by Zain Khan
Categories: Business Automation, E-commerce, Intelligence, AI This workflow automates high-frequency price tracking across e-commerce platforms. It combines the data-handling power of the Decodo node with the intelligence of Google Gemini to eliminate manual price checks. It is for businesses seeking real-time market intelligence. Benefits Total Automation: Handles data sourcing, and email notifications without human help. Intelligent Extraction: Uses AI to analyze the full page content. Precision Alerting: Triggers notifications when a product's price meets or falls below the "Desired Price." Scalable Architecture: Processes large batches of products. How It Works Scheduled Data Retrieval: The Schedule Trigger pulls a list of URLs and target prices from Google Sheets. Raw Data Processing: Data flows through a Decodo node. Full-Body Extraction: The workflow captures the entire body of the webpage. AI-Driven Analysis: An AI Agent, powered by Google Gemini, analyzes the text to identify the product name and price. Regex Data Cleaning: A JavaScript node uses Regular Expressions to sanitize the AI's response. Smart Comparison & Alerting: An If Node compares the live price against the "Desired Price." If the condition is met, an automated alert is sent via Gmail. Requirements n8n Instance Google Account Google Gemini API Key Decodo Credentials How to Use Setup your Spreadsheet: Create a Google Sheet with columns for the product link and "Desired price." Authenticate Nodes: Connect your Google Sheets, Gmail, and Gemini credentials within n8n. Configure Parameters: Ensure the If node correctly references the "Desired price" column from your Google Sheet output. Deploy: Activate the workflow. The system will now run automatically, monitoring the list and notifying of deals. Business Use Cases Retail Arbitrage Agencies: Spot price drops on supplier sites to maximize profit margins. Competitor Intelligence: Monitor rival pricing strategies. Procurement Departments: Automate the "buy" signal for raw materials when they hit a specific price point. E-commerce Managers: Track MAP (Minimum Advertised Price) compliance. Revenue Potential Increased Margins: Buy inventory at the lowest prices. Market Leadership: React faster than competitors to market-wide price shifts. Service Offering: Provide "Price Watch" services for e-commerce clients. Difficulty Level: Intermediate Estimated Setup Time: 40 min Monthly Operating Cost: Low (based on Gemini API tokens)
by Bakdaulet Abdikhan
Analyze Meta ads with Gemini and Google Sheets Stop manually exporting CSVs and start automating your marketing insights. This workflow is designed for Marketing Agencies, Freelancers, and Media Buyers who want to keep a daily pulse on their Meta (Facebook/Instagram) Ads performance without logging into Ads Manager. It doesn't just scrape data; it uses Google Gemini AI to act as a virtual data analyst. It reviews your campaigns, identifies winning/losing creatives, and writes strategic suggestions for both your agency team and your clients. 🚀 What this workflow does Extracts Data: Wakes up every morning (6:00 AM) to fetch yesterday's Ad and Campaign performance from the Facebook Graph API. Cleans & Filters: Automatically ignores paused or zero-spend campaigns to keep your reports clean. Structuring: Uses a Code node to group Ads intelligently under their respective Ad Sets and Campaigns. AI Analysis: Sends the structured data to Google Gemini. The AI analyzes CTR, CPC, and Spend to identify the "Best Performing Ad" and "Worst Performing Ad" per Ad Set. Reporting: Saves raw Campaign Data to Google Sheets. Saves raw Ad Data to Google Sheets. Saves AI-Generated Insights (Client & Agency suggestions) to a dedicated sheet. Error Handling: If anything breaks (e.g., API token expiry), it instantly sends you an alert via Gmail with the error details. 💡 Key Features Zero-Spend Filter:** Keeps your spreadsheet tidy by excluding inactive ads. Hierarchical Data Processing:** Groups data logically so the AI understands the context of your tests. Dual-Perspective Insights:** The AI generates two types of advice: For the Client: Simple, performance-based updates. For the Agency: Technical optimization tips (e.g., "Pause Ad B, Scale Ad A"). Robust Error Monitoring:** Includes a dedicated error workflow to notify you of failures. 🛠️ Prerequisites To use this template, you will need: Meta/Facebook Developer App:** A System User Access Token with ads_read permission. Google Cloud Console Project:** Enabled APIs for Google Sheets, Gmail, and Vertex AI (Gemini). Google Sheet:** A sheet with three tabs: Campaigns, Ads, and AI_Insights. 📝 Setup Instructions Configure Credentials: Connect your Facebook Graph API and Google accounts in n8n. Set Configuration Node: Open the "Set Configuration" node and paste your Ad Account ID and Email Address for error alerts. Link Google Sheet: Open the three Google Sheets nodes and select your spreadsheet file. Activate: Turn on the workflow and let it run daily! Need help setting this up or want a custom automation for your agency? I specialize in building agentic workflows for consultants and agencies. 📧 Contact me: bakdaulet.mph@gmail.com
by Avkash Kakdiya
How it works This workflow runs on a daily schedule to analyze all Closed–Lost deals from your CRM and uncover the true reason behind each loss. It uses AI to classify the primary loss category, generate a confidence-backed explanation, and then create a realistic re-engagement strategy for every deal. All insights are consolidated into leadership-ready email and Slack summaries. Every analyzed deal and revival plan is logged for long-term tracking and audits. Step-by-step Trigger and fetch lost deals** Schedule Trigger – Runs the workflow automatically at a defined time. Get many deals – Fetches all deal records from the CRM. If – Filters only deals marked as Closed–Lost. Edit Fields – Standardizes key deal attributes like amount, industry, owner, and loss reason. Analyze loss reasons and generate revival strategies** Brief Explanation Creator – Uses AI to identify the primary loss category with confidence. Code in JavaScript – Parses and normalizes AI loss analysis output. Merge – Combines deal data with loss insights. Feedback Creator – Generates a practical re-engagement strategy for each lost deal. Code in JavaScript7 – Parses and safeguards revival strategy outputs. Merge4 – Merges deal details, loss analysis, and revival strategy into one final dataset. Report, notify, and store results** Code in JavaScript11 – Builds a consolidated HTML summary email. Send a message4 – Sends the summary to stakeholders via email. Code in JavaScript12 – Creates a structured Slack summary. Send a message1 – Delivers insights to a Slack channel. Code in JavaScript10 – Reconstructs final data with delivery status. Append or update row in sheet – Logs all results into Google Sheets for audit and tracking. Why use this? Turns lost deals into actionable learning instead of static CRM records Gives sales teams clear, realistic re-engagement plans without manual analysis Provides leadership with concise, decision-ready summaries Creates a historical database of loss reasons and revival outcomes Improves pipeline recovery while enforcing consistent sales intelligence
by 荒城直也
Title: Create daily AI news digest and send to Telegram Description: Stay ahead of the rapidly evolving artificial intelligence landscape without the information overload. This workflow acts as your personal AI news editor, automatically curating, summarizing, and visualizing the top stories of the day, delivered directly to your Telegram. It goes beyond simple RSS aggregation by using an AI Agent to rewrite headlines and summaries into a digestible format and includes a "Chat Mode" where you can ask follow-up questions about the news directly within the n8n interface. Who is it for AI Enthusiasts & Researchers:** Keep up with the latest papers and releases without manually checking multiple sites. Tech Professionals:** Get a morning briefing on industry trends to start your day informed. Content Creators:** Find trending topics for newsletters or social media posts effortlessly. How it works News Aggregation: Every morning at 8:00 AM, the workflow fetches RSS feeds from top tech sources (Google News AI, The Verge, and TechCrunch). Smart Filtering: A Code node aggregates the articles, removes duplicates, and ranks them by recency to select the top 5 stories. AI Summarization: An AI Agent (powered by OpenAI) analyzes the selected stories and writes a concise, engaging summary for each. Visual Generation: DALL-E generates a unique, futuristic header image based on the day's news context. Delivery: The digest is formatted with Markdown and emojis, then sent to your specified Telegram chat. Interactive Chat: A separate branch allows you to chat with an AI Agent via the n8n Chat interface to discuss the news or ask general AI questions. How to set up Configure Credentials: Set up your OpenAI API credential. Set up your Telegram API credential. Get Telegram Chat ID: Create a bot with @BotFather on Telegram. Send a message to your bot. Use @userinfobot to find your numeric Chat ID. Update Workflow Settings: Open the Workflow Configuration node. Paste your Chat ID into the telegramChatId value field. Activate: Toggle the workflow to "Active" to enable the daily schedule. Requirements n8n Version:** Must support LangChain nodes. OpenAI Account:** API Key with access to GPT-4o-mini (or preferred model) and DALL-E 3. Telegram Account:** To create a bot and receive messages. How to customize Change News Sources:** Edit the RSS URLs in the Workflow Configuration node to track different topics (e.g., Crypto, Finance, Sports). Adjust Personality:** Modify the system prompt in the AI News Summarizer Agent node to change the tone of the summaries (e.g., "explain it like I'm 5" or "highly technical"). Change Schedule:** Update the Daily 8 AM Trigger node to your preferred time zone and frequency.
by sato rio
This workflow automates the initial screening process for new job applications, freeing up your recruitment team to focus on qualified candidates. It receives applications from a webhook, uses OpenAI (GPT-4) to analyze resumes for skill and culture fit, generates interview questions, logs the results to Google Sheets, sends interview invitations via Gmail, and notifies your team on Slack. 🚀 Who is this for? HR and Recruitment Teams** looking to automate repetitive screening tasks. Hiring Managers** who want a consistent, data-driven first pass on applicants. Startups and SMBs** aiming to build an efficient, scalable hiring pipeline without a large HR team. 💡 How it works Receive Application: The workflow triggers when a new application is submitted via a webhook from your job board or application form. Extract & Analyze: It downloads the resume/CV, extracts the text, and sends it to OpenAI (GPT-4) with a custom prompt. Score & Generate: The AI scores the candidate on skill match and culture fit, provides a summary, and generates tailored interview questions based on their experience. Log Data: The evaluation scores, AI summary, and candidate information are appended to a new row in a Google Sheet for tracking. Schedule Interview: A personalized email is sent to the candidate via Gmail with a link to schedule their interview. Notify Team: A summary card with the AI evaluation and links to the full report is posted in a Slack channel to keep the hiring team informed. ⚙️ How to set up Configure Credentials: Set up your credentials for OpenAI, Google (for both Sheets and Gmail), and Slack in n8n. Webhook URL: Copy the "Production URL" from the "Webhook: New Application" node and set it as the destination in your job board's webhook settings (e.g., Greenhouse, Lever, Ashby, or a web form). Google Sheet: Create a Google Sheet to track applicants. Update the "G Sheets: Save Evaluation" node with your Spreadsheet ID and Sheet Name. Ensure the columns in your sheet match the data you want to save. Customize Prompts & Email: Modify the prompts in the two OpenAI nodes to match your company's values and the specific job requirements. Update the Gmail node with your email content and the logic for your scheduling link (e.g., Calendly, SavvyCal). 📋 Requirements An n8n instance (Cloud or self-hosted). An OpenAI API key. A Google account for Google Sheets and Gmail. A Slack workspace. A job application source capable of sending webhooks.
by Yassin Zehar
Description Automatically triage Product UAT feedback using AI, route it to the right tools and teams, and close the feedback loop with testers, all in one workflow. This workflow analyzes raw UAT feedback, classifies it (critical bug, feature request, UX improvement, or noise), validates AI confidence, escalates when human review is needed, and synchronizes everything across Jira, Slack, Notion, Google Sheets, and email. Context Product teams often receive unstructured UAT feedback from multiple sources (forms, Slack, internal tools), making triage slow, inconsistent, and error-prone. This workflow ensures: Faster bug detection Consistent categorization Zero feedback lost Clear accountability between Product, Engineering, and Design It combines AI automation with human-in-the-loop control, making it safe for real production environments. Who is this for? Product Managers running UAT or beta programs Project Managers coordinating QA and release validation Product Ops / PMO teams Engineering teams who want faster, cleaner bug escalation Any team managing high-volume UAT feedback Perfect for teams that want speed without sacrificing control. Requirements Webhook trigger (form, internal tool, Slack integration, etc.) OpenAI account (for AI triage) Jira (bug tracking) Slack (team notifications) Notion (product roadmap / UX backlog) Google Sheets (UAT feedback log) Gmail (tester & manual review notifications) How it works Trigger The workflow starts when UAT feedback is submitted via a webhook (form, Slack, or internal tool). Normalize & Clean Incoming data is normalized into a consistent structure (tester, build, page, message) and cleaned to be AI-ready. AI Triage An AI model analyzes the feedback and returns: Type (Critical Bug, Feature Request, UX Improvement, Noise) Severity & sentiment Summary and suggested title Confidence score Quality Control If the AI output is unreliable (low confidence or parsing error), the feedback is automatically routed to manual review via email and Slack. Routing & Actions If confidence is sufficient: Critical Bugs → Jira issue + Engineering Slack alert Feature Requests → Notion roadmap UX Improvements → Design / UX tracking Noise → Archived but traceable Closed Loop The tester is notified via Slack or email, and the workflow responds to the original webhook with a structured status payload. What you get One unified UAT triage system Faster bug escalation Clean product and UX backlogs Full traceability of every feedback Automatic tester communication Safe AI usage with human fallback About me : I’m Yassin a Product Manager Scaling tech products with a data-driven mindset. 📬 Feel free to connect with me on Linkedin
by WeblineIndia
Zoho CRM – Deal Health Predictor with AI Scoring This n8n automation monitors open Zoho CRM Deals every week, identifies stalled opportunities, scores their health using Google Gemini AI and triggers sales intervention by emailing the deal owner and creating a high-priority task in Zoho CRM — before the deal goes cold. Quick Start — Implementation in 6 Steps Import workflow into your n8n instance. Connect Zoho OAuth2 credential in all Zoho nodes. Connect Gmail OAuth2 account for outbound alerts. Confirm stage names & inactivity thresholds match your CRM. Test with sample deals before scheduling. Activate the workflow once validated by your sales team. What It Does This workflow dynamically analyzes every open sales deal retrieved from Zoho CRM. It calculates key metrics per deal such as inactivity duration, stage aging and deal age to understand whether the opportunity has stalled. Only deals with significant inactivity move forward to AI scoring. Using Google Gemini, each deal receives a Health Score (0–100), along with a risk level, reasons and recommended next actions. If a deal is considered “At-Risk,” the system automatically: Sends an alert email to the assigned sales rep Creates a high-priority Task in Zoho CRM linked to that deal It ensures timely sales intervention without needing manual checks. Who’s It For Sales teams using Zoho CRM RevOps & Sales Managers monitoring deal movement Teams wanting data-backed alerts for slow-moving deals Businesses wanting proactive pipeline management with AI Requirements | Requirement | Why | |------------|-----| | n8n instance (Self-hosted or Cloud) | Runs the workflow | | Zoho CRM OAuth2 Credentials | Fetch deals + Create tasks | | Gmail (or SMTP) credentials | Send alert emails | | Google Gemini API access | AI scoring on deals | | Deals must have Stage + Owner + Activity history | Ensures accurate scoring | How It Works — Setup & Configuration Steps Step-by-Step Setup Import workflow into n8n Enable Zoho CRM OAuth2 credentials in: Fetch Open Deals Create At-Risk Task Enable Gmail OAuth2 on the email alert node Validate fields from Zoho API: Last_Activity_Time Stage Owner.email Update the deal stage list in the Fetch URL if needed: Example: Qualification, Negotiation, Proposal, etc. Confirm scanning frequency in the Weekly Trigger Run the workflow manually once → check logs + emails + tasks Turn workflow Active How To Customize Nodes | Node | What You Can Customize | Example | |------|-----------------------|---------| | Weekly Trigger | Change execution frequency | Daily scan | | Fetch Deals | Include additional deal stages | Add “Value Proposition” | | Filter Stalled Deals | Adjust inactivity threshold | > 15 days instead of 30 | | AI Prompt | Add more data points | Probability to close | | Email Alert | Modify message template | Localization | | Task creation | Add reminder / follow-up info | Due date +1 day | Add-Ons (Optional Enhancements) You can easily extend this workflow by adding: Stage Change Webhook Trigger** → near real-time monitoring Google Sheets or Database Logging** for reporting Duplicate task checker** so the same deal isn’t flagged repeatedly Slack / Microsoft Teams alerts** SLA-based scoring** (pipeline aging logic) Manager escalation** if no response in X days Practical Use Cases This workflow is ideal for: Sales manager auto-alert system for aging deals Leaderboard tracking for untouched deals Weekly CRM hygiene and rep performance tracking Early detection of churn risk in B2B sales cycles AI-assisted deal coaching and next-step suggestions Many more scenarios are possible based on deal movement automation. Troubleshooting Guide | Issue | Possible Cause | Fix / Solution | |------|----------------|----------------| | No deals processed | Stage filters too narrow | Update fetch URL stage list | | Emails not sent | Gmail credentials missing or expired | Reconnect Gmail OAuth2 | | Tasks not created | Zoho API permissions missing | Enable write permissions | | Owner email missing | CRM field not mapped correctly | Update sendTo expression | | Health score always null | Output parser mismatch | Check prompt & parser config | | Workflow runs but no alerts sent | No stalled deals or score >= threshold | Temporarily lower threshold for testing | Need Help? If you would like expert help customizing this workflow or implementing additional automation like stage-based triggers, dashboards or integration with Slack/Teams, our n8n automation team at WeblineIndia can assist you.
by Sona Labs
Automatically analyzes your Google Ads performance every Monday and sends a comprehensive report to your inbox with AI-powered insights, week-over-week comparisons, and prioritized recommendations to optimize your campaigns. How it works Step 1: Schedule Weekly Analysis Triggers automatically every Monday at midnight Can be customized to your preferred schedule Initiates the entire data collection and analysis process Step 2: Collect Performance Data Fetches last 7 days of Google Ads data via API Retrieves previous 7 days of data (days 8-14) for comparison Extracts key metrics including impressions, clicks, cost, conversions, CTR, and CPA Calculates and summarizes performance for each week Identifies top performers, problem campaigns, and efficiency trends Merges data to create comprehensive week-over-week comparison Step 3: AI-Powered Analysis Aggregates all performance data into a single view Sends data to AI Analyst powered by GPT-5.1 AI analyzes trends, identifies insights, and spots anomalies Diagnoses root causes of performance changes Generates actionable, prioritized recommendations based on business impact Calculates efficiency metrics and budget optimization opportunities Step 4: Deliver Insights Report Formats analysis into a professional HTML report Emails comprehensive insights directly to your inbox Includes executive summary, week-over-week comparison tables, and color-coded metrics Provides high/medium/low priority action items Ready for immediate action and strategy adjustments What you'll get The workflow delivers a comprehensive weekly analysis with: Performance Metrics**: Impressions, clicks, CTR, conversions, cost, CPA, and efficiency trends Week-over-Week Comparison**: Side-by-side analysis with percentage changes and visual indicators Top Performers Analysis**: Detailed breakdown of your best-performing campaigns Issues & Performance Risks**: Identification of campaigns with high spend but zero conversions, declining CTR, or rising CPA AI-Generated Insights**: Intelligent pattern recognition and trend analysis with root cause diagnosis Actionable Recommendations**: Prioritized action items (high/medium/low) with expected impact and risk levels Budget Efficiency Analysis**: Spend allocation recommendations and wasted spend identification Campaign Intelligence**: Clear understanding of what's working and what needs attention Data Confidence Assessment**: Commentary on sample size adequacy and metric reliability Automated Delivery**: Weekly HTML report sent directly to your email without manual effort Why use this Save time on reporting**: Eliminate 2-3 hours of manual weekly analysis and report creation Never miss insights**: AI catches trends and patterns humans might overlook Consistent monitoring**: Automated weekly reviews ensure you stay on top of performance Data-driven decisions**: Make strategic adjustments based on comprehensive analysis with clear priorities Early problem detection**: Spot performance issues and wasted spend before they impact your budget Optimize continuously**: Regular insights enable ongoing campaign refinement Focus on strategy**: Spend less time analyzing data, more time implementing improvements Scalable intelligence**: Works whether you manage 1 campaign or 100 Executive-ready reports**: Professional HTML format suitable for sharing with stakeholders Setup instructions Before you start, you'll need: Google Ads Account & API Access Go to your Google Ads account at https://ads.google.com Find your Customer ID (XXX-XXX-XXXX format in top-right corner) Get a Developer Token from Google Ads API Center Enable API access for your account OpenAI API Key (for GPT-5.1 AI analysis) Sign up at https://platform.openai.com Navigate to API keys section and create a new key Ensure you have access to GPT-5.1 model Gmail Account (for receiving reports) OAuth2 authentication will be used No app password needed Configuration steps: Replace Google Ads Customer ID: Open both "Get Last Week Data" and "Get Previous Week Data" HTTP Request nodes In the URL field, replace [Customer ID] with your actual Customer ID (format: XXX-XXX-XXXX) Add Developer Token: In both HTTP Request nodes, add your Google Ads Developer Token to the header parameters Connect Google Ads OAuth2: In both HTTP Request nodes, authenticate with your Google Ads credentials Select your ad account Connect OpenAI credentials: In the "OpenAI Chat Model" node, add your OpenAI API key Verify GPT-5.1 model is selected Configure email delivery: In the "Email Report to User" node, connect your Gmail OAuth2 credentials Update the recipient email address (default: lee@sonalabs.com) Customize subject line if desired Set your schedule (optional): In the "Weekly Trigger" node, configure your preferred day and time Default is Monday at midnight Test the workflow: Click "Execute Workflow" to run manually Verify data pulls correctly from Google Ads Check that AI analysis provides meaningful insights Confirm email report arrives formatted correctly Customize analysis focus (optional): Open the "AI Analyst" node Adjust the prompt to prioritize specific metrics or goals for your business Modify thresholds for "problem campaigns" in the calculation nodes Activate automation: Enable the workflow to run automatically every Monday Monitor the first few reports to ensure accuracy Note: The workflow analyzes the last 7 days vs. the previous 7 days, giving you rolling two-week comparisons every Monday. Adjust the date ranges in the HTTP Request nodes if you need different time periods.
by Cheng Siong Chin
How It Works This workflow automates end-to-end audio translation with quality assurance for content creators, educators, and international teams managing multilingual content. It solves the challenge of translating audio into multiple languages while ensuring accuracy and maintaining organized delivery. The system receives audio files via webhook, splits them into target languages (Arabic, French, Spanish, Chinese, Hindi), and processes each through NVIDIA's Parakeet TDT translation model. OpenAI validates translation quality, and results are enhanced with comprehensive metadata. Successfully translated files are uploaded to Google Drive with organized naming, combined into a summary spreadsheet, and delivered via email notification. Failed translations trigger quality alerts, ensuring reliable output while minimizing manual oversight and reducing translation turnaround time from hours to minutes. Setup Steps Configure NVIDIA API credentials in the "Generate Audio with ElevenLabs" Add OpenAI API key for quality evaluation in the "OpenAI Chat Model" node Set up Google Drive OAuth connection and specify target folder ID for uploads Configure Gmail SMTP credentials for notification delivery Update webhook URL in source applications to trigger workflow Customize target languages in "Split Languages" node if needed Prerequisites Active accounts: NVIDIA (build.nvidia.com), OpenAI, Google Drive, Gmail. API credentials for all services. Use Cases International podcast distribution, e-learning course localization Customization Modify target languages in Split node, adjust quality thresholds in OpenAI evaluation Benefits Reduces translation time by 90%, eliminates manual quality checks through automated validation Here are clear, professional subheadings for each What / Why pair. They’re concise, action-oriented, and fit well in technical workflow documentation.
by DIGITAL BIZ TECH
AI-Powered Timesheet → Invoice Automation (Gmail + OCR + AI + Google Sheets + QuickBooks) > Note: This workflow uses sticky notes extensively to document each logical section of the automation. Sticky notes are mandatory and already included to explain OCR, AI parsing, folder logic, duplicate handling, and QuickBooks steps. This workflow automates the full lifecycle of timesheet-based invoicing — from emailed timesheets to structured Google Sheets records and finalized invoices in QuickBooks Online. It is designed for real-world billing scenarios, including split weeks across months, zero-hour months, duplicate prevention, and first-week-of-year edge cases. What This Workflow Does Listens to Gmail for timesheet emails with attachments Splits and processes each attachment independently Extracts text using OCR (no hardcoded API keys) Uses AI to parse month-wise billable hours Correctly splits weeks spanning multiple months Looks up Customer and PO details from Google Sheets Organizes files in Client → Employee → Year folders in Google Drive Reuses existing invoice sheets or creates new ones Prevents duplicate invoice rows Automatically finds or creates customers in QuickBooks Creates invoices in QuickBooks using validated data High-Level Workflow Stages Gmail Intake and Attachment Loop OCR Text Extraction AI-Based Timesheet Parsing Month Normalization and Validation Customer & PO Lookup Drive Folder Discovery and Creation Invoice Sheet Reuse or Creation Duplicate and Edge-Case Handling Append Invoice Rows to Google Sheets Create / Update Customers in QuickBooks Create Invoices in QuickBooks Each of these stages is clearly documented with sticky notes inside the workflow canvas. Quick Setup Instructions Import the workflow JSON into your n8n instance Configure credentials for: Gmail Google Drive Google Sheets OpenAI or Google Gemini QuickBooks Online Verify the OCR HTTP node: Default URL: https://universal-file-to-text-extractor.vercel.app/extract No hardcoded API keys are used Configure Get Customer Info From PO Sheet: Spreadsheet ID Sheet name and column mappings Ensure the Client Invoices root folder exists in Google Drive Send a test timesheet email Execute the workflow once manually Activate the workflow Who This Workflow Is For Agencies and consultancies billing from emailed timesheets Finance and operations teams using Google Workspace + QuickBooks Staffing firms with monthly or bi-weekly contractor billing Teams that want a fully auditable, zero-manual invoice process Requirements n8n instance Gmail account receiving timesheet emails Google Drive and Google Sheets OpenAI or Google Gemini API OCR API endpoint (configurable) QuickBooks Online account Customer PO Google Sheet containing: Email Customer Name Company Name Customer Account Number PO Number Item Folder Name Invoice range Due Date Calculation How It Works (Detailed) 1. Email Intake and Attachment Loop Gmail Trigger polls for timesheet emails Attachments are split so each file is processed independently Sticky notes explain the intake and loop logic 2. OCR Extraction Each attachment is sent to the OCR API PDFs and images are converted to plain text OCR logic is documented via sticky notes 3. AI Timesheet Parsing (Month-Wise) AI extracts data only from BILLABLE HOURS sections Outputs strict JSON: Employee Name Client Name Month Year Week Start Date Week End Date Total Billable Hours Special handling included: Split weeks across months Zero-hour months still included No guessed or inferred dates 4. Month Normalization and Validation AI output is normalized into a month array Each month is processed independently Invalid or zero-hour entries are skipped 5. Customer and PO Lookup Sender email is matched in the PO sheet Retrieved values drive: Folder structure Invoice logic Due date calculation 6. Google Drive Folder Structure The workflow enforces a strict hierarchy: Client Invoices └── Client └── Employee └── Year Missing folders are created automatically. 7. Invoice Sheet Naming and Search Sheet names are generated using: Employee Name Month Year Existing sheets are reused when found Supports monthly and 15-day billing cycles 8. Duplicate Prevention and Edge Cases Duplicate invoice rows are detected and skipped January first-week edge case is handled explicitly Safe re-runs are supported 9. Google Sheets Invoice Rows Each appended row includes: Customer Account Number Invoice Date Due Date PO Number Item Name Quantity (Total Hours) Period description 10. QuickBooks Integration Searches for existing customers in QuickBooks Creates customers automatically if missing Creates invoices using: Customer reference Item Quantity Invoice date Due date All QuickBooks logic is documented with sticky notes. How To Customize Swap AI model (OpenAI ↔ Gemini) Extend prompts to extract: Project Cost center Approval status Add tax codes, currency, or unit pricing Modify folder naming rules Insert approval steps before invoice creation Common Use Cases Monthly contractor invoicing Agency billing across multiple clients Finance automation with audit-ready records Eliminating manual timesheet-to-invoice work Troubleshooting | Issue | Likely Cause | |------|-------------| | No invoices created | Gmail filter mismatch or email already read | | OCR output empty | Unsupported file or OCR endpoint issue | | Wrong month split | Review AI prompt and month logic | | Duplicate rows | Duplicate detection conditions | | Invoice missing in QuickBooks | Customer or item configuration issue | Notes on Community Guidelines Sticky notes are used throughout the workflow No hardcoded API keys are present Markdown is used (no HTML tags) This workflow is original and not copied Need Help or Customization? Digital Biz Tech can help tailor this workflow to your business. We offer free setup support, including credential configuration and deployment. Contact: rajeet.nair@digitalbiz.tech Website: https://www.digitalbiz.tech LinkedIn: https://www.linkedin.com/company/digital-biz-tech/ You can also DM us on LinkedIn for any help. You can also DM us on LinkedIn.
by Milo Bravo
Event Registration + Auto-Enrichment Intelligence Who is this for? Event organizers, conference planners, and marketing teams fighting registration drop-off who want 4-field forms with LinkedIn-level attendee intelligence. What problem is this workflow solving? Multi-page forms kill conversions: 80-90% drop-off on page 2 No attendee insights post-reg Manual enrichment wastes hours Abandoned carts = lost revenue This captures 4 fields but enriches 15+ data points automatically. What this workflow does 3 Webhook Intelligence Suite: POST /event-registration**: 4-field form → enrichment → HubSpot POST /reg-beacon**: Abandoned cart tracking pixel POST /validate-promo**: AJAX promo code validation Requires 2 sub-workflows: 1) Abandoned Cart Recovery 2) Participant Re-engager Enrichment Waterfall: Clearbit → LinkedIn (Proxycurl) → Google+AI → Full profile Outputs: HubSpot contacts with company/role/title Data Tables: enriched_profiles / reg_analytics Slack alerts + email confirmations Setup (12 minutes) Data Tables**: enriched_profiles, reg_analytics, promo_codes HubSpot**: API key + custom properties APIs**: Clearbit, Proxycurl, SerpAPI, Gemini Host**: reg-page/index.html (update webhook URLs) SMTP/Slack**: Notifications Fully configurable, no code changes needed. How to customize to your needs Forms**: Swap HTML for Typeform/Webflow Enrichment**: Add Apollo/Hunter for emails CRM**: HubSpot → Salesforce → Airtable Promos**: Tiered discounts / early-bird Companion**: Abandoned Cart + Re-engager templates ROI: 3x registration completion** (4 fields vs 12+) 65% enriched profiles** (company/role/title) 20% revenue recovery** (abandoned carts) Need help customizing?: Contact me for consulting and support: LinkedIn / Message Keywords: event registration, attendee enrichment, abandoned cart recovery, conference automation, HubSpot
by Cheng Siong Chin
How It Works This workflow automates platform trust and safety operations by deploying a multi-agent AI system that detects abuse signals, investigates behaviour, scores risk, checks policy compliance, and enforces actions automatically. Designed for platform safety teams, content moderation managers, and compliance officers, it eliminates manual triage delays and ensures high-severity violations are actioned immediately. An abuse signal webhook triggers behaviour analysis via OpenAI, classifying signals by severity. A routing node directs cases to a Governance Agent, which orchestrates Investigation, Risk Scoring, and Policy Compliance Checker sub-agents. Enforcement data is prepared, then routed by action type-logging to abuse records, alerting the security team via Slack, sending escalation emails, or triggering auto-enforcement actions based on threshold checks—before all outcomes are logged. Setup Steps Configure Abuse Signal Webhook URL and authenticate incoming POST requests. Add OpenAI API credentials to all OpenAI Model nodes. Connect Google Sheets for abuse records and enforcement action logging. Configure Slack credentials and set security team alert channel. Add Gmail/SMTP credentials to Send Escalation Email node. Prerequisites Slack workspace with bot token Gmail or SMTP credentials Google Sheets for abuse and enforcement logging Use Cases Real-time abuse detection and auto-suspension on social platforms Customization Replace OpenAI with Anthropic Claude or NVIDIA NIM models Benefits Eliminates manual abuse triage with real-time AI signal processing