Workflow Templates

How It Works This workflow automates comprehensive real estate investment analysis by orchestrating specialized AI agents to evaluate property data, market trends, and financial metrics. Designed for real estate investors, portfolio managers, and property analysts managing multiple properties or evaluating acquisition opportunities, it eliminates the manual research and analysis that typically requires days of work across multiple data sources. The system aggregates data from real estate APIs, market databases, and local statistics, then deploys specialized agents: performance analysis evaluates ROI and cash flow, recommendation engines identify optimal properties, market analysis assesses location trends, sentiment analysis mines reviews and local feedback, and workflow tools calculate financial projections. An orchestrator coordinates these agents to generate consolidated investment reports with property rankings, risk assessments, and portfolio recommendations. Results populate Google Sheets dashboards and trigger email notifications, transforming weeks of analysis into automated insights delivered in hours. Setup Steps Configure real estate API credentials (Zillow/Realtor.com) Add market data API keys for local statistics and demographics Input NVIDIA API keys for all OpenAI Model nodes Set OpenAI API key in Team Collaboration Agent/Orchestrator Configure Calculator Tool parameters for financial projections Connect Google Sheets and specify portfolio tracking spreadsheet ID Set up Gmail credentials and specify recipient addresses for reports Prerequisites NVIDIA API access, OpenAI API key, real estate data API subscriptions Use Cases Multi-property portfolio analysis, acquisition opportunity screening. Customization Adjust investment criteria thresholds, add custom financial metrics Benefits Reduces analysis time by 90%, evaluates unlimited properties simultaneously

UTM Link Creator & QR Code Generator with Scheduled Google Analytics Reports This workflow enables marketers to generate UTM-tagged links, convert them into QR codes, and automate performance tracking in Google Analytics with scheduled reports every 7 days. This solution helps monitor traffic sources from different marketing channels and optimize campaign performance based on analytics data. Prerequisites Before implementing this workflow, ensure you have the following: Google Analytics 4 (GA4) Account & Access Ensure you have a GA4 property set up. Access to the GA4 Data API to schedule performance tracking. Refer to the Google Analytics Data API Overview for more information. Airtable Account & API Key Create an Airtable base to store UTM links, QR codes, and analytics data. Obtain an Airtable API key from your Account Settings. Detailed instructions are available in the Airtable API Authentication Guide. Step-by-Step Guide to Setting Up the Workflow 1. Generate UTM Links Create a form or interface to input: Base URL** (e.g., https://example.com) Campaign Name** (utm_campaign) Source** (utm_source) Medium** (utm_medium) Term** (Optional: utm_term) Content** (Optional: utm_content) Append UTM parameters to generate a trackable URL. 2. Store UTM Links & QR Codes in Airtable Set up an Airtable base with the following columns: UTM Link** QR Code** Campaign Name** Source** Medium** Date Created** Adjust as needed based on your tracking requirements. For guidance on setting up your Airtable base and using the API, refer to the Airtable Web API Documentation. 3. Convert UTM Links to QR Codes Use a QR code generator API (e.g., goqr.me, qrserver.com) to generate QR codes for each UTM link and store them in Airtable. 4. Schedule Google Analytics Performance Reports (Every 7 Days) Use the Google Analytics Data API to pull weekly performance reports based on UTM parameters. Extract key metrics such as: Sessions Users Bounce Rate Conversions Revenue (if applicable) Store the data in Airtable for tracking and analysis. Adjust timeframe as needed For more details on accessing and using the Google Analytics Data API, consult the Google Analytics Data API Overview. Benefits of This Workflow ✅ Track Marketing Campaigns: Easily monitor which channels drive traffic. ✅ Automate QR Code Creation: Seamless integration of UTM links with QR codes. ✅ Scheduled Google Analytics Reports: No manual reporting—everything runs automatically. ✅ Improve Data-Driven Decisions: Optimize ad spend and marketing strategies based on performance insights. This version ensures proper Markdown structure, includes relevant documentation links, and improves readability. Let me know if you need any further refinements! 🚀

About the Automation Staying on top of competitor pricing changes can be a full-time job. Manual price tracking is time-consuming and prone to errors, especially when dealing with complex pricing structures and multiple subscription tiers. Paid competitor price monitoring tools like Competera, Visualping and Fluxguard can be expensive. What if you could automate this process and get instant alerts when competitors adjust their pricing? How to easily monitor competitor pricing With this automation, you'll learn how to set up automated price monitoring system using Airtop's built-in node in n8n. By the end, your system will automatically track competitor pricing changes and notify you of any modifications. What You'll Need A free Airtop API Key Google Sheets account with a copy of this sheet URLs of competitors' pricing pages Understanding the Process This automation continuously monitors competitor pricing pages and compares them against your baseline data. The workflow: Tracks all different pricing plans (monthly, yearly, etc.). Monitors feature changes across different tiers. Detects and logs pricing structure modifications. Alerts you via Slack when changes are detected Setting Up Your Automation We've created a ready-to-use blueprint for seamless price monitoring. Here's how to get started: Connect your Google Sheets Set up your Airtop API connection Define update frequency Customization Options Enhance the basic template with these popular modifications: Add other notification channels (Email, Telegram, etc.). Include feature comparison tracking. Set up threshold-based alerts for significant price changes Track historical pricing trends Real-World Applications Case Study 1: A B2B SaaS company can use this automation to track competitors' pricing changes. When they identify a market-wide pricing shift, they can adjust their strategy proactively within minutes. Case Study 2: An online Ecommerce retailer automates monitoring of 100+ competitor products, maintaining optimal pricing positions and increasing profit margins. Best Practices To ensure accurate tracking: Include detailed baseline data for each pricing tier Specify both monthly and annual pricing clearly List all features included in each plan Update your baseline data whenever you verify changes Include any promotional pricing or special offers Document currency and regional variations if applicable Example Structure in Google Sheets: Competitor: Acme Tools Basic Plan: Monthly: $29 Annual: $290 ($24.17/mo) Features: 5 users, 10GB storage, basic support Pro Plan: Monthly: $79 Annual: $790 ($65.83/mo) Features: 20 users, 50GB storage, priority support What's Next? After setting up your price monitoring automation, consider the following: Creating automated competitive analysis reports Setting up market trend analysis Implementing automatic pricing recommendations Expanding monitoring to feature changes Happy monitoring!

Automated Daily AI Summaries from WhatsApp Groups using a Custom AI Agent Transform your WhatsApp group conversations into actionable business intelligence through automated AI analysis and daily reporting. This workflow eliminates manual conversation monitoring by capturing messages in real-time, processing voice notes, and delivering structured insights directly to your team. Overview This workflow provides complete conversation intelligence automation from message capture to insight delivery. It eliminates manual monitoring, analysis, and reporting by using Evolution API integration, OpenAI transcription, and advanced LLM analysis for hands-free business intelligence that scales your team's awareness of important discussions. Core Function: Autonomous conversation analysis that transforms WhatsApp group chatter into structured business insights with zero manual intervention, maintaining consistent daily reporting while capturing emerging opportunities and trends before your competition. Key Capabilities Real-time message capture - Monitors multiple WhatsApp groups simultaneously with instant processing and smart filtering Voice message transcription - Automatic conversion of audio messages to searchable text using OpenAI Whisper AI-powered insight extraction - Advanced LLM analysis identifies trends, opportunities, and actionable information while filtering noise Automated daily reporting - Scheduled intelligence summaries delivered directly to your team via WhatsApp Multi-group organization - Separate tracking and analysis for different communities with unified reporting Smart content filtering - AI agent trained to focus on business-relevant discussions (AI, automation, tech trends, opportunities) Tools Used n8n: Workflow orchestration managing the entire intelligence pipeline from capture to delivery Evolution API: WhatsApp Business API integration for real-time message monitoring and sending OpenAI Whisper: Voice message transcription ensuring no important audio content is missed OpenRouter/GPT-4.1: Advanced AI analysis for intelligent insight extraction and content filtering Google Sheets: Organized message storage with timestamps and metadata for historical analysis Custom AI Agent: "WhatsOn" - specialized business intelligence detective for tech and automation insights How to Install Import the Workflow: Download the JSON file and import into your n8n instance Configure Evolution API: Set up WhatsApp integration and webhook endpoints for message capture API Credentials Setup: Add OpenAI, OpenRouter, and Google Sheets credentials in n8n Group Configuration: Update group IDs in the "Set Info" node with your monitored groups Google Sheets Setup: Create organized spreadsheet with separate tabs for each group Schedule Configuration: Set your preferred daily summary delivery time Test Execution: Run manual test to verify message capture and AI analysis work correctly Use Cases Business Intelligence Automation: Stay informed about industry discussions without manual monitoring Opportunity Detection: Identify emerging trends, tools, and business opportunities in real-time Team Knowledge Sharing: Automated distribution of relevant insights from multiple communities Competitive Intelligence: Monitor industry discussions to stay ahead of market developments Community Management: Track engagement patterns and important conversations across groups Voice Message Processing: Ensure audio-based insights aren't lost in team communications Setup Requirements Evolution API account: WhatsApp Business integration with webhook capabilities OpenAI API: Voice transcription access through Whisper API OpenRouter account: Access to GPT-4.1 for advanced conversation analysis Google Sheets: Message storage and organization with proper permissions configured WhatsApp Groups: Access to business or professional groups with relevant discussions Total setup time: 15-20 minutes once all API accounts are properly configured. How to Customize Analysis Focus: Modify the AI agent's system prompt to target your industry or specific topics. Adjust keyword priorities, conversation themes, or insight categories based on your business needs. Group Management: Add additional groups by extending the Switch node logic, creating new Google Sheets tabs, and updating group ID variables. Scale from 3 to unlimited group monitoring. Delivery Schedule: Change summary frequency from daily to weekly, multiple times per day, or custom schedules. Add multiple delivery destinations for different team segments. AI Intelligence: Customize the "WhatsOn" agent personality, adjust insight priorities, modify filtering criteria, or add sentiment analysis for deeper conversation understanding. Storage & Organization: Modify Google Sheets structure, add custom metadata fields, integrate with other databases, or connect to business intelligence dashboards for advanced analytics. Advanced Features Smart Voice Processing Automatically transcribes voice messages to text using OpenAI's Whisper API, ensuring critical audio-based discussions are captured and analyzed alongside text conversations. Intelligent Content Filtering The AI agent is specifically trained to identify valuable business insights while filtering out casual conversation, ensuring your daily summaries focus on actionable information that drives decisions. Multi-Fragment Delivery System Large intelligence summaries are automatically broken into properly formatted WhatsApp messages with natural pacing to avoid delivery issues and improve readability. Historical Analysis Capability All conversations are stored with full metadata in Google Sheets, enabling historical trend analysis, keyword tracking, and long-term pattern recognition for strategic planning. Ready to transform group conversations into competitive intelligence? This template converts casual WhatsApp discussions into structured business insights delivered automatically to your team, ensuring you never miss important industry developments or opportunities. Google Sheets Template The workflow includes a pre-configured structure for tracking: Message timestamps and sender information Full conversation content with voice transcriptions Group-specific organization and categorization Daily summary delivery logs and performance metrics Was this helpful? Let me know! I truly hope this WhatsApp intelligence system helps streamline your team's awareness of important conversations. Your feedback helps me create better automation resources for the n8n community. Ready to Build Something Great? If you're looking to take your n8n skills or business automation to the next level, I can help. 🎓 n8n Coaching: Want to become an n8n pro? I offer one-on-one coaching sessions to help you master workflows, tackle specific problems, and build with confidence. ➡️ Book a Coaching Session 💼 n8n Consulting: Have a complex project, an integration challenge, or need a custom workflow built for your business? Let's work together to create a powerful automation solution. ➡️ Inquire About Consulting Services Stay Updated on Automation For more content automation strategies, AI workflow tips, and business automation insights: Follow me on LinkedIn Happy Automating! Daniel Lianes

Quick overview This workflow runs weekly to read KPI rows from Google Sheets, merge them with benchmark KPI data from an HTTP API, calculate week-over-week trends, generate an executive summary with Google Gemini, then send the result via Gmail and Slack and log it back to Google Sheets. How it works Runs on a weekly schedule to start the reporting cycle. Reads weekly KPI data from a Google Sheets spreadsheet and fetches benchmark KPI data from an HTTP endpoint. Normalizes both data sources into a consistent KPI structure and merges them into a single list. Calculates KPI movement metrics such as absolute change, percentage change, trend direction, and whether each metric is above or below target. Sends the consolidated KPI results to Google Gemini to generate a concise executive-style weekly summary. Formats the AI summary for distribution, then sends it via Gmail and Slack and appends a copy to a Google Sheets log. Setup Configure the Schedule Trigger to run on your preferred weekly day and time. Add Google Sheets credentials and set the document and sheet for both the KPI input spreadsheet and the KPI log spreadsheet. Ensure your KPI input sheet includes columns like week_start, channel, metric_name, current_value, previous_value, target_value, and notes. Add a Google Gemini (PaLM) API credential and select the model you want to use for summary generation. Add Gmail credentials and set the recipient email address, and add Slack credentials and choose the target channel for the weekly post. Replace or remove the benchmark HTTP endpoint (jsonplaceholder) if you do not want demo benchmark data mixed into your report. Additional info How To Customize Nodes This workflow is easy to adapt without changing the full structure. Weekly KPI Schedule Trigger Adjust the run day and time to match your reporting cycle. Set Weekly Report Context Change the report title, date label format, or add extra fields such as business unit or reporting owner. Read Weekly KPI Data Switch the spreadsheet, use another tab, or filter source rows before normalization. Fetch Benchmark KPI Data Replace the placeholder API with a live benchmark source such as an analytics API, CRM endpoint, ad platform API, or internal reporting service. Normalize Sheet KPI Data Add more fields from your spreadsheet, such as region, campaign, product line, or owner. Normalize Benchmark KPI Data Change how external metrics are mapped so they match the same schema as your main KPI data. Calculate Weekly KPI Trends Extend the logic to calculate rolling averages, status colors, weighted scoring, or alert thresholds. Build Executive Summary Prompt Refine the prompt for a different writing tone, longer narrative summaries, or department specific outputs. Generate Weekly KPI Summary Switch model versions or tune generation settings if your summaries need more detail or tighter control. Format Email and Slack Message Create separate message structures for leadership, sales, marketing, or clients. Send Weekly Summary Email Send to multiple recipients, use a group mailbox, or route through a different email provider. Send Weekly Summary to Slack Post into multiple channels, threads, or team specific destinations. Log Weekly Summary to Google Sheets Add more columns such as workflow status, report owner, channel count, or execution ID. Add ons You can extend this workflow with additional features such as: Error handling branches for failed API, Slack, Gmail, or Sheets steps Conditional routing so only failed or below target KPIs are escalated Multi team summaries for different departments from the same source file HTML email formatting for richer presentation PDF report generation before email delivery Dashboard sync to a data warehouse or BI tool Approval flow before sending the summary externally Separate prompts for leadership and operational teams Use Case Examples This workflow supports several practical business scenarios, including these common examples: 1. Weekly marketing performance update Pull sessions, leads, and email metrics from Google Sheets, summarize movement, and post the result to leadership each Monday. 2. Agency client KPI reporting Collect weekly client metrics, draft a readable update with AI, and deliver the summary through email and Slack while saving a history log. 3. Operations review automation Track weekly process or service KPIs from a spreadsheet, calculate movement against target, and generate a management ready summary. 4. Startup founder reporting Create a short investor or founder style weekly snapshot from operational metrics without manually preparing a report every week. 5. Benchmark comparison testing Keep the placeholder benchmark branch during development to test merge logic, prompt quality, and final message formatting before switching to real external data. There can be many more use cases for this workflow depending on your reporting structure, KPI sources, and communication channels. Troubleshooting Guide | Issue | Possible Cause | Solution | |---|---|---| | Workflow does not start on schedule | Workflow is inactive or schedule settings are incomplete | Activate the workflow and recheck the Weekly KPI Schedule Trigger configuration | | Google Sheets data is empty | Wrong spreadsheet, wrong tab, or missing access | Reconnect credentials and confirm the correct document and sheet are selected | | KPI calculations look wrong | Source values are stored as text or fields do not match expected names | Review the source sheet columns and confirm Number conversion in the normalization step | | Benchmark data looks irrelevant | Placeholder API is still active | Replace the Fetch Benchmark KPI Data node with your real benchmark source or remove the branch | | Gemini summary is too generic | Prompt is too broad or test data is weak | Improve the Build Executive Summary Prompt node and use more realistic KPI inputs | | Gmail node fails | Gmail credential expired or sending account lacks permission | Reconnect Gmail and test sending from the configured mailbox | | Slack message is not posted | Wrong channel selected or Slack app lacks posting rights | Reconnect Slack, select the correct channel, and verify app permissions | | Log row is not added to Google Sheets | Wrong log sheet or incorrect column mapping | Review the append node, log sheet destination, and mapped column names | | Merge output is incomplete | One branch is not returning records | Test both normalization branches separately and confirm each one outputs items before the merge | | AI output formatting is messy | The formatter node is not extracting the expected Gemini field | Review the Format Email and Slack Message node and confirm which response property contains the summary text | Need Help This workflow can be a solid foundation for a reliable reporting system and it can be tailored further based on your exact business process. If you need help setting up this workflow, replacing the placeholder benchmark API with a production data source, improving the Gemini prompt, adding approval flows or extending the workflow with more channels and logic, WeblineIndia can help. WeblineIndia can assist with: n8n workflow setup and deployment Credential and node configuration Google Sheets, Slack, Gmail, and AI integration setup Prompt optimization for business summaries Production hardening with error handling and retries Building similar custom automation workflows for operations, reporting, sales and marketing Hiring dedicated n8n developers

About The Product Hunt Automation Staying up-to-date with specific topics and launches on Product Hunt can be time-consuming. Manually checking the site multiple times a day interrupts your workflow and risks missing important launches. What if you could automatically get relevant launches delivered to your Slack workspace? How to Monitor Product Hunt In this guide, you'll learn how to create a Product Hunt monitoring system using Airtop's built-in node in n8n. This automation will scan Product Hunt for your chosen topics and deliver the most relevant launches directly to Slack. What You'll Need A free Airtop API key A Slack workspace with permissions to add incoming webhooks Estimated setup time: 5 minutes Understanding the Process The Monitor Product Hunt automation uses Airtop's cloud browser capabilities to access Product Hunt and extract launch information. Here's what happens: Airtop visits Product Hunt and navigates the page It searches for and extracts up to 5 launches related to your chosen topic The information is formatted and sent to your specified Slack channel This process can run on your preferred schedule, ensuring you never miss relevant launches. Setting Up Your Automation We've created a ready-to-use template that handles all the complex parts. Here's how to get started: Connect your Airtop account by adding the API key you created Connect your Slack account Set your prompt in the Airtop node. For this example, we’ve set it to be “Extract up to 5 launches related to AI products” Choose your preferred monitoring schedule. Customization Options While our template works immediately, you might want to customize it for your specific needs: Adjust the prompt and the maximum number of launches to monitor Customize the Slack message format Change the monitoring frequency Add filters for particular keywords or companies Real-World Applications Here's how teams can use this automation: A startup's engineering team could track trends in other product’s tech stack, helping them stay informed about potential issues and improvements. A product manager can track launches of competitor products, enabling them to gather valuable market insights and user feedback directly from the tech community on that launch. Best Practices To get the most out of this automation: Choose Specific Search Terms**: For more relevant results, instead of broad terms like "AI," use specific phrases like "machine learning for healthcare" Optimize Scheduling**: When setting the monitoring frequency, consider your team's workflow. Running the scenario every 4 hours during working hours often provides a good balance between staying updated and avoiding notification fatigue. Set Up Error Handling**: Enable n8n's error output to alert you if the automation encounters any issues with accessing Product Hunt or sending messages to Slack. Regular Topic Review**: Schedule a monthly review of your monitored topics to ensure they're still relevant to your needs and adjust as necessary. What's Next? Now that you've set up your Product Hunt monitor automation, you might be interested in: Creating a similar monitor for other tech websites Setting up automated content curation for your team's newsletter Building a competitive intelligence dashboard using web monitoring Happy Automating!

WhatsApp Bulk Message Broadcast via Google Sheets (n8n Workflow) Use Case This workflow enables automated bulk WhatsApp message broadcasting using the WhatsApp Business Cloud API. It pulls recipient and message data from a Google Sheet, sends templated messages (optionally with image headers), and updates the sheet with the message status. It is ideal for marketing teams, support agents, and businesses handling high-volume outreach. Who Is This For? Businesses conducting WhatsApp marketing or outreach campaigns Customer support or notification teams Administrators seeking an automated, no-code message distribution system using Google Sheets What This Workflow Does Triggers automatically every minute to scan for pending messages Fetches unsent entries from a Google Sheet Limits the number of messages processed per execution to comply with API usage guidelines Sanitizes WhatsApp numbers for proper formatting Sends messages using a pre-approved WhatsApp template (text and optional image) Marks the row as "Sent" in the sheet upon successful delivery Workflow Breakdown (Node by Node) 1. Trigger Every 5 Minutes Initiates the workflow every minute using a scheduled trigger to continuously monitor pending rows. 2. Fetch All Pending Queries for Messaging Reads rows from a Google Sheet where the Status column is empty, indicating they haven’t been processed yet. 3. Limit Restricts processing to 2 rows per execution to manage API throughput. 4. Loop Over Items Uses SplitInBatches to iterate through each row individually. 5. Clean WhatsApp Number A code node that strips non-numeric characters from the WhatsApp No field, ensuring the format is valid for the API. 6. Send Message to 300 Phone No Sends a WhatsApp message using the WhatsApp Cloud API and a pre-approved template. Template includes: An image from the Image URL column (as header, optional) Dynamic variables for the recipient's Name and Message fields Template variables must be pre-defined and approved in the Meta Developer Portal, such as {{1}}, {{2}}. 7. Change State of Rows in Sent1 Updates the Status column to Sent for each successfully processed row using the row number as a reference. Google Sheet Format Structure your Google Sheet as shown below: | WhatsApp No | Name | Message | Image URL | Status | |--------------|------------|---------------------------|---------------------|--------| | +8801XXXXXXX | John Doe | Hello, your order shipped | https://.../img.jpg | | Leave the Status column empty for rows that need to be processed. Requirements WhatsApp Business Cloud API access via Meta for Developers A properly structured Google Sheet as described above Active OAuth2 credentials configured in n8n for: googleSheetsOAuth2Api whatsAppApi Customization Options Update the Limit node to control how many rows are processed in each run Adjust the trigger schedule (e.g., change to every 5 minutes) Replace the message template ID with your own custom-approved one from Meta Add error-handling logic (e.g., IF or Try/Catch nodes) to log failures or set Status = Failed Sample Sheet Template View Sample Google Sheet Workflow Highlights Automated execution every 1 minute Reads and processes only pending records Verifies WhatsApp numbers and delivers templated messages Updates Google Sheet after each attempt Support & Community Need help setting up or customizing the workflow? WhatsApp: Contact Support Discord: Join SpaGreen Server Facebook Group: SpaGreen Community Website: Visit SpaGreen Creative

Quick overview This workflow monitors Gmail for invoice emails, extracts structured fields from attached PDFs using Groq LLMs, validates invoices against Purchase Orders stored in Google Sheets, predicts rejection risk with an LLM, emails suppliers about problems, and logs approved invoices to an AP tracking Google Sheet. How it works Triggers every minute when a new invoice email arrives in Gmail. Downloads the email attachment and extracts text from the invoice PDF. Uses a Groq LLM chain to extract invoice fields (invoice/PO/GRN numbers, supplier details, currency, totals, and line items) into structured JSON. Looks up the referenced PO in a Google Sheets PurchaseOrders table, rejecting the invoice via Gmail if no matching PO is found. Merges the invoice data with the PO record and runs data integrity checks (required fields, non-zero amount, and PO status is Approved), emailing the supplier if validation fails. Applies 3-way match rules against the PO (supplier, amount, currency, PO approval, and presence of GRN) to set the invoice status as APPROVED, FLAGGED, or REJECTED. Uses an LLM to predict invoice rejection risk and, if risk is HIGH, emails the supplier a pre-submission warning, then routes approved invoices to a Google Sheets AP log and non-approved invoices to an AP manual-review Gmail alert. Setup Connect Gmail credentials for the Gmail trigger and all Gmail send/get actions, and verify the sender/recipient rules you want to monitor. Connect Google Sheets credentials and update the document IDs/sheet tabs for the PurchaseOrders lookup sheet and the Invoice Readiness logging sheet. Provide Groq (or compatible) LLM credentials/models for both the invoice extraction and the risk prediction steps. Ensure your PurchaseOrders sheet includes columns like po_number, supplier_name, currency, total_amount, and status (with "Approved" as the expected value). Set the supplier email field in the invoice template (or adjust the email recipient mapping) so supplier notifications go to the correct address. Additional info How To Customize Nodes Adjusting Match Rules:* Open the *3-Way Match Validator** node to edit the JavaScript logic (e.g., you can add a 5% "buffer" for price differences). Switching AI Models:** You can replace the Groq/Llama nodes with OpenAI nodes if you prefer to use GPT-4o for extraction. Email Templates:** The Gmail nodes use HTML templates. You can easily edit the colors, logos, and wording to match your company branding. Add‑ons Slack/MS Teams Integration:** Replace the "Manual Review" email with a real-time notification in a dedicated finance chat channel. Duplicate Detection:** Add a node to check your Google Sheet for existing Invoice Numbers to prevent paying the same bill twice. Currency Conversion:** Integrate a currency API to validate invoices billed in foreign currencies against a base-currency PO. Use Case Examples Supplier Compliance:** Automatically rejecting any invoice that doesn't reference a valid, approved PO. Partial Shipment Handling:** Flagging invoices where the billed amount is less than the PO, requiring a human to verify if it’s a partial delivery. Fraud Prevention:** Identifying "High Risk" invoices where the supplier's name or email does not perfectly match your approved vendor list. Automated Data Entry:** Seamlessly moving data from a PDF attachment into a structured spreadsheet without typing a single character. Proactive Supplier Support:* Automatically telling a supplier *exactly why their invoice might be rejected before they have to call and ask. Troubleshooting Guide | Issue | Possible Cause | Solution | | :--- | :--- | :--- | | Extraction Failed | PDF is a low-quality scan or image. | Ensure the LLM node is using a vision-capable model or OCR is enabled in the PDF node. | | PO Not Found | Leading/Trailing spaces in PO numbers in the Sheet. | Use the .trim() function in the Search ERP node filter. | | Credentials Error | Gmail or Google Sheets token expired. | Re-connect your accounts in the n8n Credentials settings. | | AI Output is Malformed | LLM did not return valid JSON. | Ensure the "Output Parser" is correctly connected and the prompt is set to "STRICT JSON." | Need Help? Setting up automated financial workflows can be complex. If you need a helping hand to customize this workflow or connect it to a different ERP (like SAP, Oracle or QuickBooks) or build a completely custom automation solution, our n8n workflow developers at WeblineIndia are here to help. Our team of n8n experts can help you scale your business processes with high-precision AI integrations. Contact WeblineIndia Today to turn your manual tasks into automated wins!

Who's this for? If you own a website and need to analyze your Google analytics data If you need to create an SEO report on which pages are getting most traffic or how your google search terms are performing If you want to grow your site based on suggestions from data Use case Instead of hiring an SEO expert, I run this report weekly. It checks compares the data from this week to the week before: Views based on countries The top performing pages Google search console performance Watch youtube tutorial here Get my SEO A.I. agent system here Read my detailed case study here How it works The workflow gathers google analytics for the past 7 days then it gathers the data for the week before for comparison. It does this 3 times to get: views per country, engagement per page and google search console results for organic search results. The google analytics nodes has already chosen the correct dimensions and metrics. At the end, it passes the data to openrouter.ai for A.I. analyse. Finally it saves to baserow. How to use this Input your Google analytics credentials Input your property ID Input your Openrouter.ai credentials Input your baserow credentials You will need to create a baserow database with columns: Name, Country Views, Page Views, Search Report, Blog (name of your blog). Created by Rumjahn

Quick overview This workflow runs daily to read competitor product URLs from Google Sheets, fetch each page, use OpenAI to extract price and stock status, and send Slack alerts and Notion logs for significant price drops while updating the latest prices back in Google Sheets. How it works Runs every day on a schedule. Loads configuration values and pulls all competitor rows (including product name, URL, and last known price) from Google Sheets. Fetches each competitor product page URL with retries and, if the request fails, posts an error alert to Slack and continues to the next item. Cleans the fetched HTML into plain text and sends it to OpenAI to extract a price, stock status, and a confidence level. Routes low-confidence extractions to a Slack “manual check” alert, otherwise compares the extracted price to the last known price to detect drops beyond the configured threshold. For significant drops, posts a Slack alert and creates a Notion database entry, then writes the latest checked time and new last-known price back to Google Sheets. After all rows are processed, posts a daily Slack summary with counts of checked items, detected drops, fetch errors, and low-confidence extractions. Setup Connect credentials for Google Sheets, OpenAI, Slack, and Notion. Create a Google Sheet with columns such as productName, competitorUrl, ourPrice, lastKnownPrice, and checkedAt, and set the sheet/document ID and sheet tab in the Google Sheets steps. Update the Config step values for slackAlertChannelId, slackErrorChannelId, notionDatabaseId, googleSheetId, and priceDropThresholdPercent. Ensure the HTTP request step is set to continue on error (so failed fetches route to Slack error alerts instead of stopping the run). Create or choose a Notion database with properties matching the fields being written (for example New Price, Change %, and Competitor URL). Requirements Google Sheet with columns: productName, competitorUrl, ourPrice, lastKnownPrice, checkedAt Google Sheets OAuth2 credential OpenAI API key Slack workspace with two channels (one for price alerts, one for errors/review) Notion database for logging price drops Customization Adjust the price drop threshold percentage in the Config node Change the schedule frequency (default: daily) Extend the AI prompt to extract additional fields like promotional badges or shipping cost Swap Notion for Airtable if preferred

This Template gives the ability to monitor all uplinks for your Meraki Dashboard and then alert your team in a method you prefer. This example is a Teams notification to our Dispatch Channel Setup will probably take around 30 minutes to 1h provided with the Template. Most time intensive steps are getting a Meraki API key which I go over and setting up the Teams node which n8n has good documentation for. Tutorial & explanation https://www.youtube.com/watch?v=JvaN0dNwRNU

Complete AI Product Description Generator Transforms product images into high-converting copy with GPT-4o Vision + Claude 3.5 The Shopify AI Product Description Factory is a production-grade n8n workflow that converts product images and metadata into refined, SEO-aware descriptions—fully automated and region-agnostic. It blends GPT-4o vision for visible attribute extraction, Claude 3.5 Sonnet for premium copy, Perplexity research for verified brand context, Google Sheets for orchestration and audit trails, plus automated daily sales analytics enrichment. Link-header pagination and structured output enforcement ensure reliable scale. To refine according to your usecase connect via my profile @connect Key Advantages Vision-first copywriting Uses gpt-4o to identify only visible physical attributes (closure, heel, materials, sole) from product images—no guesses. Premium copy generation anthropic/claude-3.5-sonnet crafts concise, benefit-led descriptions with consistent tone, length control, and clean formatting. Research-assisted accuracy perplexityTool verifies vendor/brand context from official sources to avoid speculation or fabricated claims. Pagination you can trust Automates Shopify REST pagination via Link headers and persists page_info for resumable runs. Google Sheets orchestration Centralized staging, status tracking, and QA in Products, with ProcessingState for batch/page markers, and Error_log for diagnostics. Bulletproof error feedback errorTrigger + AI diagnosis logs clear, non-technical and technical explanations to Error_log for fast recovery. Automated sales analytics Daily sales tracking automatically captures and enriches total sales data for comprehensive business intelligence and performance monitoring. How It Works Intake and filtering httpRequest fetches /admin/api/2024-04/products.json?limit=200&{page_info} code filters only items with: Image present Empty body_html The currSeas:SS2025 tag Extracts tag metadata such as x-styleCode, country_of_origin, and gender when available Pagination controller code parses Link headers for rel="next" and extracts page_info googleSheets updates ProcessingState with page_info_next and increments the batch number for resumable polling Generation pipeline googleSheets pulls rows with Status = Ready for AI Description; limit throttles batch size openAi Analyze image (model gpt-4o) returns strictly visible features lmChatOpenRouter (Claude 3.5) composes the SEO description, optionally blending verified vendor context from perplexityTool outputParserStructured guarantees strict JSON: product_id, product_title (normalized), generated_description, status googleSheets writes results back to Products for review/publish Sales analytics enrichment Schedule Trigger** runs daily at 2:01 PM to capture previous day's sales httpRequest fetches paid orders from Shopify REST API with date range filtering splitOut and summarize nodes calculate total daily sales Automatic Google Sheets logging with date stamps and totals Zero-sale days are properly recorded for complete analytics continuity Reliability and insight errorTrigger routes failures to an AI agent that explains the root cause and appends a concise note to Error_log. What's Inside (Node Map) Data + API httpRequest (Shopify REST 2024-04 for products and orders) googleSheets (multiple sheet operations) googleSheetsTool (error logging) AI models openAi (gpt-4o vision analysis) lmChatOpenRouter (anthropic/claude-3.5-sonnet for content generation) AI Agent** (intelligent error diagnosis) Analytics & Processing splitOut (order data processing) summarize (sales totals calculation) set nodes (data field mapping) Tools and guards perplexityTool (brand research) outputParserStructured (JSON validation) memoryBufferWindow (conversation context) Control & Scheduling scheduleTrigger (multiple time-based triggers) cron (periodic execution) limit (batch size control) if (conditional logic) code (custom filtering and pagination logic) Observability errorTrigger + AI diagnosis to Error_log Processing state tracking Sales analytics logging Content & Compliance Rules Locale-agnostic copy**; brand voice is configurable per store Only image-verifiable attributes** (no guesses); clean HTML suitable for Shopify themes Optional normalization rules (e.g., color/branding cleanup, title sanitization) Style code inclusion supported when x-styleCode is present Gender-aware content generation when gender tag is present Strict JSON output** and schema consistency for safe downstream publishing Setup Steps Core integrations Shopify Access Token** — Products read + Orders read (REST 2024-04) OpenAI API** — gpt-4o vision OpenRouter API** — Claude Sonnet (3.5) Perplexity API** — vendor/market verification via perplexityTool Google Sheets OAuth** — Products, ProcessingState, Error_log, Sales analytics Configure sheets ProcessingState** with fields: batch number page_info_next Products** with: Product ID Product Title Product Type Vendor Image url Status country of origin x_style_code gender Generated Description Error_log** with: timestamp Reason of Error Sales Analytics Sheet** with: Date Total Sales Workflow Capabilities Discovery and staging Auto-paginate Shopify; stage eligible products in Sheets with reasons and timestamps. Vision-grounded copywriting Descriptions reflect only visible attributes plus verified brand context; concise, mobile-friendly structure with gender-aware tone. Metadata awareness Auto-injects x-styleCode, country_of_origin, and gender when present; natural SEO for brand and product type. Sales intelligence Automated daily sales tracking with Melbourne timezone support, handles zero-sale days, and maintains complete historical records. Error analytics Layman + technical diagnosis logged to Error_log to shorten MTTR. Safe output Structured JSON via outputParserStructured for predictable row updates. Credentials Required Shopify Access Token** (Products + Orders read permissions) OpenAI API Key** (GPT-4o vision) OpenRouter API Key** (Claude Sonnet) Perplexity API Key** Google Sheets OAuth** Ideal For E-commerce teams** scaling compliant, on-brand product copy with comprehensive sales insights Agencies and SEO specialists** standardizing image-grounded descriptions with performance tracking and analytics Stores** needing resumable pagination, auditable content operations, and automated daily sales reporting in Sheets Advanced Features Dual-workflow architecture**: Content generation + Sales analytics in one system Link-header pagination with page_info persistence in ProcessingState Title/content normalization (e.g., color removal) configurable per brand Gender-aware copywriting** based on product tags Memory windows (memoryBufferWindow) to keep multi-step prompts consistent Melbourne timezone support** for accurate daily sales cutoffs Zero-sales handling** ensures complete analytics continuity Structured Output enforcement for downstream safety AI-powered error diagnosis** with technical and layman explanations Time & Scheduling (Universal) The workflow includes two independent schedules: Content Generation**: Every 5 minutes (configurable) for product processing Sales Analytics**: Daily at 2:01 PM Melbourne time for previous day's sales For globally distributed teams, schedule triggers and timestamps can be standardized on UTC to avoid regional drift. Pro Tip Start with small batches (limit set to 10 or fewer) to validate both copy generation and sales tracking flows. The workflow handles dual operations independently - content generation failures won't affect sales analytics and vice versa. Monitor the Error_log sheet for any issues and use the ProcessingState sheet to track pagination progress.