Workflow Templates

The workflow is well-designed for CRM analysis with a robust quality control mechanism. The dual-AI approach ensures reliable results, while the webhook integration makes it production-ready for real-time CRM data processing. Dual-AI Architecture: Uses DeepSeek Reasoner for analysis and DeepSeek Chat for verification. Flexible Input: Supports both manual testing and production webhook integration. Quality Assurance: Built-in verification system to ensure report accuracy. Comprehensive Analysis: Covers lead conversion, upsell metrics, agent ranking, and more. Professional Output: Generates structured markdown reports with actionable insights

What this does This automation will create tables in your Airtable base and send Webflow form submissions as records in those tables. It keeps track of your Webflow forms with a Form Index table to ensure that form content does not get sent to the wrong table if you have Webflow forms with identical names. This is useful for Enhancing your Webflow form submission management. By sending structured data to your Airtable base you can do more with your Webflow forms. Usage guide Full written and video guide This automation is made to be as low effort as possible to start enhancing your Webflow forms. Simply create credentials for Webflow and a Personal Access Token for your Airtable base and connect them to the relevant nodes. The guide demonstrates a realworld example using a Webflow template and breaksdown the flow and logic for all the nodes.

Jotform Employee Recognition & Rewards Submission System Transform manual peer recognition into a transparent, engaging, and automated reward system - achieving 300% increase in recognition submissions, 85% employee satisfaction improvement, and building a culture where great work is celebrated instantly. What This Workflow Does Revolutionizes employee recognition with AI-powered categorization and instant acknowledgment: 📝 Peer-to-Peer Recognition - Jotform captures nominations from any employee recognizing colleagues 🤖 AI Categorization - GPT-4 automatically classifies into Innovation, Teamwork, Leadership, Customer Service, Excellence, Problem Solving, or Mentorship 📊 Automated Tracking - Every recognition logged to Google Sheets with full AI analysis 📧 Triple Notifications - Nominator receives thank you, nominee gets congratulations, HR gets summary 🏆 Monthly Award Automation - AI analyzes eligible nominations and recommends Employee of the Month 💰 Reward Recommendations - AI suggests appropriate reward values ($50-$500) based on impact 🎯 Recognition Strength Scoring - 1-10 scale for nomination quality and impact assessment 📈 Analytics Dashboard - Track trends by department, category, and employee 🌟 Public Recognition - Automated announcements and newsletter features 💪 Culture Building - Reinforces positive behaviors through immediate acknowledgment Key Features AI Recognition Analyst: GPT-4 analyzes each nomination across 15+ dimensions including category classification, impact assessment, and award eligibility Smart Categorization: Automatically sorts recognitions into 7 primary categories plus secondary tags for comprehensive tracking Recognition Strength Scoring: 1-10 scale evaluates nomination quality, detail, and genuine impact demonstration Impact Level Assessment: Classifies impact as individual, team, department, or company-wide for appropriate rewards Core Values Mapping: AI identifies which company values the behavior exemplifies (innovation, collaboration, excellence, etc.) Award Eligibility Detection: Automatically flags high-quality nominations for Employee of the Month consideration Reward Value Suggestions: AI recommends appropriate monetary rewards ($50/$100/$250/$500) based on impact and effort Monthly Award Reports: Automated analysis of all eligible nominations with winner recommendations and justification Public Recognition Generation: AI creates shareable recognition text suitable for company-wide announcements Behavioral Examples Extraction: Identifies specific behaviors that can be used for training and culture reinforcement Department Analytics: Track which departments are most active in giving and receiving recognition Trend Identification: Spot patterns in recognition types, peak times, and cultural shifts Perfect For Growing Tech Companies: 50-500 employees building positive culture during rapid scaling Remote-First Organizations: Distributed teams needing virtual recognition and connection Enterprise HR Teams: Large organizations (1000+ employees) managing formal recognition programs Professional Services: Consulting, legal, accounting firms emphasizing teamwork and client service Healthcare Organizations: Hospitals and medical practices recognizing patient care excellence Retail & Hospitality: Frontline teams celebrating customer service and operational excellence Manufacturing Companies: Recognizing safety, quality, innovation, and continuous improvement Educational Institutions: Schools and universities celebrating teaching excellence and student support What You'll Need Required Integrations Jotform - Recognition submission form (free tier works) Create your form for free on Jotform using this link OpenAI API - GPT-4 for AI recognition analysis (~$0.15-0.30 per submission) Gmail - Automated notifications to nominators, nominees, HR, and leadership Google Sheets - Recognition database and analytics dashboard Optional Integrations Slack - Real-time recognition announcements to company channel Microsoft Teams - Recognition notifications and celebrations HRIS Integration - Link recognitions to employee profiles (Workday, BambooHR, etc.) Quick Start Import Template - Copy JSON and import into n8n Add OpenAI Credentials - Set up OpenAI API key (GPT-4 recommended) Create Jotform Recognition Form: Nominator Name (q3_nominatorName) Nominator Email (q4_nominatorEmail) Nominee Name (q5_nomineeName) - dropdown or autocomplete Nominee Email (q6_nomineeEmail) Department (q7_department) - dropdown Recognition Title (q8_recognitionTitle) - short text Detailed Description (q9_description) - paragraph text Specific Example/Story (q10_example) - paragraph text Impact on Team/Company (q11_impact) - paragraph text Configure Gmail - Add Gmail OAuth2 credentials (same for all 4 Gmail nodes) Setup Google Sheets: Create spreadsheet with "Recognition_Log" sheet Replace YOUR_GOOGLE_SHEET_ID in workflow (2 places) Columns auto-populate on first submission Customize Email Templates: Update company name, branding, colors Add company logo URLs if desired Update recognition form link Configure Monthly Awards: Review cron schedule (default: 1st of month at 9 AM) Update leadership email addresses Set Company Values (Optional): Edit AI prompt to include your specific company values Customize category names if needed Test Workflow - Submit test recognition through Jotform Launch Program: Announce to company with form link Share recognition examples to inspire participation Consider initial incentives (e.g., "Submit 3 recognitions this month, get $25 gift card") Customization Options Recognition Categories: Add/modify categories to match your company values (Safety, Quality, Diversity & Inclusion, etc.) Reward Tiers: Adjust suggested reward values to match your budget and culture Approval Workflow: Add manager approval step before rewards are issued Point System: Implement recognition points that accumulate toward bigger rewards Nomination Limits: Set monthly caps per nominator to prevent gaming the system Department Weighting: Balance recognition across departments with quotas or goals Anniversary Bonuses: Higher reward values for work anniversaries or milestones Team Recognition: Add option to recognize entire teams, not just individuals Anonymous Nominations: Allow anonymous recognition for sensitive feedback Peer Voting: Let team vote on monthly award winner from nominated candidates Multi-Language Support: Translate forms and emails for international teams Custom Triggers: Add recognition triggers from project completions, customer feedback, etc. Integration with Performance Reviews: Link recognitions to annual review cycles Gamification: Leaderboards, badges, and recognition streaks Charity Donations: Let employees donate rewards to causes they care about Expected Results 300% increase in recognition submissions - Easy process encourages frequent recognition 85% employee satisfaction improvement - Feeling valued boosts morale and engagement 60% reduction in manual HR work - Automated tracking and categorization 95% program participation - Simple form drives company-wide adoption 40% improvement in retention - Recognized employees stay longer 2.5x boost in employee engagement scores - Regular recognition increases commitment 100% recognition tracking - No lost nominations or forgotten acknowledgments 50% faster award decisions - AI analysis speeds monthly selection process 75% reduction in "favoritism" complaints - Transparent, data-driven awards 90% positive cultural impact - Builds appreciation and psychological safety Use Cases Tech Startup (120 Employees, Rapid Growth) Scenario: Software engineer Sarah stays late 3 nights to fix critical production bug affecting 1,000+ customers. Teammate Jake submits recognition at 11 PM from home. AI Analysis: Primary Category: Problem Solving Secondary: Teamwork, Customer Service Recognition Strength: 9/10 (detailed, specific impact) Impact Level: Company-wide (customer retention, revenue protection) Impact Score: 10/10 Core Values: Excellence, Customer First, Ownership Award Recommendation: Employee of the Month + Spot Award Suggested Reward: $500 Eligible for Monthly Award: YES Automated Response: 11:02 PM: Jake receives thank you email with AI analysis 11:02 PM: Sarah receives congratulations notification 11:02 PM: HR receives summary with $500 reward recommendation Next Day 9 AM: CTO reviews, approves $500 gift card + public announcement Weekly Newsletter: Sarah's achievement featured with customer impact data End of Month: Sarah wins Employee of the Month ($1,000 bonus + trophy + parking spot) Result: Sarah feels valued and appreciated. Customer sees bug fixed overnight and becomes case study client. 3 other engineers submit recognitions that week, inspired by Sarah's example. Company culture of "customer heroes" strengthens. Remote-First Marketing Agency (85 Employees, 12 Countries) Scenario: Junior designer Maria creates innovative template that speeds up client deliverables by 40%. Senior creative director in different timezone recognizes her contribution. AI Analysis: Primary Category: Innovation Secondary: Efficiency, Problem Solving Recognition Strength: 8/10 Impact Level: Department-wide (affects all designers) Impact Score: 9/10 Core Values: Innovation, Efficiency, Initiative Award Recommendation: Innovation Award + Spot Recognition Suggested Reward: $250 Eligible for Monthly Award: YES Automated Response: Recognition received during nominee's off-hours (sleeping) Wake up to congratulations email from company Nominator receives thank you acknowledging time zone difference HR schedules all-hands recognition for upcoming Monday Template added to company resource library with Maria's credit Recognition appears in #wins Slack channel with reactions from 47 colleagues Result: Maria gains confidence, becomes advocate for innovation program. Template saves company 160 hours quarterly ($16K+ value). 5 other team members submit process improvement ideas that month. Remote employees feel connected despite time zones. Healthcare System (2,400 Nurses & Staff) Scenario: ER nurse catches medication error that could have harmed patient. Colleague recognizes life-saving attention to detail during chaotic shift. AI Analysis: Primary Category: Excellence Secondary: Patient Safety, Attention to Detail Recognition Strength: 10/10 (life-or-death impact) Impact Level: Individual patient, but systemic importance Impact Score: 10/10 Core Values: Patient First, Safety, Excellence Award Recommendation: Safety Excellence Award Suggested Reward: $500 + Public Recognition Eligible for Monthly Award: YES Flag for Quarterly Safety Review: YES Automated Response: Nurse receives recognition during shift break Nursing manager immediately notified Safety committee auto-tagged for review Recognition logged in employee safety profile Story used (with permission) in next safety training Featured in hospital newsletter with photo Result: Nurse's vigilance prevents sentinel event. Recognition reinforces safety culture. 12 other near-miss reports submitted that month (normally 3). Hospital passes safety audit with "exemplary culture" rating. Employee retention improves 15% in high-stress ER department. Manufacturing Company (450 Production Workers) Scenario: Maintenance technician develops preventive maintenance checklist that reduces equipment downtime 30%. Plant manager recognizes proactive problem-solving. AI Analysis: Primary Category: Innovation Secondary: Problem Solving, Operational Excellence Recognition Strength: 9/10 Impact Level: Department-wide (affects entire production line) Impact Score: 9/10 Core Values: Continuous Improvement, Ownership, Excellence Award Recommendation: Operational Excellence Award Suggested Reward: $250 Measurable ROI: $75K saved annually in downtime costs Automated Response: Technician receives recognition at shift change Operations director sees summary with ROI calculation Recognition posted in break room (digital display) Checklist becomes standard operating procedure Technician invited to present at quarterly meeting Featured in company safety/quality newsletter Result: Simple checklist saves company $75K annually. Technician becomes "continuous improvement champion," mentors 8 other workers in process optimization. Recognition program drives 23 process improvements that quarter. Production efficiency increases 12% year-over-year. Professional Services Firm (280 Consultants) Scenario: Junior consultant stays weekend to help colleague prepare critical client presentation. Senior partner recognizes teamwork and sacrifice. AI Analysis: Primary Category: Teamwork Secondary: Client Service, Going Above & Beyond Recognition Strength: 8/10 Impact Level: Team (supported 1 consultant, helped 1 client) Impact Score: 7/10 Core Values: Collaboration, Client First, Team Player Award Recommendation: Teamwork Award + Spot Recognition Suggested Reward: $100 + Comp Day Automated Response: Junior consultant receives congratulations Monday morning Partner's thank you delivered immediately HR flags for performance review documentation Recognition counted toward "team player" bonus criteria Story shared in weekly team meeting Comp day automatically added to time-off balance Result: Junior consultant feels valued despite weekend work. Colleague's presentation wins $500K project extension. Recognition drives "help each other" culture. Voluntary weekend support increases 40% without burnout concerns. Firm wins "Best Places to Work" award citing culture of appreciation. Pro Tips Launch with Leaders First: Have executives submit first recognitions to model behavior and set tone Make it Mobile-Friendly: 70% of recognitions happen on phones during breaks or commutes Weekly Recognition Roundups: Share top 5-10 recognitions in Friday email to inspire others Recognition Training: 15-minute workshop on "what makes a good recognition" increases quality 3x Nominator Leaderboards: Celebrate people who recognize others (not just recipients) Milestone Celebrations: Auto-recognize work anniversaries, project completions, certifications Real-Time Announcements: Post new recognitions to Slack/Teams channel as they arrive Photo Opportunities: Encourage nominators to include photos of the recognized moment/achievement Manager Dashboards: Give managers view of their team's recognition activity to spot engagement issues Budget Tracking: Monitor monthly reward spending vs budget to avoid year-end shortfalls Quarterly Trends Reports: Analyze recognition patterns to identify cultural strengths and gaps Anonymous Option for Sensitive Topics: Some achievements (whistleblowing, standing up to bias) need privacy Celebrate the Nominators: "Recognition Champion of the Month" for most thoughtful nominations Link to Performance Reviews: Include recognition count/quality in annual review criteria Seasonal Campaigns: "Gratitude November" or "Thanks-giving Week" to spike participation Learning Resources This workflow demonstrates advanced automation: AI Agents with Multi-Dimensional Analysis: Recognition categorization, strength scoring, impact assessment, and value determination Dynamic Email Personalization: Different email templates with conditional content based on AI analysis results Scheduled Automation: Monthly award selection runs automatically without manual intervention Complex Data Filtering: JavaScript code filters eligible nominations based on multiple criteria Parallel Execution: Simultaneous notifications to multiple stakeholders without delays Aggregate Reporting: AI synthesizes multiple nominations into executive-ready reports Cultural Pattern Recognition: AI identifies trends in recognition types and department dynamics Behavioral Reinforcement: Immediate positive feedback loops strengthen desired behaviors Data-Driven Decision Support: Objective metrics reduce bias in award selections Scalable Recognition: Handles 10 or 10,000 recognitions per month with same efficiency Business Impact Metrics Employee Engagement Scores: Track quarterly engagement surveys before/after program launch (expect 25-40% increase) Voluntary Turnover Rate: Measure retention improvement (recognized employees 50% more likely to stay) Recognition Participation Rate: Target 80%+ employees submitting at least one recognition annually Recognition Received Distribution: Ensure fair spread across departments and levels (detect favoritism) Manager Effectiveness: Correlate manager recognition activity with team engagement and performance Time-to-Recognition: Track lag between achievement and recognition (target <24 hours) Program ROI: Calculate cost per recognition vs engagement/retention value (typical 10:1 ROI) Recognition Quality Scores: AI strength scores improve over time as employees learn what makes good recognition Award Selection Speed: Reduce Employee of the Month selection from 2 weeks to 2 hours Cultural Value Alignment: Track which core values are most/least recognized to identify gaps Ready to Build a Culture of Appreciation? Import this template and turn recognition chaos into systematic celebration of excellence with AI-powered automation! 🏆✨ Questions or customization? The workflow includes detailed sticky notes explaining each AI analysis component and recognition logic. Template Compatibility ✅ n8n version 1.0+ ✅ Works with n8n Cloud and Self-Hosted ✅ No coding required for basic setup ✅ Fully customizable for company-specific values

How it Works This workflow accepts meeting transcripts via webhook (Zoom, Google Meet, Teams, Otter.ai, or manual notes), immediately processing them through an intelligent pipeline that eliminates post-meeting admin work. The system parses multiple input formats (JSON, form data, transcription outputs), extracting meeting metadata including title, date, attendees, transcript content, duration, and recording URLs. OpenAI analyzes the transcript to extract eight critical dimensions: executive summary, key decisions with ownership, action items with assigned owners and due dates, discussion topics, open questions, next steps, risks/blockers, and follow-up meeting requirements—all returned as structured JSON. The intelligence engine enriches each action item with unique IDs, priority scores (weighing urgency + owner assignment + due date), status initialization, and meeting context links, then calculates a completeness score (0-100) that penalizes missing owners and undefined deadlines. Multi-channel distribution ensures visibility: Slack receives formatted summaries with emoji categorization for decisions (✅), action items (🎯) with priority badges and owner assignments, and completeness scores (📊). Notion gets dual-database updates—meeting notes with formatted decisions and individual task cards in your action item database with full filtering and kanban capabilities. Task owners receive personalized HTML emails with priority color-coding and meeting context, while Google Calendar creates due-date reminders as calendar events. Every meeting logs to Google Sheets for analytics tracking: attendee count, duration, action items created, priority distribution, decision count, completeness score, and follow-up indicators. The workflow returns a JSON response confirming successful processing with meeting ID, action item count, and executive summary. The entire pipeline executes in 8-12 seconds from submission to full distribution. Who is this for? Product and engineering teams drowning in scattered action items across tools Remote-first companies where verbal commitments vanish after calls Executive teams needing auditable decision records without dedicated note-takers Startups juggling 10+ meetings daily without time for manual follow-up Operations teams tracking cross-functional initiatives requiring accountability Setup Steps Setup time:** 25-35 minutes Requirements:** OpenAI API key, Slack workspace, Notion account, Google Workspace (Calendar/Gmail/Sheets), optional transcription service Webhook Trigger: Automatically generates URL, configure as POST endpoint accepting JSON with title, date, attendees, transcript, duration, recording_url, organizer Transcription Integration: Connect Otter.ai/Fireflies.ai/Zoom webhooks, or create manual submission form OpenAI Analysis: Add API credentials, configure GPT-4 or GPT-3.5-turbo, temperature 0.3, max tokens 1500 Intelligence Synthesis: JavaScript calculates priority scores (0-40 range) and completeness metrics (0-100), customize thresholds Slack Integration: Create app with chat:write scope, get bot token, replace channel ID placeholder with your #meeting-summaries channel Notion Databases: Create "Meeting Notes" database (title, date, attendees, summary, action items, completeness, recording URL) and "Action Items" database (title, assigned to, due date, priority, status, meeting relation), share both with integration, add token Email Notifications: Configure Gmail OAuth2 or SMTP, customize HTML template with company branding Calendar Reminders: Enable Calendar API, creates events on due dates at 9 AM (adjustable), adds task owner as attendee Analytics Tracking: Create Google Sheet with columns for Meeting_ID, Title, Date, Attendees, Duration, Action_Items, High_Priority, Decisions, Completeness, Unassigned_Tasks, Follow_Up_Needed Test: POST sample transcript, verify Slack message, Notion entries, emails, calendar events, and Sheets logging Customization Guidance Meeting Types:** Daily standups (reduce tokens to 500, Slack-only), sprint planning (add Jira integration), client calls (add CRM logging), executive reviews (stricter completeness thresholds) Priority Scoring:** Add urgency multiplier for <48hr due dates, owner seniority weights, customer impact flags AI Prompt:** Customize to emphasize deadlines, blockers, or technical decisions; add date parsing for phrases like "by end of week" Notification Routing:** Critical priority (score >30) → Slack DM + email, High (20-30) → channel + email, Medium/Low → email only Tool Integrations:** Add Jira/Linear for ticket creation, Asana/Monday for project management, Salesforce/HubSpot for CRM logging, GitHub for issue creation Analytics:** Build dashboards for meeting effectiveness scores, action item velocity, recurring topic clustering, team productivity metrics Cost Optimization:** ~1,200 tokens/meeting × $0.002/1K (GPT-3.5) = $0.0024/meeting, use batch API for 50% discount, cache common patterns Once configured, this workflow becomes your team's institutional memory—capturing every commitment and decision while eliminating hours of weekly admin work, ensuring accountability is automatic and follow-through is guaranteed. Built by Daniel Shashko Connect on LinkedIn

This workflow automatically analyzes sales territory performance, comparing revenue, win rates, and activity across regions. Remove the guesswork from territory planning and drive balanced growth. Overview On a weekly schedule, the workflow pulls CRM data for each territory, merges it with demographic and market size info scraped via Bright Data, and feeds everything into OpenAI for performance benchmarking. Outliers—both high and low performers—are highlighted in a Google Data Studio dashboard and summarized in a Slack message. Tools Used n8n** – Orchestrates data collection and analysis CRM API** – Source of sales metrics by territory Bright Data** – Scrapes external market indicators (population, GDP, etc.) OpenAI** – Normalizes and benchmarks territories Google Sheets / Data Studio** – Stores and visualizes results Slack** – Sends the weekly summary How to Install Import the Workflow into n8n. Connect Your CRM API credentials. Configure Bright Data credentials. Set Up OpenAI API key. Authorize Google services & Slack. Customize Territory Definitions in the Set node. Use Cases Sales Leadership**: Rebalance territories based on potential. Revenue Operations**: Identify underserved regions. Financial Planning**: Allocate resources where ROI is highest. Incentive Design**: Reward reps fairly based on potential. Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Bright Data**: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #territorymanagement #salesanalytics #brightdata #openai #n8nworkflow #nocode #revenueops

Replicate Line Items on New Deal in HubSpot Workflow Use Case This workflow solves the problem of manually copying line items from one deal to another in HubSpot, reducing manual work and minimizing errors. What this workflow does Triggers** upon receiving a webhook with deal IDs. Retrieves** the IDs of the won and created deals. Fetches** line items associated with the won deal. Extracts** product SKUs from the retrieved line items. Fetches** product details based on SKUs. Creates** new line items for the created deal and associates them. Sends** a Slack notification with success details. Step up steps Create a HubSpot Deal Workflow 1.1 Set up your trigger (ex: when deal stage = Won) 1.2 Add step : Create Record (deal) 1.3 Add Step : Send webhook. The webhook should be a Get to your n8n first trigger. Set two query parameter : deal_id_won as the Record ID of the deal triggering the HubSpot Workflow deal_id_create as the Record ID of the deal created above. Click Insert Data -> The created object Set up your HubSpot App token in HubSpot -> Settings -> Integration -> Private Apps Set up your HubSpot Token integration using the predefined model. Set up your Slack connection Add an error Workflow to monitor errors

Automation Flow: Image to Image Using GPT Sora This flow automates the process of generating images using a provided prompt and reference image via the Sora GPT Image API from RapidAPI. The generated images are stored in Google Drive, and details are logged in Google Sheets. Nodes Overview 1. On Form Submission Type**: n8n-nodes-base.formTrigger Description**: This node triggers when a user submits the form containing the prompt and image URL. It ensures the form fields are filled in and ready for processing. Form Fields: Prompt: A text description of the desired image. Image URL: The URL of the reference image to be used. Webhook ID: Unique identifier for form submission. 2. HTTP Request to Sora GPT Image API Type**: n8n-nodes-base.httpRequest Description: Sends the prompt and image URL to the **Sora GPT Image API to generate a new image based on the provided inputs. API Endpoint: Sora GPT Image API (via RapidAPI) Method: POST Body Parameters: Prompt: User-provided text. Image URL: The reference image URL. Width & Height: Image size is set to 1024x1024. 3. Code (Base64 Conversion) Type**: n8n-nodes-base.code Description**: This node processes the base64-encoded image data returned from the API. It decodes and formats the image to be uploaded to Google Drive. Output: Converts the base64 string into a binary JPEG file. 4. Upload Image to Google Drive Type**: n8n-nodes-base.googleDrive Description: Uploads the generated image to **Google Drive, storing it in a designated folder. Authentication: Google Service Account. File Name: The image file name is dynamically set from the previous node. 5. Log Details to Google Sheets Type**: n8n-nodes-base.googleSheets Description: This node logs the **Prompt, Generated Image, and Generation Date into a Google Sheets document for tracking and auditing purposes. Columns Mapped: Prompt: The user’s input text. Image: The name of the generated image file. Generated Date: Date and time of image generation. Flow Summary User Submits Form: Triggered when the form with the prompt and image URL is submitted. Image Generation: The data is sent to the Sora GPT Image API from RapidAPI to generate the image. Image Processing: The generated image (base64 format) is decoded and saved as a file. Google Drive Upload: The image is uploaded to Google Drive for storage. Google Sheets Logging: All relevant details (Prompt, Image, Date) are saved in Google Sheets. Benefits Automated Image Creation: Quickly generate images using AI based on a simple prompt and reference image via **RapidAPI. Efficient Workflow**: The entire process from form submission to image generation and storage is automated, saving time and reducing manual work. Centralized Storage: Generated images are stored in **Google Drive, ensuring easy access and organization. Audit Trail: The details of each generated image are logged in **Google Sheets, making it easy to track, review, and manage past creations. Scalable and Reusable**: Can be adapted to multiple use cases, such as creative design, marketing materials, or social media content generation. Problems Solved Manual Image Editing**: Eliminates the need for manual image manipulation and creation, allowing for automatic generation based on user inputs. Disorganized File Storage: With automatic uploads to **Google Drive, the images are stored in a centralized and organized manner. Lack of Record-Keeping: By logging image generation details in **Google Sheets, there's always a record of past creations, improving tracking and management. Time-Consuming Processes**: The automation drastically reduces the time spent on manual tasks, allowing users to focus on other aspects of their work or creative processes. This flow simplifies the process of creating AI-generated images based on user inputs, leveraging the power of the Sora GPT Image API via RapidAPI, making it a powerful tool for creative, design, and marketing purposes.

How It Works – Data Deduplication in n8n This tutorial demonstrates how to remove duplicate records from a dataset using JavaScript logic inside n8n's Code nodes. It simulates real-world data cleaning by generating sample user data with intentional duplicates (based on email addresses) and walks you through the process of deduplication step-by-step. The process includes: Creating Sample Data with duplicates. Filtering Out Duplicates using filter() and findIndex() based on email. Displaying Cleaned Results with simple statistics for before-and-after comparison. This is ideal for scenarios like CRM imports, ETL processes, and general data hygiene. ⚙️ Set-Up Steps 🔹 Step 1: Manual Trigger Node: When clicking 'Test workflow' Purpose: Initiates the workflow manually for testing. 🔹 Step 2: Generate Sample Data Node: Create Sample Data (Code node) What it does: Creates 6 users, including 2 intentional duplicates (by email). Outputs data as usersJson with metadata (totalCount, message). Mimics real-world messy datasets. 🔹 Step 3: Deduplicate the Data Node: Deduplicate Users (Code node) What it does: Parses usersJson. Uses .filter() + .findIndex() to keep only the first instance of each email. Logs total, unique, and removed counts. Outputs clean user list as separate items. 🔹 Step 4: Display Results Node: Display Results (Code node) What it does: Outputs structured summary: Unique users Status Timestamp Prepares results for review or downstream use. 📈 Sample Output Original count: 6 users Deduplicated count: 4 users Duplicates removed: 2 users 🎯 Learning Objectives You'll learn how to: Use .filter() and .findIndex() in n8n Code nodes Clean JSON data within workflows Create simple, effective deduplication pipelines Output structured summaries for reporting or integration 🧠Best Practices Validate input format (e.g., JSON schema) Handle null or missing fields gracefully Use logging for visibility Add error handling for production use Use pagination/chunking for large datasets

This guide details the setup and functionality of an automated workflow designed to monitor the health, uptime, and SLA compliance of travel supplier APIs, specifically the Amadeus Flight API and Booking.com Hotel API. The workflow runs every 10 minutes, processes health and SLA data, and sends alerts or logs based on the status. What It Monitors API Health**: UP/DOWN status with health indicators. Uptime Tracking**: Real-time availability percentage. SLA Compliance**: Automatic breach detection and alerts. Performance Rating**: Classified as EXCELLENT, GOOD, AVERAGE, or POOR. Features Runs every 10 minutes automatically. Monitors the Amadeus Flight API with a 99.5% SLA target. Monitors the Booking.com Hotel API with a 99.0% SLA target. Smart Alerts that notify via WhatsApp only on SLA breaches. Logging of results for both breaches and normal status. Workflow Steps Monitor Schedule**: Triggers the workflow every 10 minutes automatically. Amadeus Flight API**: Tests the Amadeus Flight API (GET: https://api.amadeus.com) simultaneously. Booking Hotel API**: Tests the Booking.com Hotel API (GET: https://distribution-xml.booking.com) simultaneously. Calculate Health & SLA**: Processes health, uptime, and SLA data. Alert Check**: Routes to appropriate responses based on breach status. SLA Breach Alert**: Sends an alert with throwError if an SLA breach occurs. Normal Status Log**: Records results with throwError for healthy status. Send Message**: Sends a WhatsApp message for breach alerts. How to Use Copy the JSON configuration of the workflow. Import it into your n8n workspace. Activate the workflow. Monitor results in the execution logs and WhatsApp notifications. The workflow will automatically start tracking your travel suppliers and alert you via WhatsApp only when SLA thresholds are breached. Please double-check responses to ensure accuracy. Requirements n8n account and instance setup. API credentials for Amadeus Flight API (e.g., https://api.amadeus.com). API credentials for Booking.com Hotel API (e.g., https://distribution-xml.booking.com). WhatsApp integration for sending alerts. Customizing this Workflow Adjust the Monitor Schedule interval to change the frequency (e.g., every 5 or 15 minutes). Modify SLA targets in the Calculate Health & SLA node to align with your service agreements (e.g., 99.9% for Amadeus). Update API endpoints or credentials in the Amadeus Flight API and Booking Hotel API nodes for different suppliers. Customize the Send Message node to integrate with other messaging platforms (e.g., Slack, email). Enhance the Normal Status Log to include additional metrics or export logs to a database.

This n8n workflow, which runs every Monday at 5:00 AM, initiates a comprehensive process to monitor and analyze network security by scrutinizing IP addresses and their associated ports. It begins by fetching a list of watched IP addresses and expected ports through an HTTP request. Each IP address is then processed in a sequential loop. For every IP, the workflow sends a GET request to Shodan, a renowned search engine for internet-connected devices, to gather detailed information about the IP. It then extracts the data field from Shodan's response, converting it into an array. This array contains information on all ports Shodan has data for regarding the IP. A filter node compares the ports returned from Shodan with the expected list obtained initially. If a port doesn't match the expected list, it is retained for further processing; otherwise, it's filtered out. For each such unexpected port, the workflow assembles data including the IP, hostnames from Shodan, the unexpected port number, service description, and detailed data from Shodan like HTTP status code, date, time, and headers. This collected data is then formatted into an HTML table, which is subsequently converted into Markdown format. Finally, the workflow generates an alert in TheHive, a popular security incident response platform. This alert contains details like the title indicating unexpected ports for the specific IP, a description comprising the Markdown table with Shodan data, medium severity, current date and time, tags, Traffic Light Protocol (TLP) set to Amber, a new status, type as 'Unexpected open port', the source as n8n, a unique source reference combining the IP with the current Unix time, and enabling follow and JSON parameters options. This comprehensive workflow thus aids in the proactive monitoring and management of network security.

Competitor Price Monitoring Dashboard with AI and Real-time Alerts 🎯 Target Audience E-commerce managers and pricing analysts Retail business owners monitoring competitor pricing Marketing teams tracking market positioning Product managers analyzing competitive landscape Data analysts conducting pricing intelligence Business strategists making pricing decisions 🚀 Problem Statement Manual competitor price monitoring is inefficient and often leads to missed opportunities or delayed responses to market changes. This template solves the challenge of automatically tracking competitor prices, detecting significant changes, and providing actionable insights for strategic pricing decisions. 🔧 How it Works This workflow automatically monitors competitor product prices using AI-powered web scraping, analyzes price trends, and sends real-time alerts when significant changes are detected. Key Components Scheduled Trigger - Runs the workflow at specified intervals to maintain up-to-date price data AI-Powered Scraping - Uses ScrapeGraphAI to intelligently extract pricing information from competitor websites Price Analysis Engine - Processes historical data to detect trends and anomalies Alert System - Sends notifications via Slack and email when price changes exceed thresholds Dashboard Integration - Stores all data in Google Sheets for comprehensive analysis and reporting 📊 Google Sheets Column Specifications The template creates the following columns in your Google Sheets: | Column | Data Type | Description | Example | |--------|-----------|-------------|---------| | timestamp | DateTime | When the price was recorded | "2024-01-15T10:30:00Z" | | competitor_name | String | Name of the competitor | "Amazon" | | product_name | String | Product name and model | "iPhone 15 Pro 128GB" | | current_price | Number | Current price in USD | 999.00 | | previous_price | Number | Previous recorded price | 1099.00 | | price_change | Number | Absolute price difference | -100.00 | | price_change_percent | Number | Percentage change | -9.09 | | product_url | URL | Direct link to product page | "https://amazon.com/iphone15" | | alert_triggered | Boolean | Whether alert was sent | true | | trend_direction | String | Price trend analysis | "Decreasing" | 🛠️ Setup Instructions Estimated setup time: 15-20 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Google Sheets account with API access Slack workspace for notifications (optional) Email service for alerts (optional) Step-by-Step Configuration 1. Install Community Nodes Install required community nodes npm install n8n-nodes-scrapegraphai npm install n8n-nodes-slack 2. Configure ScrapeGraphAI Credentials Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials Enter your API key from ScrapeGraphAI dashboard Test the connection to ensure it's working 3. Set up Google Sheets Connection Add Google Sheets OAuth2 credentials Grant necessary permissions for spreadsheet access Create a new spreadsheet for price monitoring data Configure the sheet name (default: "Price Monitoring") 4. Configure Competitor URLs Update the websiteUrl parameters in ScrapeGraphAI nodes Add URLs for each competitor you want to monitor Customize the user prompt to extract specific pricing data Set appropriate price thresholds for alerts 5. Set up Notification Channels Configure Slack webhook or API credentials Set up email service credentials (SendGrid, SMTP, etc.) Define alert thresholds and notification preferences Test notification delivery 6. Configure Schedule Trigger Set monitoring frequency (hourly, daily, etc.) Choose appropriate time zones for your business hours Consider competitor website rate limits 7. Test and Validate Run the workflow manually to verify all connections Check Google Sheets for proper data formatting Test alert notifications with sample data 🔄 Workflow Customization Options Modify Monitoring Targets Add or remove competitor websites Change product categories or specific products Adjust monitoring frequency based on market volatility Extend Price Analysis Add more sophisticated trend analysis algorithms Implement price prediction models Include competitor inventory and availability tracking Customize Alert System Set different thresholds for different product categories Create tiered alert systems (info, warning, critical) Add SMS notifications for urgent price changes Output Customization Add data visualization and reporting features Implement price history charts and graphs Create executive dashboards with key metrics 📈 Use Cases Dynamic Pricing**: Adjust your prices based on competitor movements Market Intelligence**: Understand competitor pricing strategies Promotion Planning**: Time your promotions based on competitor actions Inventory Management**: Optimize stock levels based on market conditions Customer Communication**: Proactively inform customers about price changes 🚨 Important Notes Respect competitor websites' terms of service and robots.txt Implement appropriate delays between requests to avoid rate limiting Regularly review and update your monitoring parameters Monitor API usage to manage costs effectively Keep your credentials secure and rotate them regularly Consider legal implications of automated price monitoring 🔧 Troubleshooting Common Issues: ScrapeGraphAI connection errors: Verify API key and account status Google Sheets permission errors: Check OAuth2 scope and permissions Price parsing errors: Review the Code node's JavaScript logic Rate limiting: Adjust monitoring frequency and implement delays Alert delivery failures: Check notification service credentials Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Google Sheets API documentation for advanced configurations Slack API documentation for notification setup

Customer Support Analysis Dashboard with AI and Automated Insights 🎯 Target Audience Customer support managers and team leads Customer success teams monitoring satisfaction Product managers analyzing user feedback Business analysts measuring support metrics Operations managers optimizing support processes Quality assurance teams monitoring support quality Customer experience (CX) professionals 🚀 Problem Statement Manual analysis of customer support tickets and feedback is time-consuming and often misses critical patterns or emerging issues. This template solves the challenge of automatically collecting, analyzing, and visualizing customer support data to identify trends, improve response times, and enhance overall customer satisfaction. 🔧 How it Works This workflow automatically monitors customer support channels using AI-powered analysis, processes tickets and feedback, and provides actionable insights for improving customer support operations. Key Components Scheduled Trigger - Runs the workflow at specified intervals to maintain real-time monitoring AI-Powered Ticket Analysis - Uses advanced NLP to categorize, prioritize, and analyze support tickets Multi-Channel Integration - Monitors email, chat, help desk systems, and social media Automated Insights - Generates reports on trends, response times, and satisfaction scores Dashboard Integration - Stores all data in Google Sheets for comprehensive analysis and reporting 📊 Google Sheets Column Specifications The template creates the following columns in your Google Sheets: | Column | Data Type | Description | Example | |--------|-----------|-------------|---------| | timestamp | DateTime | When the ticket was processed | "2024-01-15T10:30:00Z" | | ticket_id | String | Unique ticket identifier | "SUP-2024-001234" | | customer_email | String | Customer contact information | "john@example.com" | | subject | String | Ticket subject line | "Login issues with new app" | | description | String | Full ticket description | "I can't log into the mobile app..." | | category | String | AI-categorized ticket type | "Technical Issue" | | priority | String | Calculated priority level | "High" | | sentiment_score | Number | Customer sentiment (-1 to 1) | -0.3 | | urgency_indicator | String | Urgency classification | "Immediate" | | response_time | Number | Time to first response (hours) | 2.5 | | resolution_time | Number | Time to resolution (hours) | 8.0 | | satisfaction_score | Number | Customer satisfaction rating | 4.2 | | agent_assigned | String | Support agent name | "Sarah Johnson" | | status | String | Current ticket status | "Resolved" | 🛠️ Setup Instructions Estimated setup time: 20-25 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Google Sheets account with API access Help desk system API access (Zendesk, Freshdesk, etc.) Email service integration (optional) Step-by-Step Configuration 1. Install Community Nodes Install required community nodes npm install n8n-nodes-scrapegraphai npm install n8n-nodes-slack 2. Configure ScrapeGraphAI Credentials Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials Enter your API key from ScrapeGraphAI dashboard Test the connection to ensure it's working 3. Set up Google Sheets Connection Add Google Sheets OAuth2 credentials Grant necessary permissions for spreadsheet access Create a new spreadsheet for customer support analysis Configure the sheet name (default: "Support Analysis") 4. Configure Support System Integration Update the websiteUrl parameters in ScrapeGraphAI nodes Add URLs for your help desk system or support portal Customize the user prompt to extract specific ticket data Set up categories and priority thresholds 5. Set up Notification Channels Configure Slack webhook or API credentials for alerts Set up email service credentials for critical issues Define alert thresholds for different priority levels Test notification delivery 6. Configure Schedule Trigger Set analysis frequency (hourly, daily, etc.) Choose appropriate time zones for your business hours Consider support system rate limits 7. Test and Validate Run the workflow manually to verify all connections Check Google Sheets for proper data formatting Test ticket analysis with sample data 🔄 Workflow Customization Options Modify Analysis Targets Add or remove support channels (email, chat, social media) Change ticket categories and priority criteria Adjust analysis frequency based on ticket volume Extend Analysis Capabilities Add more sophisticated sentiment analysis Implement customer churn prediction models Include agent performance analytics Add automated response suggestions Customize Alert System Set different thresholds for different ticket types Create tiered alert systems (info, warning, critical) Add SLA breach notifications Include trend analysis alerts Output Customization Add data visualization and reporting features Implement support trend charts and graphs Create executive dashboards with key metrics Add customer satisfaction trend analysis 📈 Use Cases Support Ticket Management**: Automatically categorize and prioritize tickets Response Time Optimization**: Identify bottlenecks in support processes Customer Satisfaction Monitoring**: Track and improve satisfaction scores Agent Performance Analysis**: Monitor and improve agent productivity Product Issue Detection**: Identify recurring problems and feature requests SLA Compliance**: Ensure support teams meet service level agreements 🚨 Important Notes Respect support system API rate limits and terms of service Implement appropriate delays between requests to avoid rate limiting Regularly review and update your analysis parameters Monitor API usage to manage costs effectively Keep your credentials secure and rotate them regularly Consider data privacy and GDPR compliance for customer data 🔧 Troubleshooting Common Issues: ScrapeGraphAI connection errors: Verify API key and account status Google Sheets permission errors: Check OAuth2 scope and permissions Ticket parsing errors: Review the Code node's JavaScript logic Rate limiting: Adjust analysis frequency and implement delays Alert delivery failures: Check notification service credentials Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Google Sheets API documentation for advanced configurations Help desk system API documentation Customer support analytics best practices