by Airtop
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!
by Airtop
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!
by Daniel Lianes
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
by SpaGreen Creative
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
by Ron
Get weather alerts on your mobile phone via push, SMS or voice call. This flow gets weather information every morning and sends out an alert to your SIGNL4 on-call team. For example you can send out weather alerts in case of freezing temperatures, snow, rain, hail storms, hot weather, etc. The flow also supports automatic alert resolution. So, for example if the temperature goes up again the alert is closed automatically in the app. User cases: Dispatch snow removal teams Inform car dealers to protect the cars outside in case of hail storms Set sails if there are high winds And much more ... Can be adapted easily to other weather warnings, like rain, hail storm, etc.
by WeblineIndia
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!
by Syed Hassan Ali
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
by Gavin
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
by Kumar Shivam
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.
by Wildkick
🚀 Local Multi-LLM Testing & Performance Tracker This workflow is perfect for developers, researchers, and data scientists benchmarking multiple LLMs with LM Studio. It dynamically fetches active models, tests prompts, and tracks metrics like word count, readability, and response time, logging results into Google Sheets. Easily adjust temperature 🔥 and top P 🎯 for flexible model testing. Level of Effort: 🟢 Easy – Minimal setup with customizable options. Setup Steps: Install LM Studio and configure models. Update IP to connect to LM Studio. Create a Google Sheet for result tracking. Key Outcomes: Benchmark LLM performance. Automate results in Google Sheets for easy comparison. Version 1.0
by A Z
Automatically scrape X (Twitter) for posts hiring specific roles (e.g., automation engineers, video editors, graphic designers), filter true hiring intent with AI, deduplicate in Google Sheets, and alert via Telegram. What it does Pulls recent X/Twitter posts for multiple role keywords via Apify. Normalizes each post (text, author, links, location). Uses an AI Agent to keep only posts where the author is hiring (not self-promo). Checks Google Sheets for duplicates by URL before saving. Writes qualified posts to a sheet and sends a Telegram notification. We are using n8n automation roles as the example here How it works (Step by Step) Schedule Trigger – Runs on an interval (currently every 12 hours). Scrape X/Twitter – Apify tweet-scraper fetches up to 50 latest posts for keywords like: n8n developer, looking for n8n, n8n expert, hire AI automation, looking for AI automation. Normalize Fields – Set node maps to: url, text, author.userName, author.url, author.location. AI Filter & Dedupe Check Accept only clear hiring posts for n8n/AI automation roles (reject self-promotion). Queries Google Sheets to see if url already exists; duplicates are dropped. Gate – IF node passes only non-empty AI outputs. Parse JSON Safely – Code node extracts/validates JSON from the AI output. Save to Google Sheets – Appends/updates a row (matching on url). Telegram Alert – Sends a message with the tweet URL, author, location, and text. Who it’s for Freelancers, agencies, and job seekers who want a steady radar of real hiring posts for their target roles. Customization Ideas Swap keywords to track other roles (video editors, designers, copywriters, etc.). Add Slack/Discord notifications. Extend the AI rules (e.g., different geographies or role scopes). Treat the sheet as a mini-CRM (status, outreach date, notes).
by victor de coster
*Smartlead to HubSpot Performance Analytics A streamlined workflow to analyze your Smartlead performance metrics by tracking lifecycle stages in HubSpot and generating automated reports.* Who is this for? (Outbound) Automation Agencies, Sales and marketing teams using Smartlead for outreach campaigns who want to track their performance metrics and lead progression in HubSpot. What problem does this workflow solve? Manual tracking of lead performance across Smartlead and HubSpot is time-consuming and error-prone. This workflow automates performance reporting by connecting your Smartlead data with HubSpot lifecycle stages, providing clear insights into your outreach campaign effectiveness. What this workflow does Automatically pulls performance data from your Smartlead campaigns Cross-references contact status with HubSpot lifecycle stages Generates comprehensive performance reports in Google Sheets Provides customizable reporting schedules to match your team's needs Setup Requirements PostgreSQL Database Set up your PostgreSQL instance (includes $300 free GCP credits) Follow our step-by-step setup guide: Find a step-by-step guide here Google Account Integration Connect your Google Account to n8n Find the guide here Smartlead Configuration Connect your Smartlead instance: Detailed connection guide included in workflow How to customize this workflow Configure the Trigger node to adjust report frequency Modify the Google Sheets template to match your specific KPIs Customize HubSpot lifecycle stage mapping in the Function node Adjust PostgreSQL queries to track additional metrics Need assistance or have suggestions? lmk here