Workflow Templates

n8n Workflow: WhatsApp Lead Nurturing (MQL) 🔄 Purpose This workflow fetches unqualified leads from Postgres at defined retry intervals, sends personalized WhatsApp template messages via Gallabox API, and logs message activity while updating lead status in the database. 🧩 Workflow Structure Schedule Trigger Type: n8n-nodes-base.scheduleTrigger Runs the workflow automatically at set intervals (seconds-based). Entry point of the workflow. Execute a SQL query Type: n8n-nodes-base.postgres Fetches leads from mql_contacts that: Have count = 0, 1, 2, or 3. Respect time delays: count=1 → after 3 minutes count=2 → after 5 minutes count=3 → after 8 minutes Must have disposition = unqualified. Loop Over Items4 Type: n8n-nodes-base.splitInBatches Iterates over each lead individually. Ensures one-by-one processing. Code1 Type: n8n-nodes-base.code Selects message content based on: Lead’s model (nexus, magnus, reo, general). Current count (0–3). Ensures personalized, varied message text. new_lead_4 Type: n8n-nodes-base.httpRequest Sends WhatsApp template message through Gallabox API. Dynamic fields: Lead’s name and phone. Message details selected from Code1. Quick reply buttons: Show Brochure, Get Showroom Location, Not Interested. Insert rows in a table4 Type: n8n-nodes-base.postgres Inserts a record into mql_logs. Captures: Phone, name, disposition. Message count, message_id, timestamps. Gallabox API response (status, code). Update rows in a table4 Type: n8n-nodes-base.postgres Updates mql_contacts: Increments count by 1. Updates last_message_sent timestamp. Matches using phone number. Sticky Notes Provide inline documentation: SQL query purpose. Message matrix explanation. Gallabox API role. Postgres update/logging details. ⚙️ Data Flow Summary Trigger** → Runs every X seconds SQL Query** → Fetches eligible leads (unqualified, retry intervals) Loop** → Processes each lead sequentially Code1** → Chooses personalized message based on model & count HTTP Request** → Sends WhatsApp template via Gallabox Insert Log** → Stores activity in mql_logs Update Contact** → Updates count & last sent in mql_contacts Cycle repeats** until all leads are processed 📊 Use Case Automates WhatsApp drip campaigns for unqualified leads. Respects retry intervals to avoid spamming. Uses personalized message variations based on product model & retry count. Provides full traceability with logs and lead updates.

Automatically Send Monthly Sales Reports from Square via Outlook What It Does This workflow automatically connects to the Square API and generates a monthly sales summary report for all your Square locations. The report matches the figures displayed in Square Dashboard > Reports > Sales Summary. It's designed to run monthly and pull the previous month’s sales into a CSV file, which is then sent to a manager/finance team for analysis. This workflow builds on my previous template, which allows users to automatically pull data from the Square API into n8n for processing. (See here: https://n8n.io/workflows/6358) Prerequisites To use this workflow, you'll need: A Square API credential (configured as a Header Auth credential) A Microsoft Outlook credential How to Set Up Square Credentials: Go to Credentials > Create New Choose Header Auth Set the Name to Authorization Set the Value to your Square Access Token (e.g., Bearer <your-api-key>) How It Works Trigger: The workflow runs on the 1st of every month at 8:00 AM Fetch Locations: An HTTP request retrieves all Square locations linked to your account Fetch Orders: For each location, an HTTP request pulls completed orders for the previous calendar month Filter Empty Locations: Locations with no sales are ignored Aggregate Sales Data: A Code node processes the order data and produces a summary identical to Square’s built-in Sales Summary report Create CSV File: A CSV file is created containing the relevant data Send Email: An email is sent using Microsoft Outlook to the chosen third party Example Use Cases Automatically send monthly Square sales data to management for forecasting and planning Automatically send data to an external third party, such as a landlord or agent, who is paid via commission Automatically send data to a bookkeeper for entry into QuickBooks How to Use Configure both HTTP Request nodes to use your Square API credential Set the workflow to Active so it runs automatically Enter the email address of the person you want to send the report to and update the message body If you want to remove the n8n attribution, you can do so in the last node Customization Options Add pagination to handle locations with more than 1,000 orders per month Adjust the date filters in the HTTP node to cover the full calendar month (e.g., use Luxon or JavaScript to calculate start_date and end_date) Why It's Useful This workflow saves time, reduces manual report pulling from Square, and enables smarter automation around sales data — whether for operations, finance, or performance monitoring.

What It Does This workflow lets users create Google Calendar events through natural chat messages — no forms, no clicking around, just type like you're talking to a friend. For example, you can say: “Lunch with John tomorrow at 12:30” and it’ll auto-create a calendar event with the correct title, time, and duration. How It Works Trigger: Chat Message Received The flow starts with a chat interface node (When chat message received) that listens for incoming user messages like: “Book dentist next Wed 10am” “Schedule Zoom call with Jane Friday 3–4pm” AI Agent with Scheduling Instructions The message is handed off to a Langchain-powered AI Agent that: Parses the message Resolves relative time (like "next Tuesday") into actual ISO timestamps Generates a title (summary) if not provided by the user Ensures all required fields are correctly filled Handles vague messages by asking a single clarifying question LLM (OpenAI) The agent is powered by gpt-4o-mini (or your preferred OpenAI model). You can customize this or swap it out. Google Calendar Integration Once the AI agent has structured the event details, it uses the Google Calendar Tool Node to create the event via your connected Google account. (Optional) A response node (Respond to Chat) is included (but currently disabled) — you can enable it to send a confirmation message back to the user like: “📅 Booked: Lunch with John on Aug 30 at 12:30 PM Asia/Manila.” Requirements To make this workflow functional, you need to connect: 🔐 Google Calendar OAuth2 credentials Add your Google account under Credentials > Google Calendar OAuth2 API. 🧠 OpenAI credentials Provide your OpenAI API key (used for message interpretation and slot filling). Customization Ideas Add email collection to invite attendees Expand to support recurring events Add error handling or fallback if date parsing fails Connect to Slack or Telegram for real-time event booking Important Note on Credentials This template does not include any personal API keys or credential tokens. You’ll need to connect your own Google and OpenAI credentials after import.

Replace YOUR_API_KEY with your actual SerpApi key. 2️⃣ Set Up OpenAI Connection Go to OpenAI Platform Navigate to Billing and ensure your account has credits/funding Copy your API Key into the OpenAI credentials in n8n 🧠 Workflow Breakdown Chat Trigger → User enters a financial question (e.g., “What’s the current price of Tesla?”). HTTP Request (SerpApi Finance Search) → Fetches the latest market data for the requested ticker or index. OpenAI Node → Takes both the raw financial data and the user’s query, then formulates a natural language response. Output → Returns a clear, conversational answer that can be displayed in chat, Slack, or another integration. 🎛️ Customization Guidance Multiple Tickers**: Update the workflow to query multiple tickers (e.g., TSLA, AAPL, AMZN) and return a combined report. Scheduling: Add a **Schedule Trigger to run this workflow every morning and send a market recap. Delivery Channels**: Use Slack, Email, or Google Sheets nodes to distribute reports automatically. Extended Data**: Adjust the SerpApi query to include more than prices — e.g., company info, market news, or related tickers. Custom Prompts**: Change the OpenAI system prompt to make the chatbot more formal (for reporting) or casual (for quick insights). 💬 Example Questions & Responses Question: “What’s the current price of the S&P 500?” Expected Response: “The S&P 500 (^GSPC) is currently trading at 4,725.13, down 0.8% today.” Question: “Summarize the performance of Tesla and Apple today.” Expected Response: Tesla (TSLA): $238.45, up 1.5% Apple (AAPL): $192.11, down 0.3% Question: “Give me a quick market recap.” Expected Response: “Markets are mixed today — the S&P 500 is slightly down, while tech stocks like Tesla are showing gains. Apple dipped slightly after earnings news.” 📬 Contact Need help customizing this workflow (e.g., multiple tickers, daily summaries, or integrating into dashboards)? 📧 robert@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com

Automatically Generate AI Follow-Up Messages from Fireflies Transcripts This workflow automates creating personalized follow-up messages for your clients based on meeting transcripts fetched from Fireflies. It ensures the right guest information is captured, the transcript is processed by AI, and the output is stored neatly in Google Drive. What it Does Triggers on New Appointment: The workflow starts when a new appointment is created in Google Calendar. Extracts Guest and Appointment Details: The Edit Fields node extract the guest's email, appointment start/end time, status, and creator. Fetches Transcript from Fireflies: The GraphQL node queries Fireflies using the guest email to fetch the meeting transcript, including sentences, participants, and summary. Skip IF Empty: The Filter node skip passing the Info to AI Agent if there is no record in Fireflies Generates Follow-Up Messages via AI: The AI Agent node (powered by Google Gemini) creates 12 personalized follow-up messages/emails for the guest. Messages are conversational, concise, and reference topics and pain points mentioned in the call. The messages are tailored to re-engage the client and guide them towards making a purchase. Stores Messages in Google Drive: The Google Drive node saves the AI-generated messages in a specific folder, named after the guest, for easy reference. Use Cases Missed Follow-Ups:** Automatically create personalized follow-ups after client calls without manual effort. Sales & Customer Engagement:** Ensure every client gets context-specific messages, improving engagement and conversion. Team Collaboration:** Messages are saved in Google Drive, making it easy for your team to review and send manually if needed. Customization Transcript Source:** The GraphQL node can be customized to fetch transcripts for specific guests or date ranges. Message Personalization:** The AI prompt in AI Agent can be updated to change the tone, style, or length of messages. Storage Folder:** You can change the folder in the Google Drive node to organize messages per team, campaign, or client. Troubleshooting AI Messages Not Generated:** Verify AI Agent node is connected to Google Gemini Chat Model and has correct API credentials. Messages Not Saved:** Check the Google Drive folder ID and access permissions. Requirements An N8N instance (self-hosted or cloud). Google Gemini API credentials. Google Drive account with proper folder access. Fireflies API credentials with GraphQL access. How to Set Up Connect Credentials:** In Google Calendar Node, GraphQL, AI Agent, and Google Drive nodes, select your credentials for Google Calendar, Fireflies, Google Gemini, and Google Drive. Set Guest Details Extraction:** Verify the Edit Fields node extracts all required fields (first name, last name, email, appointment times, status). Update GraphQL Query:** Ensure the query correctly fetches transcripts by guest email. Adjust if your Fireflies workspace uses different fields. Customize AI Prompt:** Update AI Agent with the exact instructions for message generation (number of messages, tone, context, platform). Configure Google Drive Storage:** Select the proper folder to save messages, ideally using guest name as file name for easy reference. Activate Workflow:** Save and activate the workflow. Video Tutorial:** Step by step video instructions present here for beginners https://youtu.be/5t9xXCz4DzM

CPO Agent with Product Team Description Streamline product development with an AI-powered Chief Product Officer (CPO) agent orchestrating specialized product team members for comprehensive product strategy and execution. Overview This n8n workflow creates a comprehensive product development department using AI agents. The CPO agent analyzes product opportunities and delegates tasks to specialized agents for product management, UX design, user research, analytics, documentation, and strategic planning. Features Strategic CPO agent using OpenAI O3 for complex product strategy and decision-making Six specialized product agents powered by GPT-4.1-mini for efficient execution Complete product lifecycle coverage from ideation to launch Automated user research and persona development UX/UI design specifications and wireframing Product analytics and KPI tracking Technical documentation and API specifications Team Structure CPO Agent**: Product vision and strategy coordination (O3 model) Product Manager**: Roadmaps, feature specifications, user stories, planning UX/UI Designer**: User flows, wireframes, interface design, usability User Research Specialist**: Research plans, personas, market analysis, insights Product Analytics Specialist**: Metrics, KPIs, A/B testing, data analysis Technical Writer**: Product documentation, API docs, user guides Product Strategy Analyst**: Competitive analysis, market positioning, GTM strategy How to Use Import the workflow into your n8n instance Configure OpenAI API credentials for all chat models Deploy the webhook for chat interactions Send product requests via chat (e.g., "Design a new mobile app feature for user onboarding") The CPO will analyze and delegate to appropriate specialists Receive comprehensive product deliverables and strategic insights Use Cases Feature Development**: Concept → Research → Design → Specifications → Metrics Product Launch**: Strategy → Documentation → Analytics → Go-to-market planning User Experience Optimization**: Research → Personas → User flows → Testing → Iteration Competitive Analysis**: Market research → Positioning → Differentiation strategies Product Roadmapping**: Vision → Priorities → Timeline → Resource planning Documentation Suite**: User guides → API documentation → Technical specifications Analytics Implementation**: KPI definition → Tracking setup → Performance analysis Market Research**: Customer interviews → Persona development → Requirements gathering Requirements n8n instance with LangChain nodes OpenAI API access (O3 for CPO, GPT-4.1-mini for specialists) Webhook capability for chat interactions Optional: Integration with product management tools (Jira, Figma, etc.) Cost Optimization O3 model used only for strategic CPO decisions GPT-4.1-mini provides 90% cost reduction for specialist tasks Parallel processing enables simultaneous agent execution Template library leverages proven product frameworks Integration Options Connect to product management tools (Jira, Asana, Linear) Integrate with design platforms (Figma, Sketch, Adobe XD) Link to analytics tools (Mixpanel, Amplitude, Google Analytics) Export to documentation platforms (Notion, Confluence) Performance Metrics Feature adoption rates and user engagement Product-market fit indicators User satisfaction and NPS scores Development velocity and cycle times Documentation completeness and clarity Contact & Resources Website**: nofluff.online YouTube**: @YaronBeen LinkedIn**: Yaron Been Tags #ProductManagement #UXDesign #UserResearch #ProductStrategy #ProductOps #ProductAnalytics #TechnicalWriting #ProductDevelopment #FeatureDesign #ProductAI #n8n #OpenAI #MultiAgentSystem #ProductTech #ProductLeadership #Innovation

This workflow solves a critical problem in AI chat implementations: handling multiple rapid messages naturally without creating processing bottlenecks. Unlike traditional approaches where every user waits in the same queue, our solution implements intelligent conditional buffering that allows each conversation to flow independently. Key Features: Aggregates rapid user messages (like when someone types multiple lines quickly) into single context Only the first message in a burst waits - subsequent messages skip the queue entirely Each user session operates independently with isolated Redis queues Reduces LLM API calls by 45% through intelligent message batching Maintains conversation memory for contextual responses Perfect for: Customer service bots, AI assistants, support systems, and any chat application where users naturally send multiple messages in quick succession. The workflow scales linearly with users, handling hundreds of concurrent conversations without performance degradation. Some Use Cases: Customer support systems handling multiple concurrent conversations AI assistants that need to understand complete user thoughts before responding Educational chatbots where students ask multi-part questions Sales bots that need to capture complete customer inquiries Internal company AI agents processing complex employee requests Any scenario where users naturally communicate in message bursts Why This Template? Most chat buffer implementations force all users to wait in a single queue, creating exponential delays as usage scales. This template revolutionizes the approach by making only the first message wait while subsequent messages flow through immediately. The result? Natural conversations that scale effortlessly from one to hundreds of users without compromising response quality or speed. Prerequisites n8n instance (v1.0.0 or higher) Redis database connection OpenAI API key (or alternative LLM provider) Basic understanding of webhook configuration Tags ai-chat, redis, buffer, scalable, conversation, langchain, openai, message-aggregation, customer-service, chatbot

📄 Description This workflow automates the extraction of structured invoice data from PDF files sent via Telegram and stores it in Airtable. It leverages GPT-4o for intelligent parsing and includes conversational memory for a seamless user experience. Designed for businesses and freelancers who receive invoices digitally and want to streamline their record-keeping. ⚙️ How It Works Telegram Trigger – Listens for incoming messages and PDF attachments. Switch Node – Filters messages to ensure only PDFs are processed. Extract from File – Parses the PDF content for text extraction. Edit Fields – Prepares the extracted data for AI processing. AI Agent (GPT-4o) – Orchestrates the workflow, prompts the user for missing info, and extracts structured data. Simple Memory – Maintains conversational context across sessions. Create Invoice (Airtable Tool) – Creates a new invoice record in Airtable. Create Line Item (Airtable Tool) – Adds individual line items linked to the invoice. Telegram Response – Sends confirmation back to the user. 🔐 Required Credentials To run this workflow successfully, you’ll need: Telegram Bot Token** (via @BotFather) OpenAI API Key** (with GPT-4o access) Airtable API Key** and access to: Base: Invoice Tracker Proper Tables: Invoices and Line Items 🧰 Airtable Structure Invoices Table Fields: Invoice Number Date Supplier Supplier Address Tax ID PO Number Due Date Receiver Name Receiver Address Delivery Date Total Tax Total Amount Line Items Table Fields: Product Code Description Unit Price Quantity Unit Type Sub Total Invoice (linked) 🧠 Features AI-powered invoice parsing PDF text extraction Airtable record creation with relational linking Telegram-based user interaction Conversational memory Error handling and data validation

What It Does This workflow automatically connects to the Square API and generates a daily sales summary report for all your Square locations. The report matches the figures displayed in Square Dashboard > Reports > Sales Summary. It's designed to run daily and pull the previous day's sales into a Google Sheet for easy analysis and reporting. This workflow builds on my previous template, which allows users to automatically pull data from the Square API into N8N for processing. (See here: https://n8n.io/workflows/6358) Prerequisites To use this workflow, you'll need: A Square API credential (configured as a Header Auth credential) A Google Sheets credential How to Set Up Square Credentials: Go to Credentials > Create New Choose Header Auth Set the Name to "Authorization" Set the Value to your Square Access Token (e.g., Bearer <your-api-key>) How It Works Trigger – The workflow runs daily at 4:00 AM Fetch Locations – An HTTP request retrieves all Square locations linked to your account Fetch Orders – For each location, an HTTP request pulls completed orders for the specified report_date Filter Empty Locations – Locations with no sales are ignored Aggregate Sales Data – A Code node processes the order data and produces a summary identical to Square’s Sales Summary report Append to Google Sheets – The data will automatically be appended to an existing Google sheet Example Use Cases Automatically store daily sales data in Google Sheets for analysis and historical tracking Automatically create charts or visualizations from the imported data Build weekly/monthly reports after running for multiple days Quickly calculate commissions or rent payments based on sales volume How to Use Configure both HTTP Request nodes to use your Square API credential Set the workflow to Active so it runs automatically Select the Google Sheet you want to import data into, and map the data to your columns Customization Options Add pagination to handle locations with more than 1,000 orders per day Expand the workflow to save or send the report output via other integrations (email, database, webhook, etc.) Why It's Useful This workflow saves time, reduces manual report pulling from Square, and enables smarter automation around sales data—whether for operations, finance, or performance monitoring.

How it works Fetch campaign & members from Salesforce. GPT‑4 auto‑writes a channel‑appropriate, personalised outbound message. Switch node sends via Twilio (SMS/WhatsApp), SMTP (Email). Mark each member as processed to avoid double‑touches. Error trigger notifies Slack if anything fails. Set‑up steps Time: ~10‑15 min once credentials are ready. Prereqs: Active Salesforce OAuth app, Twilio account, SMTP creds, Slack app. In‑flow sticky notes walk you through credential mapping, environment variables, and optional tweaks (e.g., campaign SOQL filter). > Copy the workflow, add your keys, and run a quick manual test—after that you can place it on a cron or Salesforce trigger.

Sales Tax Calculator API Integration: Automate Tax Calculation with Google Sheets & RapidAPI Effortlessly calculate and store sales tax rates based on user address data using the Sales Tax Calculator API on RapidAPI. Automate the process, format the data, and store results in Google Sheets for easy access.** Workflow Overview: This automation workflow integrates the Sales Tax Calculator API from RapidAPI to calculate and store sales tax rates based on user-provided address information. The workflow is designed to automate tax calculation, streamline data processing, and save results in a Google Sheets document for future reference. Node-by-Node Explanation: 1. On Form Submission: Trigger: This node listens for form submissions, capturing the user’s address data (street, city, state, zip). 2. Calculate Sales Tax: Action: Sends a POST request to the Sales Tax Calculator API (via RapidAPI) to fetch tax rates based on the submitted address data. 3. Reformat API Response: Processing: Processes and reformats the data received from the API, structuring the tax agencies, rates, and total tax calculations into rows. 4. Append to Google Sheets: Store: Appends the reformatted tax information into a Google Sheets document for easy storage and future analysis. Use Case: This workflow is ideal for businesses or individuals who need to automatically calculate sales tax based on customer-provided address information. It can be used in any e-commerce platform, accounting system, or sales management tool. Benefits: Automation: Streamline the tax calculation process by automatically calculating and storing tax rates based on user inputs. Real-Time Data: Ensure up-to-date tax rates are used for every transaction or form submission. Easy Data Access: Tax rates and details are stored in Google Sheets, providing easy access and better organization for future reference. Efficient Workflow: Saves time and reduces the possibility of human error by automating the entire process from data collection to storage. Integration with RapidAPI: This workflow is powered by the Sales Tax Calculator API from RapidAPI, which ensures accurate and real-time tax calculations based on user addresses. Key Features of the Sales Tax Calculator API: Fetch tax rates based on various address details (street, city, state, zip). Reliable and fast service via RapidAPI, ensuring smooth API integrations. Provides tax rate data for multiple jurisdictions (states, cities, etc.). Start using the Sales Tax Calculator API on RapidAPI today and streamline your sales tax process. 🔑 How to Get API Key from RapidAPI Sales Tax Calculator Follow these steps to get your API key and start using it in your workflow: Visit the API Page 👉 Click here to open Sales Tax Calculator on RapidAPI Log in or Sign Up Use your Google, GitHub, or email account to sign in. If you're new, complete a quick sign-up. Subscribe to a Pricing Plan Go to the Pricing tab on the API page. Select a plan (free or paid, depending on your needs). Click Subscribe. Access Your API Key Navigate to the Endpoints tab. Look for the X-RapidAPI-Key under Request Headers. Copy the value shown — this is your API key. Use the Key in Your Workflow In your n8n workflow (HTTP Request node), replace: "x-rapidapi-key": "your key" with: "x-rapidapi-key": "YOUR_ACTUAL_API_KEY" Keywords: Sales Tax Calculator, Sales Tax API, RapidAPI, Tax Calculation, Google Sheets Integration, Automation, API Integration

🌐 Bulk Domain Authority (DA/PA) Checker And Google Sheet Logging Easily check Domain Authority (DA) and Page Authority (PA) for multiple domains using this automated n8n workflow powered by the Bulk DA PA Checker API on RapidAPI. Simply submit your domains via a web form, and the workflow fetches detailed SEO metrics and logs the data into Google Sheets. 🚀 What This Workflow Does This automation leverages the Bulk DA PA Checker API from RapidAPI to: Accept multiple domains via a user-friendly form Send bulk requests to the Bulk DA PA Checker API for fast SEO metric retrieval Process and reformat the API response for easy consumption Append the domain authority data directly into Google Sheets for tracking and analysis Perfect for SEO pros, marketers, and agencies looking to streamline their domain analysis with the power of RapidAPI. ⚙️ Workflow Highlights | 🧩 Node | 🔍 Description | |--------|----------------| | 📝 Form Trigger | User submits comma-separated domains through a simple form. | | 🌐 Check DA PA Bulk (RapidAPI) | Sends a POST request to the Bulk DA PA Checker API to fetch DA/PA and related SEO metrics. | | 🛠️ Re Format | Parses and extracts each domain’s data from the API response. | | 📊 Append in Google Sheets | Logs all metrics in a structured Google Sheet for easy review and reporting. | 🧠 Key SEO Metrics Retrieved Domain Authority Page Authority Spam Score HTTP Status Code Last Crawled Date External URLs and Redirects And many more from the Bulk DA PA Checker API response ✅ Why Use This Workflow with the Bulk DA PA Checker API? Bulk checking saves time compared to manual domain lookups Reliable data powered by a trusted RapidAPI service Seamless integration with Google Sheets for reporting Easily repeatable and scalable for large domain lists 🔑 How to Get API Key from RapidAPI Bulk DA PA Checker API Follow these steps to get your API key and start using it in your workflow: Visit the API Page 👉 Click here to open Bulk DA PA Checker API on RapidAPI Log in or Sign Up Use your Google, GitHub, or email account to sign in. If you're new, complete a quick sign-up. Subscribe to a Pricing Plan Go to the Pricing tab on the API page. Select a plan (free or paid, depending on your needs). Click Subscribe. Access Your API Key Navigate to the Endpoints tab. Look for the X-RapidAPI-Key under Request Headers. Copy the value shown — this is your API key. Use the Key in Your Workflow In your n8n workflow (HTTP Request node), replace: "x-rapidapi-key": "your key" with: "x-rapidapi-key": "YOUR_ACTUAL_API_KEY"