Workflow Templates

AI Customer Support Triage with Gmail, OpenAI, Airtable & Slack How it Works This workflow monitors your Gmail support inbox every minute, automatically sending each unread email to OpenAI for intelligent analysis. The AI evaluates sentiment (Positive/Neutral/Negative/Critical), urgency level (Low/Medium/High/Critical), categorizes requests (Technical/Billing/Feature Request/Bug Report/General), extracts key issues, and generates professional response templates. The system calculates a priority score (0-110) by combining urgency and sentiment weights, then routes tickets accordingly. Critical issues trigger immediate Slack alerts with full context and 30-minute SLA reminders, while routine tickets post to standard monitoring channels. Every ticket logs to Airtable with complete analysis and thread tracking, then updates a Google Sheets dashboard for real-time analytics. A secondary AI pass generates strategic insights (trend identification, risk assessment, actionable recommendations) and stores them back in Airtable. The entire process takes seconds from email arrival to team notification, eliminating manual triage and ensuring critical issues get immediate attention. Who is this for? Customer support teams needing automated prioritization for high email volumes SaaS companies tracking support metrics and response times Startups with lean teams requiring intelligent ticket routing E-commerce businesses managing technical, billing, and return inquiries Support managers needing data-driven insights into customer pain points Setup Steps Setup time:** 20-30 minutes Requirements:** Gmail, OpenAI API key, Airtable account, Google Sheets, Slack workspace Monitor Support Emails: Connect Gmail via OAuth2, configure INBOX monitoring for unread emails AI Analysis Engine: Add OpenAI API key, system prompt pre-configured for support analysis Parse & Enrich Data: JavaScript code automatically calculates priority scores (no changes needed) Route by Urgency: Configure routing rules for critical vs routine tickets Slack Alerts: Create Slack app, get bot token and channel IDs, replace placeholders in nodes Airtable Database: Create base with "tblSupportTickets" table, add API key and Base ID (replace appXXXXXXXXXXXXXX) Google Sheets Dashboard: Create spreadsheet, enable Sheets API, add OAuth2 credentials, replace Sheet ID (1XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX) Generate Insights: Second OpenAI call analyzes patterns, stores insights in Airtable Test: Send test email, verify Slack alerts, check Airtable/Sheets data logging Customization Guidance Priority Scoring:** Adjust urgency weight (25) and sentiment weight (10) in Code node to match your SLA requirements Categories:** Modify AI system prompt to add industry-specific categories (e.g., healthcare: appointments, prescriptions) Routing Rules:** Add paths for High urgency, VIP customers, or specific categories Auto-Responses:** Insert Gmail send node after routine tickets for automatic acknowledgment emails Multi-Language:** Add Google Translate node for non-English support VIP Detection:** Query CRM APIs or match email domains to flag enterprise customers Team Assignment:** Route different categories to dedicated Slack channels by department Cost Optimization:** Use GPT-3.5 (~$0.001/email) instead of GPT-4, self-host n8n for unlimited executions Once configured, this workflow operates as your intelligent support triage layer—analyzing every email instantly, routing urgent issues to the right team, maintaining comprehensive analytics, and generating strategic insights to improve support operations. Built by Daniel Shashko Connect on LinkedIn

Description This workflow turns scattered user feedback into a structured product backlog pipeline. It collects feedback from three channels (Telegram bot, Google Form/Sheets, and Gmail), normalizes it, and sends it to an AI model that: Classifies the feedback (bug, feature request, question, etc.) Extracts sentiment and pain level Estimates business impact and implementation effort Generates a short summary Then a custom RICE-style priority score is computed, a Jira ticket is created automatically, a Notion page is generated for documentation, and a monthly product report is sent by email to stakeholders. It helps product & support teams move from “random feedback in multiple tools” to a repeatable, data-driven product intake process with zero manual triage. Context In most teams, feedback is: spread across emails, forms, and chat messages manually copy–pasted into Jira (when someone remembers) hard to prioritize objectively nearly impossible to review at the end of the month This workflow solves that by: Centralizing feedback from Telegram, Google Forms/Sheets, and Gmail Automatically normalizing all inputs into the same JSON structure Using AI to categorize, tag, summarize, and score each request Calculating a RICE-based priority adapted to your tiers (free / pro / enterprise) Creating a Jira issue with all the context and acceptance criteria Generating a Notion page for each feedback+ticket pair Sending a monthly “Product Intelligence Report” by email with insights & recommendations The result: less manual work, better prioritization, and a clear story of what users are asking for. Target Users This template is designed for: Product Managers and Product Owners SaaS teams with multiple feedback channels Support / CS teams that need a structured escalation path Project Managers who want objective, data-driven prioritization Any team that wants “feedback → backlog” automation without building a custom platform Technical Requirements You’ll need: Google Sheets credential Gmail credential Telegram Bot + Chat ID Google Form connected to a Google Sheet Jira credential (Jira Cloud) Notion credential OpenAI/ Anthropic credential for the AI analysis node An existing Jira project where tickets will be created A Notion database or parent page where feedback pages will be stored Workflow Steps The workflow is organized into four main sections: 1) Triggers (Multi-channel Intake) Telegram Trigger – Listens for new messages sent to your bot Google Form / Sheet Trigger – Listens for new form responses / rows Gmail Trigger – Listens for new emails matching your filter (e.g. [Feedback] in subject) All three paths send their payloads into a “Data Normalizer” node that outputs a unified structure: 2) Request Treated and Enriched (AI Analysis) Instant Reply (Telegram only) – Sends a quick “Thanks, we’re analysing your feedback” message User Enrichment – Enriches user tier based on mapping Message a Model (AI) classifies the feedback extracts tags scores sentiment, pain, business impact, effort generates a short summary & acceptance criteria JSON Parse / Merge – Merges AI output back into the original feedback object 3) Priority Calculation & Jira Ticket Creation Priority Calculator applies a RICE-style formula using: pain level business impact implementation effort user tier weight assigns internal priority: P0 / P1 / P2 / P3 maps to Jira priority: Highest / High / Medium / Low Create Jira Issue – Creates a ticket with: summary from AI description including raw feedback, AI analysis, and RICE breakdown labels based on tags priority based on the calculator Post-processing – Prepares a clean payload for notifications & logging IF (Source = Telegram) – Sends a rich Telegram message back to the user with: Jira key + URL category, priority, RICE score, tags, and estimated handling time Append to Google Sheet (Analytics Log) – Logs each feedback with: source, user, category, sentiment, RICE score, priority, Jira key, Jira URL Create Notion Page – Creates a documentation page linking: the feedback the Jira ticket AI analysis acceptance criteria 4) Monthly Reporting (Product Intelligence Report) Monthly Trigger – Runs once a month Query Google Sheet – Fetches all feedback logs for the previous month Aggregate Monthly Stats – Computes: feedback volume breakdown by category / sentiment / source / tier / priority average RICE, pain, and impact top P0/P1 issues and top feature requests Message a Model (AI) – Generates a written “Product Intelligence Report” with: executive summary key insights & trends top pain points strategic recommendations Parse Response: Extracts structured insights + short summary Create Notion Report Page with: metrics, charts-ready tables, insights, and recommendations Append Monthly Log to Google Sheet – Stores high-level stats for historical tracking Send Email with a formatted HTML report to stakeholders with: key metrics top issues recommendations link to the full Notion report Key Features Multi-channel intake: Telegram + Google Forms/Sheets + Gmail AI-powered triage: automatic category, sentiment, tags, and summary RICE-style priority scoring with tier weighting Automatic Jira ticket creation with full context Notion documentation for each feedback and for monthly reports Google Sheets analytics log for exploration and dashboards Monthly “Product Intelligence Report” sent automatically by email Designed to be adaptable: you can plug in your own labels, tiers, and scoring rules Expected Output When the workflow is running, you can expect: A Jira issue created automatically for each relevant feedback A confirmation email A Telegram confirmation message when the feedback comes from Telegram A Google Sheet filled with normalized feedback and scoring data A Notion page per feedback/ticket with AI analysis and acceptance criteria Every month: a Notion “Monthly Product Intelligence Report” page a summary email with key metrics and insights for your stakeholders How it works Trigger – Listens to Telegram / Google Forms / Gmail Normalize – Converts all inputs to a unified feedback format Enrich with AI – Category, sentiment, pain, impact, effort, tags, summary Score – Computes RICE-style priority and maps to Jira priority Create Ticket – Opens a Jira issue + Notion page + logs to Google Sheets Notify – Sends Telegram confirmation (if source is Telegram) Report – Once a month, aggregates everything and sends a Product Intelligence Report Tutorial Video Tutorial video: Watch the Youtube Tutorial video About me I’m Yassin a Project & Product Manager Scaling tech products with data-driven project management. 📬 Feel free to connect with me on Linkedin

Introduction Automate peer review assignment and grading with AI-powered evaluation. Designed for educators managing collaborative assessments efficiently. How It Works Webhook receives assignments, distributes them, AI generates review rubrics, emails reviewers, collects responses, calculates scores, stores results, emails reports, updates dashboards, and posts analytics to Slack. Workflow Template Webhook → Store Assignment → Distribute → Generate Review Rubric → Notify Slack → Email Reviewers → Prepare Response → Calculate Score → Store Results → Check Status → Generate Report → Email Report → Update Dashboard → Analytics → Post to Slack → Respond to Webhook Workflow Steps Receive & Store: Webhook captures assignments, stores data. Distribute & Generate: Assigns peer reviewers, AI creates rubrics. Notify & Email: Alerts via Slack, sends review requests. Collect & Score: Gathers responses, calculates peer scores. Report & Update: Generates reports, emails results, updates dashboard. Analyze & Alert: Posts analytics to Slack, confirms completion. Setup Instructions Webhook & Storage: Configure endpoint, set up database. AI Configuration: Add OpenAI key, customize rubric prompts. Communication: Connect Gmail, Slack credentials. Dashboard: Link analytics platform, configure metrics. Prerequisites OpenAI API key Gmail account Slack workspace Database or storage system Dashboard tool Use Cases University peer review assignments Corporate training evaluations Research paper assessments Customization Multi-round review cycles Custom scoring algorithms Benefits Eliminates manual distribution Ensures consistent evaluation

Automate admin tasks for manufacturing companies by processing emails, extracting key data from invoices & purchase orders, and delivering instant alerts via Gmail and Telegram. 📝 Description This workflow automatically: Fetches incoming emails from Gmail Classifies emails (invoices, purchase orders, payment follow-up, etc.) using AI Sends tailored auto-replies based on content and attachment presence Extracts structured data from attached invoices/POs (PDFs etc.) Delivers alerts and document files to your team via Telegram Logs or routes data for further use in accounting or internal systems ⚙️ Pre-Conditions & Requirements Before using this workflow, you need: Gmail Account with API access (for OAuth2 authentication) Telegram Bot API Token (create a Telegram bot and get your API key) Optional: API credentials for Google Sheets or other data sinks if you want to log extracted data OpenRouter API credentials (for LLM-powered nodes, if used) Access to an n8n instance (cloud or self-hosted) 🛠 Setup Instructions Import the Workflow: Download the JSON file and import it into your n8n instance. Connect Accounts: Configure the Gmail Trigger node with your Gmail OAuth2 credentials Set up the Telegram node with your bot API token Set Required Variables: Adjust AI instructions or prompt text if needed (for your company’s tone/templates) Customize labels, keywords, or filters in code nodes for your use case Set target Telegram chat/group IDs Test the Workflow: Send a sample email with attachments to your Gmail account Confirm that emails are classified, replies are sent, and Telegram notifications/mobile alerts are delivered as expected Review and Connect Optional Modules: For logging or archiving extracted data, connect additional “Google Sheets” or “Webhook” nodes as needed 🧩 Customization Tips Modify Email Categories: Update AI prompt instructions or filters to add/change labels (“Vendor Query,” “Partial Payment,” etc.) Attachment Handling: Edit the code node logic to detect and process additional file types (DWG, XLSX, ZIP, etc.) Notification Logic: Change the Telegram destination or add Slack/Microsoft Teams for broader team alerts Data Logging: Add nodes for CRM, inventory, or ERP integration (push to your accounting or workflow management tool) Example AI Prompt (for categorization) text You are the personal emailing assistant for Zenith Engineering, a manufacturing company... Your tasks: Categorize each email by priority Draft polite, professional replies... Identify and label attachments such as invoices, POs, drawings Response should be a valid JSON object: {"Label":"Important", "Response":"..."} If you have any doubts and questions let me know : smonu2303@gmail.com from Pune. Linkedin: https://www.linkedin.com/in/raj-more-171560bb/

Description This workflow intelligently analyzes incoming Gmail emails, classifies intent using GPT-4, and sends real-time Slack notifications while logging structured data into Google Sheets. It provides a smart, AI-assisted communication workflow that saves time and ensures no important email is overlooked. 🤖💌📊 What This Template Does Monitors Gmail for unread or new incoming emails. 📥 Extracts sender, subject, and body content for processing. ✉️ Uses GPT-4 to analyze email intent and determine priority. 🧠 Formats key insights (sender, summary, intent, urgency). 🧾 Posts structured summaries and priority alerts in Slack. 💬 Logs all processed emails with classification results in Google Sheets. 📊 Sends error notifications in case of API or parsing failures. 🚨 Key Benefits ✅ AI-driven email intent classification for smarter response handling. ✅ Seamless Slack notifications for high-priority or urgent emails. ✅ Maintains a centralized record of email insights in Google Sheets. ✅ Reduces response time by surfacing critical messages instantly. ✅ Minimizes manual email triage and improves team productivity. Features Real-time Gmail monitoring for unread emails. AI-based classification using GPT-4. Slack notifications with rich formatting and urgency tagging. Google Sheets logging for tracking and analytics. Built-in error handling with notification alerts. Modular setup for easy credential reuse across projects. Requirements Gmail OAuth2 credentials with inbox read access. Slack Bot token with chat:write and channels:history scopes. Google Sheets OAuth2 credentials for data logging. Azure OpenAI (or OpenAI GPT-4) API credentials. n8n instance (cloud or self-hosted). Target Audience Customer support teams managing shared inboxes. Operations teams tracking email-based requests. Sales or marketing teams prioritizing inbound leads. AI automation enthusiasts optimizing email workflows. Remote teams using Slack for real-time updates. Step-by-Step Setup Instructions Connect your Gmail, Slack, Google Sheets, and GPT-4 credentials in n8n. 🔑 Specify the Gmail search filter (e.g., is:unread) for tracking new emails. 📬 Add your Slack channel ID in the notification node. 💬 Set your Google Sheet ID and tab name for logging results. 📊 Run once manually to verify connection and output structure. ✅ Enable the workflow for continuous, real-time execution. 🚀

Instant, automated scheduling. This AI Scheduling Agent manages real-time appointments, availability checks, and rescheduling across Google Calendar and Sheets, eliminating human hold times. 🎯 Problem Statement Traditional call center or online booking systems often lack the flexibility to handle complex, multi-step customer requests like rescheduling, checking dynamic availability across multiple time slots, or handling context-aware conversational booking. This leads to friction, missed bookings, and high administrative overhead for service companies like HVAC providers. ✨ Solution This workflow deploys a sophisticated AI Scheduling Agent that acts as a virtual receptionist. It uses the Language Model's (LLM) "tool-use" capability to intelligently execute complex, sequential business logic (e.g., check availability before booking, find existing events before rescheduling) and manages the entire lifecycle of a service appointment, from initial inquiry to final confirmation. ⚙️ How It Works (Multi-Step Execution) Trigger: A customer request (e.g., from an external voice or text platform) hits the Webhook Trigger with intent details (e.g., tool\_request: 'reschedule\_appointment'). Agent Logic: The Receptionist Agent uses a strict system prompt and its internal tools to formulate an execution plan. It maintains conversational state via the simple-memory node. Tool Execution (Example: Reschedule): The Agent executes a predefined sequence of private tools: find\_old\_event: Locates the existing booking ID using the customer's email. check\_calendar: Verifies the proposed new time is available (2-hour window). reschedule\_appointment: Updates the calendar event. log\_lead: Updates the central Google Sheet. Synchronous Response: The Agent sends a confirmation or follow-up question via the respond\_to\_webhook node. Asynchronous Confirmation: The log\_lead action triggers a secondary workflow that composes a professional email via a second LLM (Anthropic) and sends it to the customer via Gmail, followed by an internal alert via Google Chat. 🛠️ Setup Steps Credentials: AI/LLM: Configure credentials for the Language Model used (OpenAI or Gemini) for the core Agent. Google Services: Set up OAuth2 credentials for Google Calendar (for booking/checking), Google Sheets (for logging), and Gmail (for customer confirmation). Google Calendar: Specify the technician's calendar ID (bhuvaneshx13@gmail.com in the template) in all Calendar nodes. Google Sheets: Create a new Google Sheet to serve as the Lead Log and update the Document ID and Sheet Name in the log\_lead and log\_lead\_trigger nodes. Tool Configuration: Review and customize the Agent's system prompt in the Receptionist node to align time zone rules (currently Asia/Kolkata - IST) and business hours (9:00 AM to 6:00 PM) with your operations. ✅ Benefits Increased Efficiency: Fully automates complex scheduling and rescheduling, freeing up human staff. Contextual Service: AI handles multi-turn conversations and adheres to strict business rules (e.g., 2-hour slots, maximum tool usage). Data Integrity: Ensures all bookings are immediately logged to Google Sheets, maintaining a centralized record (CRM). Professional Flow: Provides immediate confirmation to the customer via email and instant notification to the internal team via chat. 🚀 Other Use Cases The underlying multi-step, tool-execution pattern is highly versatile and can be adapted for any service industry requiring complex, rules-based scheduling: Real Estate:** Scheduling property viewings (Check agent availability → Book viewing → Send directions). HVAC Services:** Managing maintenance and repair visits (Diagnose issue type → Match with qualified technician → Check part availability → Schedule visit → Send service confirmation). Medical/Dental:** Booking patient appointments (Check insurance eligibility → Check doctor availability → Book → Send pre-visit forms). Legal Services:** Intake for consultations (Collect client issue → Check specialist availability → Book → Send retainer agreement). Automotive Repair:** Scheduling service bays (Check bay and mechanic availability → Book → Update internal service board).

Promo Seeker automatically finds, verifies, and delivers active promo codes to users via Telegram or email using SerpAPI + Gemini (OpenRouter). Saves hours of manual searching and deduplicates results into an n8n Data Table for fast reuse. Why Use This Workflow? Time Savings: Reduces manual promo hunting from 2 hours to 5 minutes per query. Cost Reduction: Cuts reliance on paid scraping tools or manual services — potential savings of $50–$200/month. Error Prevention: Cross-references sources and enforces a 30‑day recency filter to reduce expired-code hits by ~60% vs single-source checks. Scalability: Handles hundreds of queries per day with Data Table upserts and optional scheduling for continuous discovery. Ideal For Marketing / Growth Managers:** Quickly discover competitor or partner discounts to promote in campaigns. Customer Support / Operations:** Respond to user requests with verified promo codes via Telegram or email. Affiliate / Content Teams:** Aggregate and maintain a clean promo feed for newsletters or site widgets. How It Works Trigger: Incoming request via Webhook, Telegram message, Google Form submission, or scheduled run. Data Collection: The LangChain agent uses SerpAPI search results and Gemini (OpenRouter) to locate recent promo codes. Processing: Filter for recency (last 30 days), extract code, value, terms, and expiry. Intelligence Layer: Gemini 2.5 Pro (OpenRouter) + LangChain agent structure and verify results, outputting a standardized JSON. Output & Delivery: If a code exists in the Data Table, notify the requester via Telegram and Gmail; otherwise, return results and upsert them into the Data Table. Storage & Logging: Results stored/upserted in an n8n Data Table to prevent duplicates and enable fast lookups. Setup Guide Prerequisites | Requirement | Type | Purpose | |-------------|------|---------| | n8n instance | Essential | Execute the workflow — import JSON to your n8n instance | | SerpAPI account | Essential | Web search results for promo code discovery | | OpenRouter (Gemini) account | Essential | Language model (Gemini 2.5 Pro) for extraction and verification | | Telegram Bot (BotFather) | Essential | Receive queries and send promo notifications | | Gmail OAuth2 | Essential | Send rich email notifications | | n8n Data Tables | Essential | Store and deduplicate promo code records | Get your n8n instance here: n8n instance — import the JSON and begin configuration. (Repeat link for convenience) n8n instance Installation Steps Import the JSON workflow into your n8n instance. Configure credentials (use n8n's Credentials UI — do NOT paste keys into nodes): SerpAPI: paste your SerpAPI API Key from your SerpAPI dashboard. OpenRouter API: paste your OpenRouter API Key (for Gemini 2.5 Pro). Telegram API: create bot via @BotFather, then add Bot Token to Telegram credentials. Gmail OAuth2: use n8n's Gmail OAuth2 credential flow and authorize the account. Update environment-specific values: Webhook path: /v1/promo-seeker (configured in the Webhook node) or replace with your preferred path. Data Table ID: point to your own Data Table Form/webhook recipient fields (email/chatId mappings). Customize settings: Adjust the LangChain agent prompt (Promo Seeker Agent) for different recency windows or regional focus. Change max results/limit on the Data Table node (default limit = 3). Test execution: Trigger via Telegram or a POST to the webhook with sample payload: { "platform":"example.com", "email":"you@domain.com" } Confirm notifications arrive and Data Table rows are upserted. Technical Details Core Nodes | Node | Purpose | Key Configuration | |------|---------|-------------------| | SerpAPI | Fetch web search results | Provide credential; adjust search params in agent prompt | | Gemini 2.5Pro (OpenRouter) | Extract & verify promo details | Use OpenRouter credential; model google/gemini-2.5-pro | | Promo Seeker Agent (LangChain) | Orchestrates search + parsing | System prompt enforces 30‑day recency & result format | | Structured Output Parser | Validates agent output | JSON schema example for platform/code/value/terms/validUntil | | Data Table (Get row(s)) | Lookup existing promos | Filters by platform; limit = 3 | | If (Code Exist?) | Branching logic | Checks existence of platform field | | Data Table (Upsert row(s)) | Insert or update promo | Mapping from agent output to Data Table columns | | Telegram Trigger / Telegram | Receive queries & notify users | Webhook-based trigger; parse_mode = HTML for messages | | Gmail | Send rich HTML emails | Uses Gmail OAuth2 credential | | Webhook / Form Trigger | Alternate inputs | Webhook path /v1/promo-seeker and Form trigger for manual submissions | Workflow Logic On trigger, the Platform Set node normalizes the incoming query and receiver. Get row(s) checks Data Table for existing promos. If found: notify via Telegram and send Gmail (email template included). If not found: the Promo Seeker Agent runs SerpAPI searches, parses structured output, then Upsert row(s) saves results and notifications are sent. Structured Output Parser enforces correct JSON to avoid bad upserts. Customization Options Basic Adjustments Recency window: change the agent prompt to 7/14/30 days. Result limit: increase Data Table Get limit or change Upsert batch size. Advanced Enhancements Add Slack or Microsoft Teams notifications (moderate complexity). Add caching layer (Redis) to reduce repeated SerpAPI calls (advanced). Parallelize searches across multiple search engines (higher API usage & complexity). Performance & Optimization | Metric | Expected Performance | Optimization Tips | |--------|----------------------|-------------------| | Execution time | 8–30s per new search (depends on SerpAPI + LM response) | Reduce SerpAPI page depth; cache recent results | | API calls | 3–10 SerpAPI calls per complex query | Batch queries; use higher-quality search params | | Error handling | Agent retries on malformed output | Use retry nodes and set onError strategy for downstream nodes | Troubleshooting | Problem | Cause | Solution | |---------|-------|----------| | No results returned | Query too vague or rate-limited API | Improve query specificity; check SerpAPI quota | | Gmail send fails | OAuth scope not granted or token expired | Reconnect Gmail OAuth2 credential in n8n | | Telegram webhook not firing | Incorrect bot token or webhook setup | Recreate Telegram credential and check bot permissions | | Duplicate rows | Upsert mapping mismatch | Ensure promoCode mapping in Upsert matches structured output | | Agent returns malformed JSON | LM prompt too permissive | Tighten the agent system prompt and validate with Structured Output Parser | Created by: khaisa Studio Category: Marketing Automation Tags: promo-codes, coupons, serpapi, telegram, gmail, openrouter, data-tables Need custom workflows or help adapting this template? 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Never miss a competitor price change again. This advanced workflow automates the most difficult aspect of market monitoring: intelligently extracting structured pricing data from complex, dynamic competitor websites and comparing it against your historical baseline. It sends instant, conditional alerts only when a significant price shift is detected. The workflow uses Decodo for dynamic scraping, Gemini for reliable data parsing, and Google Sheets for robust historical state management. ✨ Key Features AI-Powered Extraction:* Uses *Gemini 2.5 Flash** to analyze raw, noisy website HTML and output a clean JSON array of plan names, prices, and features, bypassing brittle CSS selectors. Historical Comparison:** Automatically retrieves the price from the previous workflow run and calculates the percentage difference (diff) for every single plan item. Edge Case Handling:* Includes specific code logic to prevent errors and flag crucial events like a *"Free-to-Paid"** plan transition (division by zero). Conditional Alerting:** Sends immediate Slack notifications only when the price change exceeds your predefined percentage threshold. State Management:* Uses Google Sheets to automatically *shift data** (Current Price $\rightarrow$ Old Price) to maintain the historical baseline for the next scheduled execution. ⚙️ How it Works (The Monitoring Loop) Setup & Sourcing: The workflow is executed on a schedule, defining the global alert threshold and retrieving the list of target URLs from a Google Sheet. Scraping (Dynamic): Decodo runs with JavaScript rendering ON to fetch the complete, dynamic HTML of the pricing page. AI Structuring: Gemini receives the raw HTML and uses a strict System Prompt to extract a clean JSON array of all pricing plans. Comparison & Calculation: A Code Node parses the current plan list and the list from the previous run (stored in Sheets). It calculates the percentage change for every matching plan. Alert Decision: An If Node checks the calculated change against the threshold. If the condition is met, the filtered alert proceeds to Slack. Data Shift & Log: The final Sheets Update node shifts the current plan data to the "Last Plans" column and moves the previous "Last Plans" to the "Old Plans" column, setting the new baseline for the next scheduled check. 📥 Decodo Node Installation The Decodo node is used three times in this workflow for precision scraping and searching. Find the Node: Click the + button in your n8n canvas. Search: Search for the Decodo node and select it. Credentials: When configuring the first Decodo node, use your API key (obtained with the 80% discount coupon). 🎁 Exclusive Deal for n8n Users To run this workflow, you require a robust scraping provider. We have secured a massive discount for Decodo users: Get 80% OFF the 23k Advanced Scraping API plan. Coupon Code: ATTAN8N Sign Up Here: Claim 80% Discount on Decodo 🛠️ Setup Instructions Credentials: Obtain API keys for Decodo (using the coupon below), Google Sheets, and Slack. Google Sheets Setup: Create a sheet with the following required columns for tracking (one row per URL): Name URL Old Plans (JSON String) Last Plans (JSON String) Updated At (Date) Global Configuration: Open the Config: Alert Parameters node to set your alert_threshold (e.g., 10). I understand. To complete the final template description for your Competitor Price Monitoring workflow, here is the dedicated How to Adapt the Template section, focusing on functional changes a user can make for advanced monitoring. ➕ How to Adapt the Template The workflow is currently configured for maximum efficiency and stability. To expand its functionality or change its dependencies, you can implement the following adaptations: Change Database for Storage:* Replace the *Google Sheets* nodes with *Airtable* or *Notion** nodes for historical storage. Since your comparison logic relies on the JSON string being saved and retrieved, you will only need to change the read/write operations (the Code logic remains the same). Change Alert Channel:* Easily swap the *Slack* node with a *Gmail, **Discord, or Pushover node to deliver critical price alerts to a different team or application. Dynamic Thresholds:* Modify the *Config: Alert Parameters* to include separate fields for price *increases (e.g., alert_increase_threshold) and price decreases (e.g., alert_decrease_threshold), allowing you to track competitor sales differently than price hikes. Advanced Price Filtering:* Adjust the code logic in *Code: Isolate Pricing Section** to target specific currency symbols (e.g., €, £) or to filter out prices that appear to be marked as promotional (e.g., text containing "SALE" or "Discount"). Add Advanced Alert Reporting:* Instead of sending a simple Slack message, use the full list of price_diffs (which contains all plans) to generate a consolidated daily *CSV report* or a professional *HTML email** summarizing all movements, even those below the alert threshold.

Overview Stop struggling with content creation for your e-commerce store. This workflow acts as your automated AI Content Marketer, instantly transforming your Shopify product details into high-quality, SEO-optimized blog posts. It handles everything from reading product data to writing the article and uploading it directly to your store as a draft. What this workflow does Fetches Product Data: Automatically pulls product titles and descriptions directly from your Shopify store (configurable limit). Data Logging: Backs up the raw product data into Google Sheets for record-keeping before processing. AI SEO Writing: Uses a powerful LLM (via OpenRouter/DeepSeek) to write a complete, engaging blog post based on the product's features. It generates an SEO-friendly title and formats the body content in clean HTML (headings, bullet points, etc.). Smart Parsing: A custom Code node ensures the AI's output is strictly formatted as JSON, separating the Blog Title from the Blog Content to prevent errors. Auto-Drafting in Shopify: Uploads the generated article directly to your specific Shopify Blog ID as a "Draft" (so you can review it before publishing). Email Notification: Sends a confirmation email via Gmail to let you know your new blog posts are ready for review. Setup Requirements To run this workflow, you will need to set up credentials in n8n for the following services: Shopify Admin API: To fetch products and create articles. (You will need your Shop Name and an Access Token). OpenRouter (or OpenAI): To power the AI Agent. The template is configured for DeepSeek via OpenRouter, but can be swapped for OpenAI. Google Sheets: To log product data and generated blog content. Gmail: To send the completion notification. How to use Configure Variables: Double-click the "Variables" node (Set node) at the start of the workflow. Enter your shop name (e.g., my-store from my-store.myshopify.com) and your blogId (found in the URL when viewing your blog in Shopify Admin). Connect Google Sheets: Open the Google Sheets nodes and map them to a sheet in your Drive. Ensure your sheet has columns for ID, Title, and Description. Select AI Model: In the Chat Model node, ensure your API key is connected (OpenRouter is used by default for cost-efficiency). Run: Execute the workflow. It will process your products and populate your Shopify Blog with new drafts automatically. Video Tutorial Watch the full setup guide here: Guide

This workflow automatically collects customer reviews from Google, Facebook, Trustpilot, and Yelp, analyzes their sentiment using AI, sends real-time alerts for negative feedback, and generates a weekly summary report. It is ideal for businesses that want to monitor their online reputation across multiple platforms and respond quickly to customer concerns. How It Works Daily Schedule**: Triggers the workflow every day at 09:00. Review Collection**: Fetches new reviews from Google, Facebook, Trustpilot, and Yelp using their official APIs. Data Normalization**: Merges and standardizes all reviews into a unified format. AI Sentiment Analysis**: Uses GPT-4 to analyze the sentiment and extract key insights from each review. Negative Review Alerts**: Sends a Slack notification to managers if a negative review is detected. Logging**: Saves all reviews and their analysis to a Google Sheet for record-keeping. Weekly Reporting**: Every Monday, aggregates the past week’s reviews, generates an AI-powered summary, and emails it to management. Configuration API Credentials: Google My Business API: Create a project in Google Cloud, enable the My Business API, and generate OAuth credentials. Facebook Graph API: Create a Facebook App, request the necessary permissions, and obtain a Page Access Token. Trustpilot API: Register for a Trustpilot Business account and generate an API key. Yelp Fusion API: Sign up for Yelp Fusion, create an app, and get your API key. OpenAI API: Create an account at OpenAI, generate an API key for GPT-4 access. Slack API: Create a Slack App, enable Incoming Webhooks, and get the webhook URL. Google Sheets API: Enable the Google Sheets API in Google Cloud and create OAuth credentials. Set Up Environment Variables: Add all API keys, tokens, and configuration values in the Workflow Configuration node or as n8n credentials. Google Sheet Setup: Create a Google Sheet with columns for review data and share it with your service account email. Slack Channel: Set up a Slack channel for alerts and add the webhook URL in the configuration. Email Settings: Configure the recipient email address for weekly reports in the workflow. Usage Activate the workflow after configuration. Reviews will be collected and analyzed daily. Negative reviews trigger instant Slack alerts. Every Monday, a summary report is sent via email. Use Case: Monitor and respond to customer feedback across Google, Facebook, Trustpilot, and Yelp, automate sentiment analysis, and keep management informed with actionable weekly insights.

AI-Powered Lead Qualification & Enrichment Pipeline 🎯 Who is this for? This template is perfect for: Marketing Teams** looking to automatically qualify inbound leads from campaigns Sales Teams** wanting to prioritize high-value prospects instantly Agencies** offering lead qualification as a service to clients SaaS Companies** routing trial signups to appropriate nurture sequences B2B Service Providers** scoring and enriching leads from multiple sources 💡 What problem does it solve? Manual lead qualification is slow, inconsistent, and expensive. Sales teams waste hours on unqualified leads while hot prospects go cold. This workflow: Eliminates manual research** - Automatically enriches company data via LinkedIn Scores leads instantly** - AI analyzes 15+ data points to score 0-100 Routes intelligently** - Hot leads get instant alerts, warm leads enter nurture Personalizes outreach** - AI generates custom emails based on company context ⚡ What this workflow does 1. Lead Capture & Validation Captures leads via built-in n8n Form (embeddable on any website) Validates email format and detects business vs personal emails Normalizes data from various field naming conventions 2. Company Enrichment via Apify Uses Google Search to find company's LinkedIn profile Scrapes LinkedIn for industry, size, description, specialties, and more Gracefully skips enrichment for personal emails (Gmail, Yahoo, etc.) 3. AI Lead Qualification (GPT-4.1) Scores leads 0-100 based on buying signals Assigns tier: Hot (80+), Warm (60-79), Cold (40-59), Disqualified (<40) Identifies buyer persona (Decision Maker, Influencer, Champion, etc.) Generates personalized talking points and risk factors 4. Intelligent Routing & Actions Hot Leads**: Instant Slack alert + AI-generated personalized email + HubSpot contact Warm Leads**: Slack notification for nurture sequence Cold Leads**: Logged for future reference All Leads**: Recorded to Google Sheets with full qualification data 🔧 Setup Required Credentials | Service | Purpose | |---------|---------| | OpenAI | AI qualification & email generation | | Apify | Google Search + LinkedIn scraping | Optional Credentials | Service | Purpose | |---------|---------| | Slack | Lead alerts and notifications | | HubSpot | CRM contact creation | | Gmail | Sending personalized emails | | Google Sheets | Lead database logging | Apify Setup Create account at apify.com Get API token from Settings → Integrations Open the Apify HTTP nodes and replace YOUR_API_KEY with the API token obtained in the above step Apify Actors Used Google Search Scraper PPR** (Actor ID: G9PR1B1upfS0mRvp0) - ~$0.004/search LinkedIn Company Scraper PPR** (Actor ID: G9y3V8J1hXYJTf1Ho) - ~$0.02/company Total cost: ~$0.02-0.03 per enriched lead 📊 Lead Scoring Criteria | Score | Tier | What it means | |-------|------|---------------| | 80-100 | 🔥 Hot | Strong buying signals, budget confirmed, urgent timeline | | 60-79 | 🌡️ Warm | Good fit, some buying signals, needs nurturing | | 40-59 | ❄️ Cold | Potential fit but unclear intent | | 0-39 | ⛔ Disqualified | Poor fit, spam, or invalid | 🎨 Customization Modify Form Fields Edit the "Lead Capture Form" node to add/remove fields for your use case. Adjust AI Scoring Edit the system prompt in "AI Lead Qualification" to customize: Score thresholds for your industry Buyer persona definitions Custom qualification criteria Add Integrations Easily extend with: Pipedrive, Salesforce, or other CRMs Email sequences (Mailchimp, ActiveCampaign) SMS notifications (Twilio) Calendar booking (Calendly) 📈 Example Output { "qualification": { "score": 85, "tier": "Hot", "buyerPersona": "Decision Maker", "urgencyLevel": "High" }, "insights": { "keyInsights": [ "VP-level with direct budget authority", "Company in growth phase (51-200 employees)", "Industry aligned with our ICP" ], "talkingPoints": [ "Reference their sustainability focus", "Highlight ROI for mid-market companies" ] } } 🙋 Need Help? Check the sticky notes in the workflow for section-by-section guidance Ensure Apify credentials are properly configured Test with a business email (not Gmail/Yahoo) to see full enrichment Created by Agentical AI - AI Automation Agency specializing in workflow automation and AI solutions.

AI-Powered Lead Qualification using Zoho CRM, People Data Labs, and Google Gemini This workflow automatically checks Zoho CRM every 5 minutes for newly created leads, enriches each lead using People Data Labs, evaluates its quality using Google Gemini (LLM Chain) and updates the lead status in Zoho CRM as Qualified or Not Qualified. Qualified leads trigger an automated Gmail notification to the sales team. Quick Start Setup Add Zoho CRM OAuth credentials. Add your People Data Labs API key. Add your Google Gemini (PaLM) LLM API credentials. Add Gmail OAuth credentials and set your recipient email. Activate the workflow. Create a test lead and verify enrichment → scoring → update → email. What It Does This workflow serves as an automated AI-driven lead qualification engine. Every 5 minutes, it fetches leads from Zoho CRM, filters newly created ones, enriches them using People Data Labs and scores them via Google Gemini. Based on the AI-generated score, the workflow updates the lead status and optionally sends an email notification. Who’s It For Sales teams using Zoho CRM SDR/Marketing automation teams Agencies performing automated lead pre-qualification Businesses with high inbound lead volume Anyone wanting AI-powered CRM automation via n8n Requirements n8n instance Zoho CRM OAuth credentials People Data Labs API key (can use another service , modify accordingly) Google Gemini API credentials Gmail OAuth credentials Zoho fields: Company, Email, First_Name, Last_Name, Created_Time, Lead_Status How It Works & Setup Steps Step 1: Run every 5 minutes via Schedule Trigger Triggers the workflow and computes a timestamp window. Step 2: Fetch Zoho leads Retrieves all leads from Zoho CRM. Step 3: Filter newly created leads Compares Created_Time with timestamp from previous run. Step 4: Extract website field Extract the website field, Used for People Data Labs enrichment API for search about that company. Step 5: Enrich via People Data Labs Adds company size, industry, founding year, etc. Step 6: Score using Google Gemini LLM produces a JSON response: summary, score, factors. Step 7: Update CRM status IF score > 80 → Qualified Else → Not Qualified Step 8: Send Gmail notification Send gmail notifications to sales team, Only for Qualified leads - informs that this Lead is marked as Qualified Leads Customization Adjust score threshold in IF node Edit email recipients in Gmail node Modify AI prompt in LLM Chain Change 3rd party api for enrichment, if required Modify PDL parameters Change Zoho CRM fields Add‑Ons Slack notifications Google Sheets logging Auto-create Deals in Zoho Add CRM notes Owner reassignment Tagging Use Case Examples Automated B2B lead scoring High-intent lead notifications CRM hygiene automation Enriched lead analytics SDR productivity boost Troubleshooting Guide | Issue | Cause | Solution | |-------|--------|----------| | No new leads detected | Timestamp mismatch | Validate “Compute Last Check” logic | | No enrichment data | Empty website / invalid API key | Check PDL credentials & website value | | AI output invalid | Prompt overwritten | Restore original prompt | | CRM update fails | Wrong leadId mapping | Confirm Zoho lead ID | | Gmail errors | OAuth expired | Reconnect Gmail credentials | | No qualified leads | Score too strict | Lower IF threshold | Need Help? WeblineIndia can help with workflow customization, advanced automations, CRM integrations and AI-driven business processes. Contact us for expert assistance.