logged, so you can analyze which channels and messages drive conversions. Enables advanced retargeting:** Unrecovered carts are automatically added to a Facebook Custom Audience for paid retargeting. Saves time:** Fully automated, with easy configuration for your store, messaging, and analytics. Scalable and extensible:** Easily adapt the sequence, add more channels, or integrate with other tools. How to install and configure 1. Prerequisites n8n instance (v2.0.2+ recommended) Shopify store with API access Accounts and API credentials for: SendGrid (email) Twilio (SMS) WhatsApp Business API Google Sheets (service account) Facebook Graph API (for Custom Audiences) Slack (for notifications) 2. Setup steps Import the workflow into your n8n instance. Configure the “Workflow Configuration” node: Set your Shopify domain, API URLs, Google Sheets ID, and high-value threshold. Connect all required credentials in the respective nodes: Shopify, SendGrid, Twilio, WhatsApp, Google Sheets, Facebook Graph API, Slack. Create a Google Sheet named “Touchpoints” with columns: cart_id, customer_id, touchpoint_type, timestamp, channel, ab_group. Set up the webhook in your Shopify store (or e-commerce platform) to trigger the workflow on cart abandonment. Test the workflow with a sample abandoned cart event to ensure emails, SMS, WhatsApp, and logging work as expected. Enable the workflow in n8n for live operation. Node-by-node breakdown Abandoned Cart Webhook:** Receives abandoned cart events. Workflow Configuration:** Stores global settings (API URLs, Shopify domain, Google Sheets ID, high-value threshold). Normalize Cart Data:** Cleans and standardizes incoming cart data. Fetch Cart Details / Fetch Customer History:** Enriches data with full cart and customer info. Predict Abandonment Reason:** Uses business logic to guess why the cart was abandoned. Personalization Engine:** Segments the customer, assigns A/B group, calculates discount, and builds checkout URL. Customer Segment Check / Device Type Check:** Applies routing logic for personalized messaging. Wait / Check Order Status / Generate & Send Messages:** Timed sequence for Email, SMS, and WhatsApp, with order status checks at each step. Log Touchpoint (Google Sheets):** Records every message sent for attribution. Attribution Merge:** Combines all touchpoints into a single journey for analysis. Hash Customer Data for Facebook / Add to Retargeting Audience:** Adds unrecovered carts to a Facebook Custom Audience. Check Cart Value Threshold / Notify High-Value Recovery:** Sends Slack alerts for high-value recoveries. Customization tips Adjust wait times and message content to fit your brand and audience. Add or remove channels (e.g., push notifications, phone calls) as needed. Expand the Google Sheet for deeper analytics (e.g., add UTM parameters, campaign IDs). Integrate with your CRM or analytics platform for end-to-end tracking. Troubleshooting Make sure all API credentials are set and tested. Check Google Sheets permissions for the service account. Test each channel (email, SMS, WhatsApp) individually before going live. Review the workflow execution logs in n8n for errors or failed steps.

How it works • Twilio webhook detects missed/unanswered calls automatically • Analyzes call context (time of day, business hours, weekend/weekday) • Checks CRM for existing customer data and purchase history (optional) • AI Chain (GPT-4o) generates personalized recovery messages for SMS and Email • Sends instant apology with booking link via SMS and/or Email • Logs all interactions to Airtable for tracking • Slack alerts sales team with customer priority and context • Waits 24 hours and checks if customer booked • Sends automatic follow-up SMS if no booking detected • Structured output parser ensures reliable JSON formatting Set up steps • Time to set up: 15-20 minutes • Add Twilio credential and configure phone number in both SMS nodes • Get Slack channel ID for sales team alerts • Create Airtable base with 10 columns (Caller_Number, Customer_Name, Call_Time, Priority, SMS_Sent, Email_Sent, Booking_Link, Status, Urgency_Score, Follow_Up_Date) • Replace booking URL with your Cal.com or Calendly link • Configure business email for SMTP sending • Update business phone and name in follow-up SMS • Add credentials: Twilio API, OpenAI (GPT-4o), Slack OAuth2, Airtable Token, SMTP Email • Replace placeholder IDs in Slack and Airtable nodes • Optional: Configure CRM API for existing customer lookup (or disable those nodes) What you'll need • Twilio - Phone number with SMS capability • OpenAI API - GPT-4o access for AI message generation • Slack - Standard workspace for sales alerts • Airtable - Free plan works for call tracking • Email SMTP - Gmail, SendGrid, or any SMTP provider • Cal.com or Calendly - Booking link for instant scheduling • CRM API (optional) - HubSpot, Salesforce, or custom CRM Who this is for Service businesses, agencies, and sales teams that lose revenue from missed calls. Perfect for businesses with high call volume that need instant personalized follow-up to recover lost opportunities.

Who this is for This workflow is designed for teams that collect feedback or survey responses via Jotform and want to automatically: Analyze sentiment (positive, neutral, negative) of each response. Extract key topics and keywords from qualitative text. Generate AI summaries and structured insights. Store results in Google Sheets and n8n DataTables for easy reporting and analysis. Use Cases Customer experience analysis Market research & survey analysis Product feedback clustering Support ticket prioritization AI-powered blog or insight generation from feedback What this workflow does This n8n automation connects Jotform, Google Gemini, and Google Sheets to turn raw responses into structured insights with sentiment, topics, and keywords. Pipeline Overview Jotform → Webhook → Gemini (Topics + Keywords) → Gemini (Sentiment) → Output Parser → Merge → Google Sheets Jotform Trigger Captures each new submission from your Jotform (e.g., a feedback or survey form). Extracts raw fields ($json.body.pretty) such as name, email, and response text. Format Form Data (Code Node) Converts the Jotform JSON structure into a clean string for AI input. Ensures the text is readable and consistent for Gemini. Topics & Keyword Extraction (Google Gemini + Output Parser) Goal: Identify the main themes and important keywords from responses. { "topics": [ { "topic": "Product Features", "summary": "Users request more automation templates.", "keywords": ["AI templates", "automation", "workflow"], "sentiment": "positive", "importance_score": 0.87 } ], "global_keywords": ["AI automation", "developer tools"], "insights": ["Developers desire more creative, ready-to-use AI templates."], "generated_at": "2025-10-08T10:30:00Z" } Sentiment Analyzer (Google Gemini + Output Parser) Goal: Evaluate overall emotional tone and priority. { "customer_name": "Ranjan Dailata", "customer_email": "ranjancse@gmail.com", "feedback_text": "Please build more interesting AI automation templates.", "sentiment": "positive", "confidence_score": 0.92, "key_phrases": ["AI automation templates", "developer enablement"], "summary": "Customer requests more AI automation templates to boost developer productivity.", "alert_priority": "medium", "timestamp": "2025-10-08T10:30:00Z" } Merge + Aggregate Combines the topic/keyword extraction and sentiment output into a single structured dataset. Aggregates both results for unified reporting. Persist Results (Google Sheets) Writes combined output into your connected Google Sheet. Two columns recommended: feedback_analysis → Sentiment + Summary JSON topics_keywords → Extracted Topics + Keywords JSON Enables easy visualization, filtering, and reporting. Visualization (Optional) Add Sticky Notes or a logo image node in your workflow to: Visually describe sections (e.g., “Sentiment Analysis”, “Topic Extraction”). Embed brand logo: Example AI Output (Combined) { "feedback_analysis": { "customer_name": "Ranjan Dailata", "sentiment": "positive", "summary": "User appreciates current templates and suggests building more advanced AI automations.", "key_phrases": ["AI automation", "developer templates"] }, "topics_keywords": { "topics": [ { "topic": "AI Template Expansion", "keywords": ["AI automation", "workflow templates"], "sentiment": "positive", "importance_score": 0.9 } ], "global_keywords": ["automation", "AI development"] } } Setup Instructions Pre-requisite If you are new to Jotform, Please do signup using Jotform Signup For the purpose of demonstation, we are considering the Jotforms Prebuilt New Customer Registration Form as a example. However, you are free to consider for any of the form submissions. Step 0: Local n8n (Optional) If using local n8n, set up ngrok: ngrok http 5678 Use the generated public URL as your Webhook URL base for Jotform integration. Step 1: Configure the Webhook Copy the Webhook URL generated by n8n (e.g., /webhook-test/f3c34cda-d603-4923-883b-500576200322). You can copy the URL by double clicking on the Webhook node. Make sure to replace the base url with the above Step 0, if you are running the workflow from your local machine. In Jotform, go to your form → Settings → Integrations → Webhooks → paste this URL. Now, every new form submission will trigger the n8n workflow. Step 2: Connect Google Gemini Create a Google Gemini API Credential in n8n. Select the model models/gemini-2.0-flash-exp. Step 3: Create Data Storage Create a DataTable named JotformFeedbackInsights with columns: feedback_analysis (string) topics_keywords (string) Step 4: Connect Google Sheets Add credentials under Google Sheets OAuth2. Link to your feedback tracking sheet. Step 5: Test the Workflow Submit a form via Jotform. Check results: AI nodes return structured JSON. Google Sheet updates with new records. Customization Tips Change the Prompt You can modify the topic extraction prompt to highlight specific themes: You are a research analyst. Extract main topics, keywords, and actionable insights from this feedback: {{ $json.body }} Extend the Output Schema Add more fields like: { "suggested_blog_title": "", "tone": "", "recommendations": [] } Then update your DataTable or Sheets schema accordingly. Integration Ideas Send sentiment alerts to Slack for high-priority feedback. Push insights into Notion, Airtable, or HubSpot. Generate weekly reports summarizing trends across all submissions. Summary This workflow turns raw Jotform submissions into actionable insights using Google Gemini AI — extracting topics, keywords, and sentiment while automatically logging everything to Google Sheets.

Workflow Overview Zoom Attendance Evaluator with Follow-up is an n8n automation workflow that automatically evaluates Zoom meeting attendance and sends follow-up emails to no-shows and early leavers with recordings and materials. Who's it for Companies and organizations that regularly host online seminars and webinars Educational institutions conducting online classes Anyone looking to streamline participant attendance management and follow-up processes How it works Scheduled execution: Runs automatically every hour Fetch meeting data: Retrieves recent Zoom meetings and participant information Evaluate attendance: Automatically classifies participants into four categories: No-show: 0 minutes attended Early-leaver: Less than 50% attendance Partial attendance: 50-80% attendance Full attendance: Over 80% attendance Automatic follow-up: Sends automated emails with recording links and materials to no-shows and early leavers Record keeping: Logs all follow-ups to Google Sheets for tracking Requirements Zoom account: OAuth2 authentication setup required SMTP email server: Configuration needed (Gmail, SendGrid, etc.) Google Drive: For storing handout materials Google Sheets: For attendance logging Credentials for each service configured in n8n How to customize the workflow Adjust attendance thresholds: Modify the 50% and 80% values in the "Evaluate Attendance" node code Change execution frequency: Configure the time interval in the "Schedule Trigger" node Customize email template: Edit subject and body in the "Prepare Email Data" node Next session registration link: Replace the placeholder URL in the code with your actual registration link This workflow completely automates post-meeting follow-up tasks, helping improve participant engagement and reduce manual work.