Workflow Templates

LinkedIn Lead Enrichment & Cold-Email Sender with Apify + OpenRouter + Gmail Most teams spend hours hunting LinkedIn profiles, enriching company data, and writing cold emails manually. This workflow does it all automatically: lead enrichment, email generation, and sending — directly from a simple Google Sheet. Benefits Find verified LinkedIn profiles with Apify scrapers Enrich company data automatically from LinkedIn Generate fully personalized cold emails with Claude 3.7 Sonnet (OpenRouter) Send emails directly through Gmail Batch-safe with error handling so the workflow never stalls Log all results and errors back to Google Sheets How It Works Add leads (First Name, Last Name, Company, Email) to Google Sheets Loop through leads in batches to avoid rate limits Search Google for “{First} {Last} {Company} site:linkedin.com” and keep only profile links Fetch person details via Apify linkedin-profile-detail (continue even if some fail) Enrich company data: use current_company_url or search for company page if missing Fetch LinkedIn company details via Apify linkedin-company-detail Generate subject + email body with Claude 3.7 Sonnet (validated with structured JSON output) Send email with Gmail OAuth2 and log status to Google Sheets Who Is This For B2B founders doing manual outbound SDR teams building lead lists Lead-gen and growth agencies wanting scalable outreach Setup Connect Google Sheets (select your leads sheet) Add Apify token for all scrapers (rag-web-browser, linkedin-profile-detail, linkedin-company-detail) Enter OpenRouter API key (Claude 3.7 Sonnet or preferred model) Connect Gmail via OAuth2 Configure sender_name, signature, and domain settings Set batch size, retries, and rate-limit thresholds ROI & Monetization Save 5–8 hours per week on research and copywriting Offer as a $1k–$3k/month outreach automation for clients Upsell deliverability monitoring and sequence testing for premium retainers Strategy Insights In the full walkthrough, I show how to: Build this workflow step by step with resilient error handling (alwaysOutputData, continue on error) Pitch it as a “Done-For-You Personalized Outreach System” Automate outreach to agencies, consultants, and SaaS teams that need enrichment Turn this into recurring revenue with retainers Check Out My Channel For more advanced AI automation systems that generate real business results, check out my YouTube channel where I share the exact strategies I use to build automation agencies, sell high-value services, and scale to $20k+ monthly revenue.

Local Lead Finder + Cold Email Sender (Form → Apify → AI → Gmail + Google Sheets) Fill a short form with business type, location, and how many leads you want. This workflow finds local businesses, grabs a valid email from each website, writes a cold email in your chosen style, sends it, and logs everything to Google Sheets. Benefits Simple form input (business type, location, lead count, email style) Finds local businesses with Apify and filters only those with a website Scrapes one best email address from each site Writes cold emails with AI (style: Friendly / Professional / Simple) Sends via Gmail and updates Google Sheets with status + send time How It Works Form Submit: Enter Business Type, Location, Lead Number, Email Style. Find Leads (Apify): Search places in the target location (up to your lead count). Filter: Keep only results that include a website. Extract Email (AI): Visit the website and pull one valid email address. Save Lead (Sheets): Add company name, category, website, phone, address, email. Generate Email (AI): Create subject + body using your selected style. Send (Gmail): Email the scraped address; retry-safe. Log Result (Sheets): Mark “Cold Mail Status = ✅” and add send time. Batching/Wait: Process leads one by one with a short wait to avoid limits. Who Is This For Agencies doing local outreach Freelancers offering lead gen services SMBs testing cold email in a city or niche Setup Connect the built-in Form Trigger (use provided fields) Add Apify actor endpoint + token Add Google Gemini (for email extraction) and OpenAI (for email writing) keys Connect Gmail OAuth2 to send emails Connect Google Sheets (Spreadsheet ID + Sheet1) ROI & Monetization Spin up targeted campaigns in minutes (no manual research) Sell as a local lead-gen + outreach package ($500–$2k/campaign) Reuse the form for any niche and city to scale quickly Strategy Insights In the full walkthrough, I show how to: Tune the Apify search for better niches and categories Improve email extraction prompts for higher-quality addresses Adjust templates for short, compliant cold emails Add fallbacks (no email → skip or save for manual review) Check Out My Channel For more AI outreach workflows that get real results, check out my YouTube channel where I share the exact setups I use to win clients and scale to $20k+ monthly revenue.

How it works This AI Customer Success Risk Prediction workflow revolutionizes customer retention by predicting churn risk 30-90 days before it happens. Here's the high-level flow: Daily Data Collection → AI Multi-Signal Analysis → Risk Scoring & Prediction → Smart Risk Routing → AI-Generated Personalized Interventions → CRM Updates & Team Alerts The system automatically gathers data from your product analytics, support system, billing platform, and email tools, then uses GPT-4 to analyze patterns and predict which customers are at risk. It creates personalized intervention strategies and routes them based on urgency level. Set up steps Time to set up: Approximately 45 minutes Prerequisites: Active accounts with your analytics platform, support system, billing provider, CRM, and AI provider Step 1: Import & Configure Workflow (5 minutes) Import the workflow JSON into your n8n instance Review the 3 comprehensive sticky notes for context Understand the AI analysis logic and intervention strategies Step 2: Set Environment Variables (10 minutes) Configure these critical variables: ANALYTICS_API_URL and ANALYTICS_API_KEY HIGH_RISK_SLACK_CHANNEL (for critical alerts) CS_TEAM_EMAIL (intervention sender) CRM_BASE_URL and CALENDAR_BOOKING_URL Step 3: Configure API Credentials (20 minutes) Set up secure credential connections for: OpenAI/Anthropic API (AI analysis engine) Analytics platform (Mixpanel/Amplitude/GA) Support system (Zendesk/Intercom) Billing platform (Stripe/Chargebee) HubSpot CRM (risk data storage) Slack API (team notifications) SMTP/SendGrid (email delivery) Step 4: Customize AI Prompts & Risk Thresholds (8 minutes) Review and adjust the AI analysis prompts for your business Modify risk score thresholds (Critical 90+, High 70-89, Medium 40-69) Customize intervention email templates and tone Set your specific risk factors (usage patterns, support indicators) Step 5: Test & Activate (2 minutes) Run a test execution with sample customer data Verify AI analysis generates appropriate risk scores Check that interventions are routed correctly Activate the daily cron schedule

Summary Send a number to your Telegram bot (e.g., 2) and get a neatly formatted digest of all Gmail newsletters received since that date. Each email is summarized by an LLM into concise topics, merged into a single Telegram message, automatically split into chunks to fit Telegram limits, and safely formatted as HTML. What this workflow does Triggers on your Telegram message containing a number of days, e.g., 1, 2, 7 Fetches all Gmail messages since that date using a custom search query, optionally filtered by senders Retrieves and decodes each email’s HTML, subject, sender name, date Prompts an LLM (GPT‑4.1‑mini) to produce a consistent JSON summary of topics per email Merges topics from all emails into a single digest Builds a readable, enumerated message (with bold titles) Splits it into 3 500‑char parts and sanitizes Markdown to Telegram‑safe HTML Sends the digest to your Telegram chat with preview disabled Apps and credentials Gmail OAuth2: Gmail account Telegram: Telegram account (bot) OpenAI: OpenAi account Typical use cases Personal or team daily/weekly newsletter digests in Telegram Curated feeds from selected senders compiled on demand Lightweight knowledge briefings without leaving Telegram How it works (node-by-node) Telegram Trigger Waits for your message (e.g., "2"). Chat ID is restricted to your Telegram ID for safety. Get days (Code) Takes the numeric daysAgo from the Telegram message text Computes YYYY/MM/DD for Gmail’s after: filter Get many messages (Gmail → getAll, returnAll: true) Uses a custom q filter like: =(from:@.com) OR (from:@.com) OR (from:@.com -"__") after:{{ $json.dateString }} Returns a list of message IDs Loop Over Items (Split in Batches) Iterates through each message ID Get a message (Gmail → get) Retrieves the full message/payload for the current email Get message data (Code) Extracts HTML from Gmail’s payload (body/parts) Normalizes sender to just the name Formats the date as DD.MM.YYYY Passes html, subject, from, date forward Clean (Code) Converts DD.MM.YYYY → MM.DD (for prompt brevity) Passes html, subject, from, date to the LLM Message a model (OpenAI, model: gpt‑4.1‑mini, JSON output) Prompt instructs: Produce JSON: { "topics": [ { "title", "descr", "subject", "from", "date" } ] } Split multi-news blocks into separate topics Combine or ignore specific blocks for particular senders (placeholders __) Keep subject untranslated; other values in __ language Injects subject/from/date/html from the current email Loop Over Items (continues) After all iterations complete, the aggregated per-email results are available Merge (Code) Flattens the topics arrays from all processed emails into one combined topics list Create TG message (Code) Renders an enumerated list: 1. Title (bold) Short description Original subject From — Date Split (Code) Splits into 3 500‑character chunks to stay below Telegram’s 4 096 limit with HTML overhead Sanitize (Code) Escapes &, <, > Fixes unbalanced * and _ Converts basic Markdown markers to Telegram HTML Send a message (Telegram) Sends each part with parse_mode=HTML, previews disabled Node map | Node | Type | Purpose | |---|---|---| | Telegram Trigger | Trigger | Receive daysAgo command from Telegram | | Get days | Code | Compute Gmail after:YYYY/MM/DD from daysAgo | | Get many messages | Gmail (getAll) | Search emails since date with custom from: filters | | Loop Over Items | Split in Batches | Iterate messages one-by-one | | Get a message | Gmail (get) | Fetch full message payload | | Get message data | Code | Extract HTML/subject/from/date; normalize sender and date | | Clean | Code | Reformat date and forward fields to LLM | | Message a model | OpenAI | Summarize email into JSON topics | | Merge | Code | Merge topics from all emails | | Create TG message | Code | Build human-friendly digest text | | Split | Code | Chunk into 3 500‑char parts | | Sanitize | Code | Escape HTML and map Markdown to Telegram HTML | | Send a message | Telegram | Deliver digest to Telegram chat | Before you start Create a Telegram bot and get its token (via @BotFather) Get your Telegram user ID to restrict access Connect Gmail OAuth2 in n8n Add your OpenAI API key Import the provided workflow JSON into n8n Setup instructions 1) Telegram Telegram Trigger node: additionalFields.chatIds = your Telegram user ID Send a message node: chatId = your Telegram user ID parse_mode = HTML disable_web_page_preview = true 2) Gmail Connect a Gmail OAuth2 credential (Gmail account) In Get many messages, adjust filters.q to your senders and rules: Example: =(from:news@publisher.com) OR (from:briefs@media.com -"promo") after:{{ $json.dateString }} If needed, add label: or category: filters 3) OpenAI Message a model: Model: gpt‑4.1‑mini (can swap to gpt‑4o‑mini or your preferred) Update the prompt placeholders: __ language → your target language __ sender rules → your special cases (combine blocks, ignore sections) 4) Safety and formatting Keep parse_mode=HTML in Telegram The Sanitize node is designed for ` and ` only; avoid other HTML tags The Split node uses 3 500 chars per part to stay safe under Telegram limits How to use In Telegram, send a number indicating “days ago” Example: 2 → will query Gmail after the date 2 days ago The workflow compiles and returns a digest in your chat Rerun anytime with a new number Customization ideas Labels instead of global search: q = label:Newsletters after:{{ $json.dateString }} Time window control: add before: or exact date ranges Different language: set the __ language in the LLM prompt Model choice: swap to cheaper/faster models if volume is high Chunk size: adjust from 3 500 to your needs Formatting: tweak Create TG message to include links parsed from HTML (if you add an HTML parser step) Limits and notes Telegram messages are limited to ~4 096 characters; we chunk to 3 500 per part Gmail “after:” uses YYYY/MM/DD and Google’s interpretation of dates; your n8n server time influences the computed date LLM usage incurs cost and latency proportional to email size and count HTML extraction is robust for typical Gmail structures but may need tweaks for exotic MIME layouts Privacy and safety Emails are sent to OpenAI for summarization—ensure that’s acceptable for your data policies The Telegram Trigger restricts chat access; keep your chatIds locked down Avoid sending raw HTML to Telegram; rely on the Sanitize node Sample output format (Telegram) Bold topic title One-sentence description Original Subject Line → Sender Name — DD.MM.YYYY Next topic title ... Tips and troubleshooting Got empty digests? Check Gmail filters.q and make sure there really are emails after the computed date Model errors or empty JSON? Lower prompt complexity or switch model HTML formatting issues in Telegram? Ensure parse_mode=HTML and keep only `, ` Long messages not fully delivered? Reduce chunk size from 3 500 Tags gmail, telegram, openai, llm, newsletters, digest, summarization, automation Changelog v1: Initial release with sender filters, topic merging, Telegram HTML sanitization, and on-demand time window via Telegram message

Who’s it for This template is for individuals or households who want to: Easily digitize and track their spending from physical receipts. Automate budget management and financial reporting. Get quick insights into their spending habits on a daily and monthly basis. Stay informed about their remaining budget through Slack notifications. What it does This workflow automates your household budget tracking in several steps: Receipt Photo Upload: You upload a photo of your receipt to a webhook. Parse Receipt: An AI agent extracts the date, store name, purchased items, and total amount from the receipt text. Add to Budget Sheet: The extracted data is then appended to your designated Google Sheet. Daily Budget Report: After each receipt entry, the workflow calculates your current month's spending, remaining budget, and sends a summary to Slack. Monthly Budget Report: Once a day (triggered by a cron job), it reads all budget data for the current month from Google Sheets, performs an analysis (total spending, daily average, top stores, items, and spending days), and sends a comprehensive report to Slack. How to set up Requirements n8n Account**: Self-hosted or Cloud. Google Sheets**: A Google Sheet set up with columns for "Date", "Store", "Items", and "Amount". Slack Workspace**: A Slack channel where you want to receive budget updates. OpenRouter Account**: An API key for OpenRouter to use their chat models. Steps Google Sheets Setup: Create a new Google Sheet (or use an existing one) and name it "Household Budget". In the first sheet (e.g., "Sheet1"), set up the following headers in the first row: "Date", "Store", "Items", "Amount". Share the Google Sheet with the service account email associated with your n8n Google Sheets credentials, granting "Editor" access. In the 'Add to Budget Sheet' and 'Get Budget Sheet (Daily)' nodes, select your Google Sheet and the appropriate sheet name. OpenRouter Credentials: Sign up or log in to OpenRouter (https://openrouter.ai/). Generate an API key. In n8n, create a new "OpenRouter" credential using your API key. Apply this credential to the 'OpenRouter Chat Model1', 'OpenRouter Chat Model2', and 'OpenRouter Chat Model' nodes. Slack Credentials: In n8n, create a new "Slack" credential. Follow the instructions to connect your Slack workspace. In the 'Send a message' and 'Send monthly report' nodes, select the Slack channel where you want to receive messages. Make sure the Slack app has permission to post to the selected channels. Webhook URLs: After activating the workflow, the 'Receipt Photo Upload' node will generate a webhook URL. Copy this URL. You will use this URL to send receipt text (e.g., from a mobile app that scans text). Monthly Budget Adjustment: In the 'Code in JavaScript2' node, locate the line const budget = 30000; and change 30000 to your desired monthly budget in JPY. How to customize the workflow Daily Report Trigger The 'Daily Report Trigger' node is set to run once a day. You can modify its schedule to trigger more or less frequently by adjusting its cron settings. AI Model You can change the AI models used in the 'OpenRouter Chat Model' nodes to any other large language model supported by n8n, such as OpenAI, Anthropic, or custom hosted models, by updating the credentials and model names. Output Formatting The Slack messages generated by the 'Report Budget' and 'Monthly Report' nodes can be customized by editing the systemMessage and text parameters in those nodes to change the tone, content, or language of the reports. Additional Integrations You can extend this workflow by adding more nodes: Integrate with other accounting software. Send notifications to different platforms (e.g., email, Discord, Telegram). Add sentiment analysis to your spending habits. Categorize expenses automatically based on items or stores using another AI node.

This automated n8n workflow streamlines the process of receiving, processing, and delivering patient-friendly lab reports with precautionary advice. 🏆 Minimal But Complete Design: Node Flow: 📧 Email Trigger → Monitors inbox for lab reports 📄 PDF Extract → Processes attachments & extracts content 🤖 AI Simplify → Converts medical jargon to simple language ✨ Format Response → Creates beautiful patient-friendly layout 📤 Send Report → Delivers simplified report via email 🚀 Key Features: ✅ Automatic Processing: Monitors email for lab report PDFs Extracts content from attachments No manual intervention needed ✅ AI-Powered Simplification: Converts complex medical terms to plain English Explains what each test result means Adds ✅/⚠️ indicators for normal/abnormal results ✅ Patient-Friendly Output: Professional HTML email formatting Clear sections: Summary, Results, Precautions Includes next steps and follow-up advice ✅ Built-in Safety: Always includes medical disclaimers Encourages consulting healthcare providers Handles edge cases with fallbacks 🛠️ Setup Requirements: APIs Needed: IMAP Email** (Gmail, Outlook, etc.) Ollama AI Model** (Local medical AI) SMTP Email** (Sending service) Quick Configuration: Import the JSON into n8n Set up email credentials (IMAP + SMTP) Configure Ollama medical model Test with a sample lab report 📋 Sample Output: 🩺 Your Lab Report - Simplified ✅ CHOLESTEROL: 180 mg/dL - Normal! Good job maintaining healthy levels. ⚠️ BLOOD SUGAR: 126 mg/dL - Slightly high Normal is under 100. Consider reducing sugar intake. 🔬 VITAMIN D: 25 ng/mL - Low You may need supplements. Ask your doctor. 📋 PRECAUTIONS: • Eat more fruits and vegetables • Exercise 30 minutes daily • Schedule follow-up in 3 months • Watch for: excessive thirst, fatigue

Introduction Automatically imports Excel schedules from Google Drive, validates data with AI, syncs to Google Calendar, and emails smart summaries. Ideal for educators, managers, and administrators handling recurring academic or project schedules. How It Works Trigger → Download Excel → Filter events → Dual AI analysis (OpenAI + Parser) → Merge insights → Enrich data → Create/Update Google Calendar events → Generate and email AI summary. Workflow Template Trigger → Download Excel → Filter Events → AI Analysis → Merge Insights → Enrich Data → Create/Update Calendar → AI Summary → Email Report Workflow Steps Trigger: Runs on schedule to detect new files. Read Excel: Converts spreadsheet data to JSON. Filter Events: Removes invalid entries. AI Context Analysis: Understands event links and conflicts. Structured Parser: Formats AI output for consistency. Merge Insights: Combines multi-AI results. Enrich Data: Prepares Google Calendar-ready events. Calendar Actions: Creates or updates events. AI Summary: Generates executive overview. Email Delivery: Sends formatted summary report. Setup Google Drive: Connect OAuth2 → get file ID. Calendar: Enable API → authorize in n8n. OpenAI: Add API key → select GPT model. Email (Gmail/SMTP): Configure sender and recipients. Trigger: Set timezone and frequency. Excel Format: Include Name, Date, Time, Location, Staff, etc.

Who it's for Construction and renovation businesses that need to generate detailed quotes from customer inquiries—plasterers, painters, contractors, renovation specialists, or any construction service provider handling quote requests through online forms. What it does Automatically transforms JotForm submissions into professional, itemized construction quotes with complete CRM tracking—no subscription needed (saving €200-500/year). When a customer fills your project request form (specifying wall/ceiling areas, finish types, ceiling heights, wet areas, prep work), the workflow extracts measurements, normalizes service selections, applies intelligent pricing rules from your Supabase catalog, calculates line items with material and labor costs plus proper VAT handling, stores everything in a structured CRM pipeline (customer → project deal → estimate), and generates a branded HTML email ready for delivery. This self-hosted pricing engine replaces paid invoicing software for quote generation, saving thousands over time while eliminating manual takeoffs and quote preparation— from 30-60 minutes to under 30 seconds. How it works Stage 1: JotForm webhook triggers → Parser extracts project data (m² measurements, service types, property details) → Normalize Dutch construction terms to database values → Save raw submission for audit trail Stage 2: Upsert customer record (idempotent on email) → Create project deal → Link to form submission Stage 3: Fetch active pricing rules → Calculate line items based on square meters, service type (smooth plaster vs decorative), ceiling height premiums, property status (new build vs renovation), wet area requirements → Apply conditional logic (high ceilings = price multiplier, prep work charges, finish level) → Group duplicate items → Save estimate header + individual lines Stage 4: Query optimized view (single call, all data) → Generate professional HTML email with logo, itemized services table (description, m², unit price, totals), VAT breakdown, CTA buttons, legal disclaimer Setup requirements Supabase account** (free tier sufficient) - Database for CRM + pricing catalog JotForm account** (free tier works) - Form builder with webhook support Email service** - Gmail, SendGrid, or similar (add your own email node) How to set up 1. Database setup (2 minutes): Run this workflow's "SQL Generator" node to output complete schema Copy output → Paste in Supabase SQL Editor → Click Run Creates 9 tables + 1 optimized view + sample construction services (plastering €21-32/m², painting €12-15/m², ornamental work, ceiling finishes) 2. Credentials: Add Supabase credentials to n8n (Project URL + Service Role Key from Supabase Settings → API) No JotForm credentials needed (uses webhook) 3. JotForm webhook: Clone demo construction form: [jotform stucco planet demo](https://form.jotform.com/252844786304060 )- Form fields: Property type, postcode, services needed, wall/ceiling m², finish level, ornament quantities, molding meters, wet areas, ceiling heights, prep removal, start date, customer contact Settings → Integrations → Webhooks → Add your n8n webhook URL Test with preview submission 4. Customize email: Update company info in "Generate Email HTML" node (logo, business address, contact details, Chamber of Commerce number, VAT number) Adjust colors/branding in HTML template Available in Dutch and English versions How to customize Add your construction services: Edit price_catalog table in Supabase (no code changes): INSERT INTO price_catalog (item_code, name, unit_price, vat_rate, unit_type) VALUES ('DRYWALL_INSTALL', 'Drywall Installation', 18.50, 9, 'm²');

Who’s it for This template is perfect for SEO writers, niche bloggers, and content marketers who want to generate high-quality blog posts from a single keyword without spending hours on research and writing. If you often find yourself stuck at the research stage or manually drafting blog content, this workflow automates the entire process from topic discovery to publication. What it does The workflow takes a keyword, performs a Google search using Dumpling AI, analyzes the top-ranking pages and People Also Ask (PAA) questions, and then uses GPT-4 to generate a detailed blog post based on the most valuable question. The blog draft is sent for approval via email, and once approved, it’s automatically published to WordPress. Here’s what happens step by step: Receives a keyword through a simple form Uses Dumpling AI to perform a Google search and extract: Top 2 organic search results People Also Ask (PAA) questions and answers Top related searches Filters for insightful PAA questions Sends the data to GPT-4 to generate a blog post in JSON format Emails the draft blog post for manual review and approval If approved, publishes the post automatically to WordPress How it works Form Trigger: Captures the keyword input Dumpling AI: Searches Google and extracts SEO data including top results, PAA, and related searches Code Node: Processes the raw search data into a structured format for GPT-4 Filter Node: Checks if PAA questions are available GPT-4: Chooses a strong PAA question and writes the blog post Gmail: Sends the draft blog post to your inbox for review Approval Node: Waits for manual approval WordPress: Publishes the approved post automatically Requirements ✅ Dumpling AI API key stored securely as credentials ✅ OpenAI GPT-4 credentials ✅ Gmail account with OAuth2 connected to n8n ✅ WordPress account with API credentials configured How to customize Edit the GPT-4 prompt to control the blog structure, tone, or style Add extra filters to select specific types of PAA questions (e.g., how-to, guides) Change the review recipient email in the Gmail node Add additional formatting or SEO optimization steps before publishing Integrate with Notion, Airtable, or Slack to log or notify team members after publication > This workflow turns a single keyword into a fully researched, GPT-4 generated, and auto-published blog post — helping you scale content creation efficiently while maintaining quality.

Simple Coupon Points Tracker with Google Sheets and Weekly Summary Email Take full control of your expected loyalty points. This workflow helps you log every coupon and the points you should receive, store proof of purchase, and get a weekly summary so you can quickly spot any points that haven’t been credited and follow up with the program if needed. Who’s it for Ideal for frequent coupon users or anyone collecting loyalty points from programs like Payback, Miles & More, or similar reward systems. If you want a centralized, reliable way to track expected points, organize screenshots, and make sure nothing goes missing, this workflow is built for you. How it works Log coupon details and screenshots: Submit your coupon info via an n8n form. Screenshots are automatically saved in a Google Drive folder, and coupon data is appended to a Google Sheet. Weekly points summary: Every week, a scheduled trigger scans your sheet for coupons that are due to have points credited. It generates a clear summary email via Gmail so you can easily see which points are expected and follow up if the program hasn’t credited them. How to set up Google credentials: Configure OAuth2 credentials in n8n for Google Drive, Sheets, and Gmail. Google Drive: Create a folder for storing screenshots and link it in the workflow. Google Sheets: Create a sheet with these columns, or use the Google Sheets Template and then set the sheet ID and name in the workflow nodes. Coupon Name | Account Used to Buy | Program | Points | Bonus Points | Purchase Date | Redeem Delay (days) | Claimable Date | Coupon Screen Email node: Configure Gmail credentials and recipient address for weekly summaries. Form trigger: Open the form URL to submit coupon data from any device. Schedule trigger: Runs weekly to send the summary; timing can be adjusted. Requirements n8n instance with Google OAuth2 credentials for Drive, Sheets, and Gmail Google Drive folder ID for screenshots Google Sheets ID and sheet name for logging points Gmail account for sending summary emails Stay on top of your expected points, ensure no reward slips through the cracks, and keep proof safely stored automatically. Happy tracking!

Description Keep your product and project teams perfectly aligned by automatically syncing task dependencies between Jira and Monday.com. This workflow ensures real-time visibility into cross-platform blockers and dependencies, allowing smoother delivery across multiple teams and tools. 🔄📅💼 What This Template Does Step 1: Trigger the workflow on a schedule or manual run. Step 2: Fetch project tasks and dependencies from Jira. Step 3: Retrieve matching items from Monday.com based on linked project IDs or issue keys. Step 4: Compare dependencies between both systems. Step 5: Identify mismatched or missing dependencies across platforms. Step 6: Send summarized reports to Slack or Gmail for team visibility. Step 7: Optionally update Monday.com or Jira items with dependency status tags. Key Benefits ✅ Maintain alignment across multiple projects and teams. ✅ Detect and resolve dependency conflicts before they cause delays. ✅ Automate visibility — no more manual cross-checking. ✅ Simplify multi-tool management for product and engineering leads. Features Integration between Jira Cloud and Monday.com API Cross-dependency comparison logic Scheduled or manual execution Slack/Gmail notifications for updates or conflicts Custom mapping for project and issue identifiers Requirements Jira Cloud account with API credentials Monday.com API key or OAuth2 token Optional: Slack or Gmail credentials for notifications n8n instance (cloud or self-hosted) Target Audience Product and Project Managers coordinating across tools 🧩 Engineering Leads overseeing multi-platform sprints ⚙️ PMOs managing dependencies across cross-functional teams 📊 Operations teams aiming for unified delivery visibility 📈 Step-by-Step Setup Instructions Connect your Jira and Monday.com credentials in n8n. Map project identifiers or keys between Jira and Monday.com. (Optional) Configure Slack or Gmail for daily status alerts. Adjust the cron expression to match your monitoring schedule. Run the workflow once manually to validate mappings. Activate the workflow for ongoing dependency tracking. ✅

📌 Description Automate your course enrollment process with this workflow that handles student submissions, evaluates eligibility, and sends acceptance or rejection emails — all without manual effort. It's perfect for instructors managing multi-week technical courses who want to streamline onboarding and communication. ⚙️ How It Works 📥 Captures student registration data via an n8n Form Trigger 📊 Evaluates responses (e.g., checks programming background & availability) 📤 Sends automated, personalized acceptance or rejection emails based on criteria 📝 Logs submission outcomes for review 📨 Optionally stores records in Google Sheets, Airtable, or a database (customizable) 🛠️ Set Up Steps 🔗 Connect Gmail (or your preferred email service) ✅ Add your course filtering logic to the decision node (simple JSON rules) 📄 Customize email templates (plain or HTML) 🧪 Test the flow with sample submissions ⏱️ Setup Time: 10–15 minutes (depending on integrations) 🔐 Notes No hardcoded API keys used – all credentials must be set up using the n8n credential system Sticky notes inside the workflow provide detailed setup and customization tips Easily extendable to add payment links, WhatsApp alerts, or CRM integration