Workflow Templates

Who is this for This template is perfect for: Market Researchers** tracking industry trends. Tech Teams** wanting to stay updated on specific technologies (e.g., "AI", "Cybersecurity"). Content Creators** looking for curated news topics. Busy Professionals** who need a high-signal, low-noise news digest. What it does Fetches News: Pulls daily articles via NewsAPI based on your chosen keyword (default: "technology"). AI Filtering: Uses an AI Agent (via OpenRouter) to filter out low-quality or irrelevant clickbait. Daily Digest (Slack): Summarizes the top 3 articles in English. Translates the summaries to Japanese using DeepL (optional). Posts both versions to a Slack channel. Data Archiving (Sheets): Extracts structured data (Title, Author, Summary, URL) and saves it to Google Sheets. Weekly Trend Report: Every Monday, it reads the past week's data from Google Sheets and uses AI to generate a high-level trend report and strategic insights. How to set up Configure Credentials: You will need API keys/auth for NewsAPI, OpenRouter (or OpenAI), DeepL, Google Sheets, and Slack. Setup Google Sheet: Create a sheet with the following headers in the first row: title, author, summary, url. Map the Sheet: In the "Append row in sheet" and "Read sheet (weekly)" nodes, select your file and map the columns. Define Keyword: Open the "Set Keyword" node and change chatInput to the topic you want to track (e.g., "Crypto", "SaaS", "Climate Change"). Slack Setup: Select your desired channel in the Slack nodes. Requirements n8n** (Self-hosted or Cloud) NewsAPI** Key (Free tier available) OpenRouter** (or any LangChain compatible Chat Model like OpenAI) DeepL** API Key (for translation) Google Sheets** account Slack** Workspace How to customize Change the Language:** Remove the DeepL node if you only want English, or change the target language code. Adjust the Prompt:** Modify the "AI Agent (Filter)" system message to change how strict the news filtering is. Change Schedule:** Adjust the Cron nodes to run at your preferred time (currently set to Daily 8 AM and Weekly Monday 9 AM).

AI YouTube Trend Intelligence Report: YouTube API + GPT-4o + PDF Dashboard Who is this for? AI creators, marketers, agencies, and researchers tracking YouTube trends who need weekly high-signal insights without 4+ hours manual research. **What problem is this workflow solving? Trend hunting is exhausting:** Scanning 500+ videos across keywords Manual engagement calculations No automated filtering or analysis Scattered spreadsheets vs polished reports This workflow auto-discovers top videos, ranks by engagement, and delivers branded PDF + Sheets dashboard. What this workflow does Trigger: Form input (keywords, days back) or weekly cron YouTube API: Searches 10 keywords → ~500 videos (past 7 days) Ranking: Views + engagement rates → top performers Google Sheets: Exports channels/videos/keywords/stats GPT-4o: Analyzes trends → content recommendations PDF.co: HTML charts → branded PDF report Gmail: Delivers to inbox Setup:(5 minutes) YouTube Data API v3 key (HTTP Query Auth) Google Sheets OAuth2 for exports OpenAI API (GPT-4o-mini) PDF.co for HTML-to-PDF Gmail OAuth2 + recipient email Fully configurable env vars—no hardcoded IDs. How to customize: Edit 10-term list for your niche Filters: Adjust min views (1k), engagement (2%) Schedule: Daily/weekly cron Output: Swap Gmail for Slack/Notion Scale: 1000s videos/month ROI: 4+ hours saved weekly 20% higher content performance Automated competitive intel Zero manual spreadsheet work Need help customizing? Contact me for consulting and support: LinkedIn / **[Message](https://tally.so/r/E Keywords: YouTube trend analysis, AI YouTube research, YouTube analytics automation, content trend tracker, video engagement ranking, YouTube API n8n, weekly YouTube report, YouTube keyword monitoring

WooCommerce Weekly Sales KPI Reporting to Slack & Google Sheets This workflow automatically generates a weekly sales performance report from WooCommerce and shares it with your team. It runs on a weekly schedule, fetches last week’s orders and refunds, calculates key sales KPIs, stores the results in Google Sheets and sends a summarized report to a Slack channel. Quick Implementation Steps (Get Started Fast) Connect WooCommerce, Slack and Google Sheets credentials in n8n. Update the WooCommerce store domain in the Configure WooCommerce Store node. Review the Slack channel and Google Sheet settings. Activate the workflow. That’s it — your weekly sales KPIs will now be generated and shared automatically. What It Does This workflow helps you track and share weekly WooCommerce performance without manual effort. It automatically calculates key sales metrics such as total orders, total revenue, average order value, refunds and top-performing products based on the previous week’s data. The workflow begins on a weekly schedule and determines the exact date range for the last completed week. Using this date range, it pulls sales orders and refund data from WooCommerce through HTTP requests. Multiple calculations are then performed to generate meaningful KPIs that are useful for both operational and leadership-level reporting. Once the KPIs are calculated, the workflow consolidates them into a clean report format. The data is saved in Google Sheets for long-term tracking and a readable summary is sent to a Slack channel so stakeholders can quickly review weekly performance. Who’s It For E-commerce store owners using WooCommerce Operations and sales teams tracking weekly performance Business managers who want automated KPI reporting Teams using Slack and Google Sheets for collaboration and reporting Requirements to Use This Workflow An active WooCommerce store with REST API access WooCommerce Consumer Key and Secret (Basic Auth) An n8n instance with scheduled workflows enabled A Slack workspace with permission to post messages A Google Sheets account with access to the target spreadsheet How the Workflow Works Weekly Schedule Trigger The workflow runs once per week. The exact day and time are configurable. Calculate Last Week’s Date Range A Code node calculates the start and end dates of the previous week. Configure WooCommerce Store The WooCommerce store domain is defined once and reused across API requests. Fetch Weekly Data from WooCommerce Orders with completed and processing status Refund data for the same date range Calculate KPIs Separate Code nodes calculate: Total orders and total revenue Average order value Refund count and refund amount Top products based on revenue Merge KPI Results All calculated KPIs are combined into a single dataset. Prepare Final KPI Report Fields Only required, clean fields are retained for reporting. Store Data in Google Sheets Each workflow run appends one new row with weekly KPI data. Send Weekly Report to Slack A formatted summary is posted to the selected Slack channel. Setup Instructions Update the WooCommerce domain in the Configure WooCommerce Store node. Verify WooCommerce API credentials in all HTTP Request nodes. Select the desired Slack channel in the Slack node. Confirm the target Google Sheet and worksheet. Adjust the weekly schedule if needed. Activate the workflow. How To Customize Nodes Weekly Sales KPI Trigger** Change the day or time to run the workflow at any point during the week. Configure WooCommerce Store** Update the domain if you move to a different store or environment. HTTP Request Nodes** Modify order statuses or add filters as needed. KPI Calculation Code Nodes** Add new metrics or adjust existing calculations. Slack Node** Send reports to a different channel or workspace. Google Sheets Node** Store data in another sheet or spreadsheet. Add-ons (Additional Features) Monthly or daily KPI reporting Email-based KPI reports Separate reports for different WooCommerce stores Alerting when revenue drops below a threshold Dashboard integration using BI tools Use Case Examples Weekly sales performance review for management Tracking revenue and refunds trends over time Sharing automated reports with remote teams Maintaining a historical KPI log in Google Sheets Supporting business decisions with consistent weekly data There can be many more use cases depending on how this workflow is customized or extended. Troubleshooting Guide | Issue | Possible Cause | Solution | |------|---------------|----------| | No data in Slack | Workflow not active | Activate the workflow | | Empty KPIs | No orders in the selected week | Verify WooCommerce data | | Incorrect dates | Schedule misconfiguration | Review trigger timing | | Google Sheets not updating | Permission issue | Reconnect Google Sheets credentials | | WooCommerce API error | Invalid credentials | Check Consumer Key and Secret | Need Help? If you need help setting up this workflow, customizing KPIs or building advanced reporting automation, our n8n workflow developers at WeblineIndia are here to help. Our team has strong expertise in n8n workflow automation, WooCommerce integrations and business intelligence reporting. Whether you want to extend this workflow or build a similar solution tailored to your business needs, feel free to reach out to WeblineIndia for expert support.

Automated Marketing Analytics Report with AI Agent How it works Transform your marketing data into actionable insights with this intelligent automation workflow. The system combines scheduled triggers with AI-powered analysis to deliver comprehensive marketing reports directly to your inbox. Key Features: Scheduled automated reporting (daily, weekly, or monthly) AI-powered data analysis using advanced language models Multi-platform marketing data integration via GoMarble MCP Intelligent report generation with actionable recommendations Direct email delivery of formatted reports Set up steps Prerequisites: GoMarble MCP account and API access Gmail account for report delivery n8n instance (cloud or self-hosted) Configuration Time: ~15-20 minutes Step-by-step setup: Connect GoMarble MCP to n8n Follow the integration guide: GoMarble n8n Setup Configure your marketing platform credentials (Google Ads, Facebook Ads, Analytics) Configure the Schedule Trigger Set your preferred reporting frequency Choose optimal timing for data availability Customize the Report Prompt Define specific metrics and KPIs to track Set analysis parameters and report format preferences Set up AI Agent Configuration Choose between Anthropic Claude or OpenAI models Configure the GoMarble MCP tools for your marketing platforms Configure Gmail Integration Set recipient email addresses Customize email template and subject line Advanced Configuration: Add conditional logic for performance thresholds Include custom data visualization requests Set up alert triggers for significant metric changes What you'll get Automated Intelligence:** Regular marketing performance analysis without manual effort Cross-Platform Insights:** Unified view of Google Ads, Facebook Ads, and Analytics data AI-Powered Recommendations:** Strategic insights and optimization suggestions Professional Reports:** Well-formatted, executive-ready marketing summaries Scalable Solution:** Easy to extend with additional marketing platforms or custom metrics Perfect for marketing teams, agencies, and business owners who want to stay on top of their marketing performance with minimal manual work.

This workflow automates the entire process of running a Print-on-Demand (POD) business by combining market trend analysis with autonomous AI design and quality control. It acts as a virtual product team that researches, designs, vets, and publishes new products to your store every week. Who is it for? This template is ideal for e-commerce entrepreneurs, content creators, and print-on-demand store owners who want to scale their merchandise inventory without spending hours on design and market research. What it does Market Research: Fetches real-time search data from Google Trends and customer preference data from Typeform. AI Design: Uses OpenAI (GPT-4o) to brainstorm t-shirt concepts based on the gathered trends, then generates high-quality vector-style images using Replicate (Flux/Stable Diffusion). Quality Control: A "Vision AI" agent analyzes the generated image, rates it on a scale of 1-10, and filters out any design scoring below 7. Dynamic Pricing & Publishing: Automatically calculates a premium price for higher-rated designs and publishes the product directly to your Printify store. Logging: Saves the product details to Airtable for your records. How to set up Configure Credentials: Open the "Workflow Configuration" node. Replace the placeholder values with your API keys for OpenAI, Replicate, Printify, and Typeform. Set Printify Details: In the "Workflow Configuration" node, add your Shop ID. In the "Publish to Printify" node, update the blueprint_id (the specific t-shirt model, e.g., Bella+Canvas 3001) and print_provider_id. Airtable Setup: Create a table with columns for Title, Description, Price, Quality Score, and Image URL, then map the IDs in the Airtable node. Requirements n8n: Cloud or Self-hosted instance. API Keys: OpenAI (with GPT-4o access), Replicate, Printify, Typeform, and Airtable. Printify Account: A connected store (e.g., Shopify, Etsy, or Pop-up). How to customize Prompt Engineering: Modify the "Chief Designer AI" system prompt to change the artistic style (e.g., from "vector" to "pixel art" or "vintage"). Pricing Logic: Adjust the JavaScript in the "Dynamic Pricing Calculator" to change your base margins or markup rules. Schedule: Change the "Weekly Schedule Trigger" to run daily or monthly depending on your volume needs.

Log meal nutrition from LINE food photos to Google Sheets using Gemini AI Who is this for Health-conscious individuals, people on a diet, and anyone who wants to track daily nutrition without manual data entry. Designed especially for LINE users (Japan, Taiwan, Thailand, etc.) who want an effortless way to monitor calories and macronutrients from meal photos. What this workflow does Send a meal photo to a LINE bot and Gemini 1.5 Flash automatically identifies the food and estimates calories, protein, fat, and carbohydrates. Each meal is logged to Google Sheets with a timestamp and user ID. The workflow calculates the running daily calorie total and warns when the personal limit is exceeded. Every Monday morning, a weekly nutrition summary with AI-generated advice is pushed via LINE automatically. How to set up Create a LINE Messaging API channel and copy the Channel Access Token Copy your LINE User ID for weekly Push messages Set up a Google Sheet with columns: Timestamp, LINE_UID, Food_Name, Meal_Type, Calories, Protein, Fat, Carbs, Confidence Get a Google Gemini API key (free tier available) Configure CALORIE_LIMIT (default 2000) and LINE_USER_ID in the Set Config Fields node Register the n8n Webhook URL in LINE Developer Console Requirements LINE Messaging API account (free tier) Google Sheets (any Google account) Google Gemini API key (free tier available) How to customize Adjust CALORIE_LIMIT in the Set Config Fields node for different dietary goals. Add a Slack notification node to share weekly reports with a fitness accountability group. Modify the Gemini prompt to track additional nutrients like fiber or sodium. Node List | # | Node Name | Type | Role | |---|-----------|------|------| | 1 | Set Config Fields | Set | Centralizes LINE token, Sheet ID, calorie limit, and user ID | | 2 | When LINE Event Received | Webhook | Receives LINE Webhook (POST) | | 3 | If Image Message | If | Branches on image vs text message | | 4 | If Report Command | If | Checks whether text is a report command | | 5 | Send Help Reply via LINE | HTTP Request | Sends usage guide as reply | | 6 | Fetch LINE Image Data | HTTP Request | Downloads image from LINE Content API | | 7 | Encode Image to Base64 | Code | Converts image binary to Base64 string | | 8 | Gemini Food Analysis Config | Gemini Chat Model | Gemini 1.5 Flash model for food analysis | | 9 | Process Food Analysis | LLM Chain | Estimates nutrition info from meal image as JSON | | 10 | Extract Nutrition Data | Code | Extracts and parses JSON from Gemini response | | 11 | Append Meal to Sheets | Google Sheets | Appends nutrition data to spreadsheet | | 12 | Read Today's Total from Sheets | Google Sheets | Retrieves all records for today | | 13 | Compute Daily Calorie Total | Code | Calculates total calories for the day | | 14 | If Over Calorie Limit | If | Checks whether daily limit is exceeded | | 15 | Send Calorie Warning via LINE | HTTP Request | Sends calorie warning reply via LINE | | 16 | Send Nutrition Info via LINE | HTTP Request | Sends nutrition info and daily total via LINE | | 17 | Weekly 9AM Schedule | Schedule Trigger | Triggers weekly report every Monday at 9 AM JST | | 18 | Read Weekly Data from Sheets | Google Sheets | Retrieves records from the past 7 days | | 19 | Summarize Weekly Stats | Code | Aggregates weekly totals, averages, and peak day | | 20 | Gemini Weekly Report Config | Gemini Chat Model | Gemini 1.5 Flash model for weekly comment | | 21 | Create Weekly Comment with LLM | LLM Chain | Generates personalized nutrition advice | | 22 | Deliver Weekly Report via LINE | HTTP Request | Sends weekly report via LINE Push | | 23 | Send Webhook Response OK | Respond to Webhook | Returns HTTP 200 to Webhook | Total: 23 nodes (+ 9 Sticky Notes) Sticky Note Compliance | # | Sticky Note Title | Color | Role | |---|-------------------|-------|------| | 1 | Main Sticky Note (Overview) | Yellow | Workflow overview, How it works, Setup steps, Customization | | 2 | Set configuration fields | White | Covers configuration setup | | 3 | Receive and verify message type | White | Covers LINE webhook and message type checks | | 4 | Download and convert image | White | Covers image fetch and Base64 encoding | | 5 | Analyze image and parse data | White | Covers Gemini analysis and data parsing | | 6 | Log and calculate nutrition | White | Covers meal logging and daily total calculation | | 7 | Notify via LINE based on calorie | White | Covers calorie warning and nutrition info LINE replies | | 8 | Weekly report scheduling and stats | White | Covers schedule trigger and weekly aggregation | | 9 | Respond to LINE webhook | White | Covers webhook response | All sticky notes use H2 headings (## ) and follow n8n public guidelines. Setup Guide 1. Create a LINE Messaging API channel Log in to LINE Developers Create a new provider and a Messaging API channel Issue a long-lived Channel Access Token and copy it Copy your User ID from the channel basic settings 2. Prepare Google Sheets Create a new spreadsheet Add the following headers in row 1: Timestamp | LINE_UID | Food_Name | Meal_Type | Calories | Protein | Fat | Carbs | Confidence Copy the spreadsheet ID from the URL (between /d/ and /edit) 3. Get a Google Gemini API key Go to Google AI Studio Create an API key (free tier available) Register it as a Google PaLM API credential in n8n 4. Configure the n8n workflow Import the workflow JSON into n8n Open Set Config Fields and enter: LINE_CHANNEL_ACCESS_TOKEN GOOGLE_SHEET_ID CALORIE_LIMIT (default: 2000) LINE_USER_ID Set up Google Sheets OAuth2 and Google PaLM API credentials 5. Register the Webhook URL Activate the workflow in n8n Copy the Webhook URL Paste it into LINE Developers Console → Messaging API settings Enable Webhook and verify the connection 6. Test Send a meal photo to your LINE bot → confirm nutrition info is returned Send "report" as text → confirm weekly summary is returned Send other text → confirm help message is returned Tags ai gemini line google-sheets health nutrition-tracking image-recognition automation

Description Automatically generate multi-jurisdiction tax summaries from Stripe invoices and sync them into Google Sheets with daily reporting. This workflow ensures compliance-ready tax data, detailed breakdowns by country/state/tax rate, and real-time Slack notifications for both success and error handling. 💳📈📢 What This Template Does Triggers daily at 2:00 AM using a scheduled cron. ⏰ Fetches paid invoices from Stripe (last 30 days). 💳 Validates data integrity before processing. ✅ Summarizes taxes by period, country, state, and rate. 🧮 Formats and logs results in Google Sheets for reporting. 📊 Sends Slack notifications for both success and failure. 📢 Key Benefits Automated tax compliance reporting. 🧾 Accurate multi-jurisdiction tracking. 🌍 Eliminates manual spreadsheet work. ⏱️ Maintains a historical audit trail. 📋 Real-time notifications keep your team informed. 🔔 Built-in error handling ensures reliability. 🛡️ Features Daily cron schedule (0 2 * * *). Stripe invoices fetched with expanded tax amounts. Intelligent grouping by period, country, state, and tax rate. Google Sheets integration with append/update logic. Success Slack message: summary totals, record count, period. Error Slack message: troubleshooting guidance and failure logs. Uses environment variables for secure configuration (GOOGLE_SHEETS_DOCUMENT_ID, SLACK_CHANNEL_ID). Requirements n8n instance (cloud or self-hosted). Stripe API credentials with invoice read access. Google Sheets OAuth2 credentials with write access. Slack API credentials with chat:write permissions. Proper tax configuration in Stripe for accurate reporting. Target Audience Finance teams handling recurring billing and tax filings. 💼 Accountants needing automated jurisdiction tax breakdowns. 📊 SaaS businesses managing global customers. 🌐 Agencies and SMEs streamlining monthly tax reporting. 🏢 Remote teams requiring real-time workflow notifications. 📲 Step-by-Step Setup Instructions Configure Stripe API credentials in n8n. Set up Google Sheets with a “Tax Summary” sheet (columns: period, country, state, tax rate, taxable amount, tax collected, processing date). Configure Slack API credentials and channel ID (e.g., tax-reports). Replace hardcoded values with environment variables for security. Import this workflow JSON into n8n. Run once manually with test invoices to validate. Enable the workflow for daily automated reporting. ✅

Who is this for This template is for sales teams, recruiters, and growth professionals who need to enrich a list of email addresses with full contact details -- names, phone numbers, and physical addresses -- and push verified new leads directly into HubSpot CRM without manual data entry. How it works The workflow accepts a list of email addresses defined in a configuration node. It submits each email to the ScraperCity People Finder API, which performs a reverse lookup to surface associated names, phones, and addresses. Because the scrape runs asynchronously, the workflow polls the job status every 60 seconds until completion. Once the scrape succeeds, it downloads the CSV results, parses each row into structured contact records, removes duplicates, and upserts every new contact into HubSpot CRM. How to set up Create a ScraperCity API Key credential in n8n (HTTP Header Auth, header name Authorization, value Bearer YOUR_KEY). Create a HubSpot App Token credential in n8n. Open the Configure Lookup Parameters node and replace the example emails with your target list. Execute the workflow manually and monitor the polling loop until results appear in HubSpot. Requirements ScraperCity account with People Finder access (app.scrapercity.com) HubSpot account with a valid private app token n8n instance (cloud or self-hosted) How to customize the workflow Add more emails to the Configure Lookup Parameters node or replace it with a Google Sheets or webhook trigger to feed emails dynamically. Adjust the Wait Before Retry node duration if your scrapes consistently finish faster or slower. Extend the Map Contact Fields node to populate additional HubSpot properties such as lifecycle stage or lead source.

Receive WhatsApp messages via Whapi, generate AI replies with a local Ollama model, log conversations in Google Sheets, and auto-capture leads — all without touching a cloud LLM. This n8n template builds a fully automated WhatsApp AI CRM using Whapi.cloud for messaging and Ollama for 100% local AI inference — no OpenAI costs, no data leaving your server. How it works A Webhook node receives inbound WhatsApp messages from Whapi.cloud. A Code node extracts the sender's phone, name, message text, and filters out outbound/non-text messages. An IF node ensures only real inbound text messages from customers are processed. Google Sheets is used to fetch that customer's full conversation history, enabling memory across sessions. A Code node builds a full prompt — system instructions + conversation history + new message — passed to the AI model. Ollama (via LangChain LLM Chain node) generates a contextual reply using a local model (default: gemma3:1b). The user message and AI reply are each appended to Google Sheets as conversation history logs. A separate Google Sheets upsert captures or updates the lead record with phone and name. The AI reply is sent back to the customer via Whapi's HTTP API. How to use Set up a Whapi.cloud account and connect a WhatsApp number. Point the webhook to your n8n webhook URL. Create a Google Sheet with a History tab (columns: Phone, Name, Role, Message, Timestamp) and a Leads tab (columns: Phone, Name, CreatedAt). Add your Google Sheets credentials and replace YOUR_GOOGLE_SHEET_ID in the relevant nodes. Run Ollama locally or on your server. Pull the model: ollama pull gemma3:1b. Update the model name in the Ollama node if using a different model. Customise the system prompt inside the Build AI Prompt node to match your business (real estate, support, bookings, etc.). Activate the workflow and send a WhatsApp message to test. Requirements Whapi.cloud account (WhatsApp Business API) Ollama running locally or on a self-hosted server Google Sheets (with OAuth2 credentials connected in n8n) Customising this workflow Switch AI models: Swap gemma3:1b for any Ollama-supported model like llama3, mistral, or phi3 depending on your hardware. Change the industry: Edit the system prompt in Build AI Prompt to serve any business — bookings, customer support, sales qualification, etc. Upgrade the CRM: Replace Google Sheets with Airtable, Notion, or a real CRM (HubSpot, Pipedrive) by swapping out the Sheets nodes. Add handoff logic: Insert a condition to escalate to a human agent if the message contains keywords like "speak to someone" or "human". Multi-language: The system prompt already instructs the AI to reply in the customer's language — no extra setup needed. Who is this for It's designed for service businesses (real estate, consultants, agencies) that want to respond to inbound WhatsApp leads instantly, log conversations, and build a simple CRM — all from a single workflow.

This workflow automates the prioritization and escalation of customer support tickets. It acts as an intelligent triage system that identifies high-value customers and potential churn risks in HubSpot, syncs them to Jira, and enforces response times via Slack alerts. Who’s it for This workflow is ideal for Customer Success (CS) teams, Support Leads, and Account Managers who need to ensure VIP clients and critical issues receive immediate engineering or support attention without manual monitoring. How it works The workflow runs on a schedule to process new tickets: Monitor: Checks HubSpot every 10 minutes for newly created tickets. Enrich: Retrieves the associated Contact’s data, specifically looking for Annual Revenue and Lifecycle Stage. Analyze: A Code node evaluates the ticket content and customer value. It assigns a "Severity" level (Critical/High/Normal) based on revenue thresholds (>10k) or churn-risk keywords (e.g., "refund," "lawyer," "cancel"). Action: Creates a formatted Jira task with all context included and notifies a Slack channel. SLA Check: Waits 15 minutes to allow for a response. Escalate: If the Jira ticket status hasn't changed to "In Progress" or "Done" after the wait period, it triggers a high-priority "Churn Risk Escalation" alert in Slack. Requirements HubSpot** account (CRM and Service Hub). Jira Software Cloud** account. Slack** workspace. How to set up Configure your credentials for HubSpot, Jira Software, and Slack. In the HubSpot: Get Associations and Get Contact Data nodes, ensure the properties match your internal naming conventions. In the Jira: Create Triage Ticket node, select your specific Project and Issue Type from the dropdown lists. In the Slack nodes, select the channel where you want alerts to be posted. How to customize the workflow Integrate other tools:** This system is modular and works with any other tool (contact us for help). You can easily replace the nodes to use your specific stack: CRM: Pipedrive, WeClapp Ticketing System: Zendesk, Intercom, FreshDesk Modify Logic:* Open the *Code: Calculate Severity** node to change the revenue threshold (currently set to 10,000). You can also replace the manual keyword matching with an LLM (AI) node to intelligently analyze ticket sentiment and intent. Adjust SLA:* Change the duration in the *Wait: Response Timer** node if your Service Level Agreement (SLA) differs from the default 15 minutes. Change Status Check:* Update the *Check: Escalation Needed?** node if your team uses different Jira statuses (e.g., "Under Review" instead of "In Progress") to determine if a ticket is being handled.

How It Works The workflow starts with a scheduled trigger that activates at set intervals. Behavioral data from multiple sources is parsed and sent to the MCDN routing engine, which intelligently assigns leads to the right teams based on predefined rules. AI-powered scoring evaluates each prospect’s potential, ensuring high-quality leads are prioritized. The results are synced to the CRM, and updates are reflected on an analytics dashboard for real-time visibility. Setup Steps Trigger: Define schedule frequency. Data Fetch: Configure APIs for all behavioral data sources. MCDN Router: Set routing rules, thresholds, and team assignments. AI Models: Connect OpenAI/NVIDIA APIs and configure scoring prompts. CRM Integration: Enter credentials for Salesforce, HubSpot, or other CRMs. Dashboard: Link to analytics tools like Tableau or Google Sheets for reporting. Prerequisites API credentials: NVIDIA AI, OpenAI, CRM platform; data sources; spreadsheet/analytics access Use Cases Lead prioritization for sales teams; customer segmentation; automated routing; Customization Adjust routing rules, add custom scoring models, modify team assignments, expand data sources, integrate additional AI providers Benefits Reduces manual lead routing 90%; improves scoring accuracy; accelerates sales cycle; enables data-driven team assignments;

Quick overview This workflow handles inbound WhatsApp insurance inquiries, uses OpenAI to converse with leads and remember context per phone number, then extracts a qualification decision, score, and summary, upserts qualified leads to HubSpot, and alerts a Slack channel when a lead requests a human. How it works Triggers whenever a new WhatsApp message is received via WhatsApp Business Cloud. Uses OpenAI to reply in the lead’s language, collect consent and key qualifying details, and maintain conversation context per phone number. Sends the assistant’s reply back to the lead on WhatsApp. Uses OpenAI again to convert the latest message and reply into structured lead data (qualified flag, 0–100 score, intent, wants-human flag, email, and a one-sentence summary). Upserts the lead as a HubSpot contact with the AI summary and score when the lead is marked qualified. Posts a handover alert to Slack when the lead asks for a human or the conversation indicates a human is needed. Setup Connect credentials for WhatsApp Business Cloud, OpenAI, HubSpot, and Slack. Set your WhatsApp Phone Number ID in the WhatsApp send message step and ensure the WhatsApp trigger is subscribed to message updates. Select the Slack channel to receive handover alerts. Review and customize the assistant’s system prompt (persona, consent/STOP handling, and qualifying questions) to match your compliance and sales process. Requirements WhatsApp Business Cloud account (Meta) with a connected phone number ID OpenAI API key (works great with gpt-4o-mini) HubSpot account (free tier is fine) Slack workspace + a channel for sales alerts n8n with the LangChain / AI nodes available (cloud or self-hosted v1.x+) Customization Swap the CRM: replace the HubSpot node with Salesforce, Pipedrive, or an HTTP Request to a custom REST API Edit the persona and qualifying questions in the "AI Insurance Assistant" node to fit any industry (real estate, solar, healthcare, etc.) Change the qualification threshold/logic in the "Qualified Lead?" and "Wants a Human?" IF nodes Add omnichannel fallback: a Twilio call, SendGrid email, or Calendly booking link off the routing branches Route handover to email or a ticketing tool instead of Slack Add a Google Sheets / database node to log every conversation for analytics Additional info This template uses natural-language qualification (not button trees) with per-contact memory, so it handles multi-message, multi-day conversations and auto-detects the lead's language. It includes a built-in consent prompt and STOP opt-out for POPIA/GDPR-friendly handling. No credentials are bundled — connect your own WhatsApp, OpenAI, HubSpot and Slack accounts, set your WhatsApp phone number ID on the two WhatsApp nodes, and activate. Each inbound message uses ~1–2 OpenAI calls, so a low-cost model is recommended.