Workflow Templates

How it works This workflow automatically collects a list of companies from Google Sheets, searches for their competitors using SerpAPI, extracts up to 10 relevant competitor names with source links, and logs the results into both Google Sheets and Airtable. It runs on a set schedule, cleans and formats the company list, processes each entry individually, checks if competitors exist, and separates results into successful and “no competitors found” lists for organized tracking. Step-by-step 1. Trigger & Input Auto Run (Scheduled) – Executes every day at the set time (e.g., 9 AM). Read Companies Sheet – Pulls the list of companies from a Google Sheet (List column). Clean & Format Company List – Removes empty rows, trims names, and attaches row numbers for tracking. Loop Over Companies – Processes each company one at a time in batches. 2. Competitor Search Search Company Competitors (SerpAPI) – Sends a query like "{Company} competitors" to SerpAPI, retrieving structured search results in JSON format. 3. Data Extraction & Validation Extract Competitor Data from Search – Parses SerpAPI results to: Identify the company name Extract up to 10 competitor names Capture the top source URL Count total search results Has Competitors? – Checks if any competitors were found: Yes → Proceeds to logging No → Logs in “no results” list 4. Logging Results Log to Result Sheet – Appends or updates competitor data into the results Google Sheet. Log Companies Without Results – Records companies with zero competitors found in a separate section of the results sheet. Sync to Airtable – Pushes all results (successful or not) into Airtable for unified storage and analysis. Benefits Automated Competitor Research – Eliminates the need for manual Google searching. Daily Insights – Runs automatically at your chosen schedule. Clean Data Output – Stores structured competitor lists with sources for easy review. Multi-Destination Sync – Saves to both Google Sheets and Airtable for flexibility. Scalable & Hands-Free – Handles hundreds of companies without extra effort.

💥 AI Image → Professional Video Workflow (NanoBanana Ultra + Kling AI + Blotato) 📄 Documentation: Notion Guide 👤 Who is this for? This workflow is designed for content creators, marketers, fashion brands, AI creators, and automation builders who want to turn a single image into a cinematic, multi-shot professional video, then automatically publish it on platforms like YouTube—without manual editing. It’s especially useful if you already work with Google Sheets, n8n, and AI image/video generation APIs. 🎯 What problem does this workflow solve? (Use case) Creating high-quality video content from images usually requires: Manual image editing Multiple AI tools Video stitching Uploading and publishing steps This workflow fully automates that pipeline: From a single image URL To a cinematic multi-shot video To automatic publishing All driven from a spreadsheet. ⚙️ What this workflow does This workflow runs in two main phases: Step 1 – Contact Sheet Generation (NanoBanana Ultra) Reads an image URL from Google Sheets Downloads the image from Google Drive Uploads it to a public host (tmpfiles) Uses NanoBanana Ultra (edit-ultra) to generate a 2×3 cinematic contact sheet Ensures: Identity preservation Fashion & texture fidelity Consistent lighting and style Saves the generated contact sheet back to Google Drive Updates the spreadsheet status Step 2 – Video Creation & Publishing (Blotato) Splits the contact sheet into 6 keyframes Uploads each frame publicly Uses Kling AI (start–end frame i2v) to generate multiple cinematic video segments Merges the generated clips into a single final video (FFmpeg API) Uploads the final video to Google Drive Publishes automatically to YouTube via **Blotato** Updates the spreadsheet with the final video URL and status 🛠️ Setup To use this workflow, you need: n8n (Cloud or Self-Hosted) Google Sheets Copy the provided template Each row controls one image → one video API Keys AtlasCloud (NanoBanana + Kling) tmpfiles.org (public hosting) Blotato (publishing) Connected Accounts Google Drive Google Sheets Blotato 🎛️ How to customize this workflow You can easily adapt it to your needs: Change video style** Edit the Kling prompt (camera movement, mood, pacing) Adjust video duration** Modify the duration parameter in Kling nodes Use fewer or more shots** Add/remove crop + Kling generation branches Publish to other platforms** Blotato supports multiple social networks Trigger automatically** Use the Schedule Trigger instead of manual execution Different aspect ratios** Adjust NanoBanana aspect_ratio and crop math 🚀 Expected outcome From one image, you get: A high-end editorial contact sheet Multiple cinematic AI-generated video clips One merged professional video Automatically uploaded and published No manual editing. No timeline work. Fully automated. 👋 Need help or want to customize this? 📩 Contact: LinkedIn 📺 YouTube: @DRFIRASS 🚀 Workshops: Mes Ateliers n8n Need help customizing? Contact me for consulting and support : Linkedin / Youtube / 🚀 Mes Ateliers n8n

This n8n template demonstrates how to turn a Telegram bot into a personal AI-powered assistant that understands both voice notes and text messages. The assistant can transcribe speech, interpret user intent with AI, and perform smart actions such as managing calendars, sending emails, or creating notes. Use cases Hands-free scheduling with Google Calendar Quickly capturing ideas as Notion notes via voice Sending Gmail messages directly from Telegram A personal productivity assistant available on-the-go Good to know Voice notes are automatically transcribed into text before being processed. This template uses Google Gemini for AI reasoning.The AI agent supports memory, enabling more natural and contextual conversations. How it works Telegram Trigger – Starts when you send a text or voice note to your Telegram bot. Account Check – Ensures only authorized users can interact with the bot. Audio Handling – If it’s a voice message, the workflow retrieves and transcribes the recording. AI Agent – Both transcribed voice or text are sent to the AI Agent powered by Google Gemini + Simple Memory. Smart Actions – Based on the query, the AI can: Read or create events in Google Calendar Create notes in Notion Send messages in Gmail Reply in Telegram – The bot sends a response confirming the action or providing the requested information. How to use Clone this workflow into your n8n instance. Replace the Telegram Trigger with your bot credentials. Connect Google Calendar, Notion, and Gmail accounts where required. Start chatting with your Telegram bot to add events, notes, or send emails using just your voice or text. Requirements Telegram bot & API key Google Gemini account for AI Google Calendar, Notion, and Gmail integrations (optional, depending on use case) Customising this workflow Add more integrations (Slack, Trello, Airtable, etc.) for extended productivity. Modify the AI prompt in the agent node to fine-tune personality or task focus. Swap in another transcription service if preferred.

How it works This workflow is a professional-grade market intelligence tool designed to bridge the gap between search interest and social media engagement. It automates the end-to-end process of trend discovery and content strategy. Detection: Polls Google Trends RSS daily for rising regional search queries. Parallel Extraction: Concurrently triggers industrial-grade Apify actors to scrape TikTok, Instagram, and X (Twitter) without the risk of account bans. Data Aggregation: Uses custom JavaScript logic to clean and merge disparate data points, optimizing them for LLM processing. AI Analysis: Google Gemini Flash analyzes the data to identify core topics, sentiment, and trend strength. Granular Delivery: Delivers individual, structured reports for each identified trend directly to Discord via Webhooks. Set up steps API Credentials: Prepare your Apify API Token and Google Gemini API Key. Discord Setup: Create a Webhook in your Discord server and paste the URL into the Discord node. Regional Configuration: Set your target country code (e.g., JP, ID, US) in the "Edit Fields" node at the start of the workflow. Node Settings: Ensure all scraper nodes are set to "Continue on Fail" to maintain workflow resilience. Requirements Apify Account. Google Gemini API Key. Discord Server for report delivery.

How it Works This workflow automates intelligent Reddit marketing by monitoring brand mentions, analyzing sentiment with AI, and engaging authentically with communities. Every 24 hours, the system searches Reddit for posts containing your configured brand keywords across all subreddits, finding up to 50 of the newest mentions to analyze. Each discovered post is sent to OpenAI's GPT-4o-mini model for comprehensive analysis. The AI evaluates sentiment (positive/neutral/negative), assigns an engagement score (0-100), determines relevance to your brand, and generates contextual, helpful responses that add genuine value to the conversation. It also classifies the response type (educational/supportive/promotional) and provides reasoning for whether engagement is appropriate. The workflow intelligently filters posts using a multi-criteria system: only posts that are relevant to your brand, score above 60 in engagement quality, and warrant a response type other than "pass" proceed to engagement. This prevents spam and ensures every interaction is meaningful. Selected posts are processed one at a time through a loop to respect Reddit's rate limits. For each worthy post, the AI-generated comment is posted, and complete interaction data is logged to Google Sheets including timestamp, post details, sentiment, engagement scores, and success status. This creates a permanent audit trail and analytics database. At the end of each run, the workflow aggregates all data into a comprehensive daily summary report with total posts analyzed, comments posted, engagement rate, sentiment breakdown, and the top 5 engagement opportunities ranked by score. This report is automatically sent to Slack with formatted metrics, giving your team instant visibility into your Reddit marketing performance. Who is this for? Brand managers and marketing teams** needing automated social listening and engagement on Reddit Community managers** responsible for authentic brand presence across multiple subreddits Startup founders and growth marketers** who want to scale Reddit marketing without hiring a team PR and reputation teams** monitoring brand sentiment and responding to discussions in real-time Product marketers** seeking organic engagement opportunities in product-related communities Any business** that wants to build authentic Reddit presence while avoiding spammy marketing tactics Setup Steps Setup time:** Approx. 30-40 minutes (credential configuration, keyword setup, Google Sheets creation, Slack integration) Requirements:** Reddit account with OAuth2 application credentials (create at reddit.com/prefs/apps) OpenAI API key with GPT-4o-mini access Google account with a new Google Sheet for tracking interactions Slack workspace with posting permissions to a marketing/monitoring channel Brand keywords and subreddit strategy prepared Create Reddit OAuth Application: Visit reddit.com/prefs/apps, create a "script" type app, and obtain your client ID and secret Configure Reddit Credentials in n8n: Add Reddit OAuth2 credentials with your app credentials and authorize access Set up OpenAI API: Obtain API key from platform.openai.com and configure in n8n OpenAI credentials Create Google Sheet: Set up a new sheet with columns: timestamp, postId, postTitle, subreddit, postUrl, sentiment, engagementScore, responseType, commentPosted, reasoning Configure these nodes: Brand Keywords Config: Edit the JavaScript code to include your brand name, product names, and relevant industry keywords Search Brand Mentions: Adjust the limit (default 50) and sort preference based on your needs AI Post Analysis: Customize the prompt to match your brand voice and engagement guidelines Filter Engagement-Worthy: Adjust the engagementScore threshold (default 60) based on your quality standards Loop Through Posts: Configure max iterations and batch size for rate limit compliance Log to Google Sheets: Replace YOUR_SHEET_ID with your actual Google Sheets document ID Send Slack Report: Replace YOUR_CHANNEL_ID with your Slack channel ID Test the workflow: Run manually first to verify all connections work and adjust AI prompts Activate for daily runs: Once tested, activate the Schedule Trigger to run automatically every 24 hours Node Descriptions (10 words each) Daily Marketing Check - Schedule trigger runs workflow every 24 hours automatically daily Brand Keywords Config - JavaScript code node defining brand keywords to monitor Reddit Search Brand Mentions - Reddit node searches all subreddits for brand keyword mentions AI Post Analysis - OpenAI analyzes sentiment, relevance, generates contextual helpful comment responses Filter Engagement-Worthy - Conditional node filters only high-quality relevant posts worth engaging Loop Through Posts - Split in batches processes each post individually respecting limits Post Helpful Comment - Reddit node posts AI-generated comment to worthy Reddit discussions Log to Google Sheets - Appends all interaction data to spreadsheet for permanent tracking Generate Daily Summary - JavaScript aggregates metrics, sentiment breakdown, generates comprehensive daily report Send Slack Report - Posts formatted daily summary with metrics to team Slack channel

WhatsApp Bulk Number Verification in Google Sheets Using Unofficial Rapiwa API Who’s it for This workflow is for marketers, small business owners, freelancers, and support teams who want to automate WhatsApp messaging using a Google Sheet without the official WhatsApp Business API. It’s suitable when you need a budget-friendly, easy-to-maintain solution that uses your personal or business WhatsApp number via an unofficial API service such as Rapiwa. How it works / What it does The workflow looks for rows in a Google Sheet where the Status column is pending. It cleans each phone number (removes non-digits). It verifies the number with the Rapiwa verify endpoint (/api/verify-whatsapp). If the number is verified: The workflow can send a message (optional). It updates the sheet: Verification = verified, Status = sent (or leaves Status for the send node to update). If the number is not verified: It skips sending. It updates the sheet: Verification = unverified, Status = not sent. The workflow processes rows in batches and inserts short delays between items to avoid rate limits. The whole process runs on a schedule (configurable). Key features Scheduled automatic checks (configurable interval; recommended 5–10 minutes). Cleans phone numbers to a proper format before verification. Verifies WhatsApp registration using Rapiwa. Batch processing with limits to control workload (recommended max per run configurable). Short delay between items to reduce throttling and temporary blocks. Automatic sheet updates for auditability (verified/unverified, sent/not sent). Defaults recommended in this workflow Trigger interval: every 5–10 minutes (adjustable). Max items per run: configurable (example: 200 max per cycle). Delay between items: 2–5 seconds (example uses 3 seconds). How to set up Duplicate the sample Google Sheet: ➤ Sample Fill contact rows and set Status = pending. Include columns like WhatsApp No, Name, Message, Verification, Status. In n8n, add and authenticate a Google Sheets node pointed to your sheet. Create an HTTP Bearer credential in n8n and paste your Rapiwa API key. Configure the workflow nodes (Trigger → Google Sheets → Limit/SplitInBatches → Code (clean) → HTTP Request (verify) → If → Update Sheet → Wait). Enable the workflow and monitor first runs with a small test batch. Requirements n8n instance with Google Sheets and HTTP Request nodes enabled. Google Sheets OAuth2 credentials configured in n8n. Rapiwa account and Bearer token (stored in n8n credentials). Google Sheet formatted to match the workflow columns. Why use Rapiwa Cost-effective and developer-friendly REST API for WhatsApp verification and sending. Simple integration via HTTP requests and n8n. Useful when you prefer not to use the official WhatsApp Business API. Note: Rapiwa is an unofficial service — review its terms and risks before production use. How to customize Change schedule frequency in the Trigger node. Adjust maxItems in Limit/SplitInBatches for throughput control. Change the Wait node delay for safer sending. Modify the HTTP Request body to support media or templates if the provider supports it. Add logging or a separate audit sheet to record API responses and errors. Best practices Test with a small batch first. Keep the sheet headers exact and consistent. Store API keys in n8n credentials (do not hardcode). Increase Wait time or reduce batch size if you see rate limits. Keep a log sheet of verified/unverified rows for troubleshooting. Example HTTP verify body (n8n HTTP Request node) { "number": "{{ $json['WhatsApp No'] }}" } Notes and best practices Test with a small batch before scaling. Store the Rapiwa token in n8n credentials, not in node fields. Increase Wait delay or reduce batch size if you see rate limits or temporary blocks. Keep the sheet headers consistent; the workflow matches columns by name. Log API responses or errors for troubleshooting. Optional Add a send-message HTTP Request node after verification to send messages. Append successful and failed rows to separate sheets for easy review. Support & Community Need help setting up or customizing the workflow? Reach out here: WhatsApp: Chat with Support Discord: Join SpaGreen Server Facebook Group: SpaGreen Community Website: SpaGreen Creative Envato: SpaGreen Portfolio

What this workflow is (About) This workflow turns a Telegram bot into an AI-powered lyrics assistant. Users send a command plus a lyrics URL, and the flow downloads, cleans, and analyzes the text, then replies on Telegram with translated lyrics, summaries, vocabulary, poetic devices, or an interpretation—all generated by AI (OpenAI). What problems it solves Centralizes lyrics retrieval + cleanup + AI analysis in one automated flow Produces study-ready outputs (translation, vocabulary, figures of speech) Saves time for teachers, learners, and music enthusiasts with instant results in chat Key features AI analysis** using OpenAI (no secrets hardcoded; uses n8n Credentials) Line-by-line translation, **concise summaries, vocabulary lists Poetic/literary device detection* and *emotional/symbolic interpretation** Robust ETL (extract, download, sanitize) and error handling Clear Sticky Notes documenting routing, ETL, AI prompts, and messaging Who it’s for Language learners & teachers Musicians, lyricists, and music bloggers Anyone studying lyrics for meaning, style, or vocabulary Input & output Input:* Telegram command with a public *lyrics URL** Output:** Telegram messages (Markdown/MarkdownV2), split into chunks if long How it works Telegram → Webhook** receives a user message (e.g., /get_lyrics <URL>). Routing (If/Switch)** detects which command was sent. Extract URL + Download (HTTP Request)** fetches the lyrics page. Cleanup (Code)** strips HTML/scripts/styles and normalizes whitespace. OpenAI (Chat)** formats the result per command (translation, summary, vocabulary, analysis). Telegram (Send Message)** returns the final text; long outputs are split into chunks. Error handling** replies with friendly guidance for unsupported/incomplete commands. Set up steps Create a Telegram bot with @BotFather and copy the bot token. In n8n, create Credentials → Telegram API and paste your token (no hardcoded keys in nodes). Create Credentials → OpenAI and paste your API key. Import the workflow and set a short webhook path (e.g., /lyrics-bot). Publish the webhook and set it on Telegram: https://api.telegram.org/bot<YOUR_BOT_TOKEN>/setWebhook?url=https://[YOUR_DOMAIN]/webhook/lyrics-bot (Optional) Restrict update types: curl -X POST https://api.telegram.org/bot<YOUR_BOT_TOKEN>/setWebhook \ -H "Content-Type: application/json" \ -d '{ "url": "https://[YOUR_DOMAIN]/webhook/lyrics-bot", "allowed_updates": ["message"] }' Test by sending /start and then /get_lyrics <PUBLIC_URL> to your bot. If messages are long, ensure MarkdownV2 is used and special characters are escaped.

Description An intelligent AI-powered workflow that automates HR document creation for new hires. Upload candidate documents via form, and the system extracts details, auto-calculates joining dates, fills professional templates using GPT-4, and saves the final Offer Letter or Employment Contract directly to Google Docs—all in seconds. What this workflow does This automation handles your complete HR onboarding document pipeline: Form-based submission:** HR fills a simple form with candidate's Identity card, Resume, Job Role, Salary, and document type selection Smart data extraction:** Automatically extracts candidate name from uploaded Resume PDF and calculates joining date (1st of next month) Template selection:** Routes to Offer Letter or Employment Contract template based on HR's selection AI-powered filling:** Uses OpenAI GPT-4.1-mini to intelligently fill all placeholders while preserving exact formatting, line breaks, and emojis Google Docs output:** Saves the final professional document directly to Google Docs, ready to send to the candidate Setup requirements Tools you'll need: Active n8n instance (self-hosted or n8n Cloud) Google Docs with OAuth access OpenAI API key (GPT-4.1-mini access) PDF documents: Candidate's Identity card and Resume Estimated setup time: 15–20 minutes Step-by-step setup 1. Connect Google Docs In n8n: Credentials → Add credential → Google Docs OAuth2 API Complete OAuth authentication Open "Save Document to Google Docs" node Create a new Google Doc or use an existing template document Copy the document URL and paste it in the documentURL field 2. Add OpenAI API credentials Get API key: https://platform.openai.com/api-keys In n8n: Credentials → Add credential → OpenAI API Paste your API key Open "OpenAI GPT-4.1 Mini Model" node Select your OpenAI credential Ensure model is set to gpt-4.1-mini 3. Customize document templates The workflow includes two pre-built templates. You can customize them: Offer Letter Template: Open "Load Offer Letter Template" node Edit the template_offer value Available placeholders: [Candidate Name], [Job Role], [Department/Team Name], [Company Name], [Joining Date], [Salary Details], [Work Location], [Reporting Manager/Team Lead], [Probation Period] Employment Contract Template: Open "Load Contract Template" node Edit the template_contract value Uses the same placeholders with additional terms and conditions sections Important: Keep all placeholders in square brackets [Placeholder Name] exactly as shown. The AI will replace them automatically. 4. Configure form fields (optional) Open "Receive Candidate Details via Form" node Default fields: Identity card (file), Resume (file), Job Role (text), Salary Details (number), Type (dropdown) Add optional fields if needed: Department Name, Work Location, Reporting Manager, Probation Period Copy the Form URL from the node settings Share this URL with your HR team 5. Test the workflow Open the Form URL in your browser Upload sample Identity card and Resume PDFs Fill Job Role: "Software Developer" Enter Salary Details: 50000 Select Type: "Offer Letter" Submit the form Check your Google Docs—the filled document should appear automatically Verify all placeholders are replaced correctly 6. Activate the workflow Toggle the workflow to Active at the top The form will now accept submissions 24/7 Each submission generates a new document in Google Docs How it works 1. Form submission HR opens the form link and uploads candidate documents (Identity card + Resume as PDFs), enters job details, and selects document type (Offer Letter or Contract). 2. Document processing The workflow splits uploaded files into separate items and auto-generates two dates: Form Date:** Current submission date Joining Date:** Automatically set to the 1st of next month 3. Text extraction Extracts text from both PDF documents using n8n's built-in Extract From File node. The candidate's name is typically pulled from the Resume. 4. Data aggregation Combines extracted text from both documents into a single data item for processing. 5. Template routing Checks the selected document type: If "Offer Letter" → loads the Offer Letter template If "Contract" → loads the Employment Contract template 6. AI template filling The AI Agent receives: The selected template with placeholders All form data (Job Role, Salary, etc.) Extracted candidate name from Resume Auto-calculated joining date GPT-4.1-mini fills every placeholder with actual data while strictly preserving: Line breaks and paragraph spacing Emojis and special characters Bold/italic formatting markers Email, phone, and web links 7. Google Docs save The final filled document is inserted into your Google Docs document. Each submission appends a new document, so you can maintain a running archive or clear the doc periodically. Key features ✅ Zero manual typing: Extract candidate name automatically from Resume PDF—no copy-paste needed ✅ Smart date calculation: Joining date auto-set to 1st of next month based on submission date ✅ Dual document types: Choose between simple Offer Letter or detailed Employment Contract with terms ✅ AI preserves formatting: GPT-4.1-mini maintains exact line breaks, emojis, and structure from templates ✅ Google Docs integration: Documents saved directly—no downloads, conversions, or file juggling ✅ Customizable templates: Edit both templates to match your company's tone, policies, and branding ✅ Form-based workflow: Share one URL with HR team—no n8n access needed for daily use Troubleshooting Google Docs not saving Re-authenticate OAuth credentials:** Go to Credentials → Google Docs OAuth2 API → Reconnect Check document URL:** Ensure the documentURL field contains a valid Google Docs link (not a Sheets link) Verify permissions:** Make sure the connected Google account has edit access to the document Candidate name not extracting correctly Resume format issue:** The workflow expects candidate name in the Resume PDF text. If your Resume format is unusual, you may need to adjust the extraction logic. Check extraction node:** Open "Extract Text from Identity card and Resume" node → Test execution → Verify text output Manual override:** Add a "Candidate Name" field to the form if automatic extraction fails AI not filling placeholders Check API key:** Verify OpenAI API key is active and has credits at https://platform.openai.com/usage Placeholder mismatch:** Ensure template placeholders exactly match the format [Placeholder Name] with square brackets Test AI node:** Click "Fill Template with AI" → Execute node → Check output for errors Joining date incorrect Timezone issue:** The date calculation uses server timezone. Verify your n8n instance timezone settings. Custom date needed:** If you want a different joining date logic (e.g., 15 days from submission), edit the "Split Documents and Calculate Dates" code node. Form not accepting file uploads File size limit:** Default n8n form limit is 16MB. Compress PDFs if larger. File type validation:** Ensure uploaded files are PDFs, not images or other formats. Browser issue:** Try a different browser (Chrome recommended for file uploads). Use cases HR teams at growing companies: Onboard 5-10 new hires per week without spending hours on document preparation. Generate consistent, professional documents in seconds. Recruitment agencies: Send offer letters to multiple candidates daily. Maintain brand consistency while scaling operations without adding admin staff. Startups and small businesses: Automate HR paperwork from day one. Focus on candidate experience instead of document formatting. Remote-first companies: Enable distributed HR teams to generate documents without shared drives or email chains. Single form link, instant output. Consulting firms: Create client-specific employment contracts with custom templates. Switch between contract types based on project requirements. Expected results Time savings:** 15-20 minutes saved per document (from 20 min manual → 2 min automated) Output quality:** Professional, error-free documents with consistent formatting every time Scalability:** Process 50+ candidates per week without additional HR headcount Error reduction:** Eliminate typos and placeholder mistakes common in manual copy-paste workflows Faster hiring:** Send offer letters within 5 minutes of candidate approval Workflow customization Add more form fields Open "Receive Candidate Details via Form" node and add custom fields: Department Name (dropdown with your teams) Work Location (dropdown: Remote, Office, Hybrid) Reporting Manager (text input) Probation Period (number input) Start Date (date picker for custom joining dates) These values automatically populate in templates if placeholders are added. Create additional templates Duplicate one of the "Load Template" nodes and create: Internship Offer Letters Part-time Contract Freelancer Agreement Probation Extension Letter Add a corresponding option in the form Type dropdown. Send documents via email Add an Email node after "Save Document to Google Docs": Attach the Google Docs link Send to candidate email (add email field to form) CC HR manager automatically Multi-language support Create template variations in different languages. Add a "Language" dropdown to the form and route to appropriate template. Support Need help or custom development? 📧 Email: info@isawow.com 🌐 Website: https://isawow.com/

Who this is for This workflow is for content creators, digital marketers, or YouTube strategists who want to automatically discover trending videos in their niche, analyze engagement metrics, and get data-driven insights for their content strategy — all from one simple form submission. What this workflow does This workflow starts every time someone submits the YouTube Trends Finder Form. It then: Searches YouTube videos* based on your topic and specified time range using the *YouTube Data API**. Fetches detailed analytics** (views, likes, comments, engagement rates) for each video found. Calculates engagement rates** and filters out low-performing content (below 2% engagement). Applies smart filters** to exclude videos with less than 1000 views, content outside your timeframe, and hashtag-heavy titles. Removes duplicate videos** to ensure clean data. Creates a Google Spreadsheet** with all trending video data organized by performance metrics. Delivers the results** via a completion form with a direct link to your analytics report. Setup To set this workflow up: Form Trigger – Customize the "YouTube Trends Finder" form fields if needed (Topic Name, Last How Many Days). YouTube Data API – Add your YouTube OAuth2 credentials and API key in the respective nodes. Google Sheets – Connect your Google Sheets account for automatic report generation. Engagement Filters – Adjust the 2% engagement rate threshold based on your quality standards. View Filters – Modify the minimum view count (currently 1000+) in the filter conditions. Regional Settings – Update the region code (currently "US") to target specific geographic markets. How to customize this workflow to your needs Change the engagement rate threshold to be more or less strict based on your niche requirements. Add additional filters like video duration, subscriber count, or specific keywords to refine results. Modify the Google Sheets structure to include extra metrics like "Channel Name", "Video Duration", or "Trending Score". Switch to different output formats like CSV export or direct email reports instead of Google Sheets.

🧠 Workflow Overview — AI-Powered Jobs Scraper & Relevancy Evaluator This workflow automates the process of finding highly relevant job listings based on a user’s resume, career preferences, and custom filters. It scrapes fresh job data, evaluates relevance using OpenAI GPT models, and automatically appends the results to your Google Sheet tracker — while skipping any jobs already in your sheet, so you don’t have to worry about duplicates. Perfect for recruiters, job seekers, or virtual assistants who want to automate job research and filtering. ⚙️ What the Workflow Does Takes user input through a form — including resume, preferences, target score, and Google Sheet link. Fetches job listings via an Apify LinkedIn Jobs API actor. Filters and deduplicates results (removes duplicates and blacklisted companies). Evaluates job relevancy using GPT-4o-mini, scoring each job (0–100) against the user’s resume & preferences. Applies a relevancy threshold to keep only top-matching jobs. Checks your Google Sheet for existing jobs and prevents duplicates. Appends new, relevant jobs directly into your provided Google Sheet. 📋 What You’ll Get A personal Job Scraper Form (public URL you can share or embed). Automatic job collection & filtering based on your inputs. Relevance scoring** (0–100) for each job using your resume and preferences. Real-time job tracking Google Sheet that includes: Job Title Company Name & Profile Job URLs Location, Salary, HR Contact (if available) Relevancy Score 🪄 Setup Instructions 1. Required Accounts You’ll need: ✅ n8n account (self-hosted or Cloud) ✅ Google account (for Sheets integration) ✅ OpenAI account (for GPT API access) ✅ Apify account (to fetch job data) 2. Connect Credentials In your n8n instance: Go to Credentials → Add New: Google Sheets OAuth2 API Connect your Google account. OpenAI API Add your OpenAI API key. Apify API Replace <your_apify_api> with your apify api key. Set Up Apify API Get your Apify API key Visit: https://console.apify.com/settings/integrations Copy your API key. Rent the required Apify actor before running this workflow Go to: https://console.apify.com/actors/BHzefUZlZRKWxkTck/input Click “Rent Actor”. Once rented, it can be used by your Apify account to fetch job listings. 3. Set Up Your Google Sheet Make a copy of this template: 📄 Google Sheet Template Enable Edit Access for anyone with the link. Copy your sheet’s URL — you’ll provide this when submitting the workflow form. 4. Deploy & Run Import this workflow (jobs_scraper.json) into your n8n workspace. Activate the workflow. Visit your form trigger endpoint (e.g. https://your-n8n-domain/webhook/jobs-scraper). Fill out the form with: Job title(s) Location Contract type, Experience level, Working mode, Date posted Target relevancy score Google Sheet link Resume text Job preferences or ranking criteria Submit — within minutes, new high-relevance job listings will appear in your Google Sheet automatically. 🧩 Example Use Cases Automate daily job scraping for clients or yourself. Filter jobs by AI-based relevance instead of keywords. Build a smart job board or job alert system. Support a career agency offering done-for-you job search services. 💡 Tips Adjust the “Target Relevancy Score” (e.g., 70–85) to control how strict the filtering is. You can add your own blacklisted companies in the Filter & Dedup Jobs node.

Try It Out! The AI Investment Research Assistant (Discord Summary Bot) transforms your Discord server into a professional-grade AI-driven crypto intelligence center. Running automatically every morning, it gathers real-time news, sentiment, and market data from multiple trusted sources — including NewsAPI, Crypto Compare, and CoinGecko — covering the most influential digital assets like BTC, ETH, SOL, BNB, and ADA. An AI Research Analyst Agent then processes this data using advanced reasoning and summarization to deliver a structured Market Intelligence Briefing. Each report distills key market events, sentiment shifts, price movements, and analyst-grade insights, all formatted into a visually clean and actionable message that posts directly to your Discord channel. Whether you’re a fund manager, community owner, or analyst, this workflow helps you stay informed about market drivers — without manually browsing dozens of news sites or data dashboards. Detailed Use Cases Crypto Research Teams:** Automate daily market briefings across key assets. Investment Communities:** Provide daily insights and sentiment overviews directly on Discord. Trading Desks:** Quickly review summarized market shifts and performance leaders. DAOs or Fund Analysts:** Centralize institutional-style crypto intelligence into your server. How It Works Daily Trigger (Schedule Node) – Activates each morning to begin data collection. News Aggregation Layer – Uses NewsAPI (and optionally CryptoPanic or GDELT) to fetch the latest crypto headlines and event coverage. Market & Sentiment Fetch – Collects market metrics via CoinGecko or Crypto Compare, including: 24-hour price change Market cap trend Social sentiment or Fear & Greed index AI Research Analyst (LLM Agent) – Processes and synthesizes all data into a cohesive insight report containing: 🧠 Executive Summary 📊 Top Gainers & Losers 💬 Sentiment Overview 🔍 Analyst Take / Actionable Insight Formatting Layer (Code Node) – Converts the analysis into a Discord-ready structure. Discord Posting Node – Publishes the final Market Intelligence Briefing to a specified Discord channel. Setup and Customization Import this workflow into your n8n workspace. Configure credentials: NewsAPI Key – For crypto and blockchain news. CoinGecko / Crypto Compare API Key – For real-time asset data. LLM Credential – OpenAI, Gemini, or Anthropic. Discord Webhook URL or Bot Token – To post updates. Customize the tracked assets in the News and Market nodes (BTC, ETH, SOL, BNB, ADA, etc.). Set local timezone for report delivery. Deploy and activate — your server will receive automated morning briefings. Output Format Each daily report includes: 📰 AI Market Intelligence Briefing 📅 Date: October 16, 2025 💰 Top Movers: BTC +2.3%, SOL +1.9%, ETH -0.8% 💬 Sentiment: Moderately Bullish 🔍 Analyst Take: Accumulation signals forming in mid-cap layer-1s. 📈 Outlook: Positive bias, with ETH showing strong support near $2,400. Compact yet rich in insight, this format ensures quick readability and fast decision-making for traders and investors. (Optional) Extend This Workflow Portfolio-Specific Insights:** Fetch your wallet holdings from AFK Crypto or Zapper APIs for personalized reports. Interactive Commands:** Add /compare or /analyze commands for Discord users. Multi-Language Summaries:** Auto-translate for international communities. Historical Data Logging:** Store briefings in Notion or Google Sheets. Weekly Recaps:** Summarize all daily reports into a long-form analysis. Requirements n8n Instance** (with HTTP Request, AI Agent, and Discord nodes enabled) NewsAPI Key** CoinGecko / Crypto Compare API Key** LLM Credential** (OpenAI / Gemini / Anthropic) Discord Bot Token or Webhook URL** APIs Used GET https://newsapi.org/v2/everything?q=crypto OR bitcoin OR ethereum OR defi OR nft&language=en&sortBy=publishedAt&pageSize=10 GET https://api.coingecko.com/api/v3/simple/price?ids=bitcoin,ethereum,solana&vs_currencies=usd&include_market_cap=true&include_24hr_change=true (Optional) GET https://cryptopanic.com/api/v1/posts/?auth_token=YOUR_TOKEN&kind=news (Optional) GET https://api.gdeltproject.org/api/v2/doc/doc?query=crypto&format=json Summary The AI Investment Research Assistant (Discord Summary Bot) is your personal AI research analyst — delivering concise, data-backed crypto briefings directly to Discord. It intelligently combines news aggregation, sentiment analysis, and AI reasoning to create actionable market intelligence each morning. Ideal for crypto traders, funds, or educational communities seeking a reliable daily edge — this workflow replaces hours of manual research with one automated, professional-grade summary. Our Website: https://afkcrypto.com/ Check our blogs: https://www.afkcrypto.com/blog

🧠 Google Ads Monthly Performance Optimization (Channable + Google Ads + Relevance AI) 🚀 Overview This workflow automatically analyzes your Google Ads performance every month, identifies top-performing themes and categories, and regenerates optimized ad copy using Relevance AI — powered by insights from your Channable product feed. It then saves the improved ads to Google Sheets for review and sends a detailed performance report to your Slack workspace. Ideal for marketing teams who want to automate ad optimization at scale with zero manual intervention. 🔗 Integrations Used Google Ads** → Fetch campaign and ad performance metrics using GAQL. Relevance AI** → Analyze performance data and regenerate ad copy using AI agents and tools. Channable** → Pull updated product feeds for ad refresh cycles. Google Sheets** → Save optimized ad copy for review and documentation. Slack** → Send a 30-day performance report to your marketing team. 🧩 Workflow Summary | Step | Node | Description | | ---- | --------------------------------------------------- | --------------------------------------------------------------------------- | | 1 | Monthly Schedule Trigger | Runs automatically on the 1st of each month to review last 30 days of data. | | 2 | Get Google Ads Performance Data | Fetches ad metrics via GAQL query (impressions, clicks, CTR, etc.). | | 3 | Calculate Performance Metrics | Groups results by ad group and theme to find top/bottom performers. | | 4 | AI Performance Analysis (Relevance AI) | Generates human-readable insights and improvement suggestions. | | 5 | Update Knowledge Base (Relevance AI) | Saves new insights for future ad copy training. | | 6 | Get Updated Product Feed (Channable) | Retrieves the latest catalog items for ad regeneration. | | 7 | Split Into Batches | Splits the feed into groups of 50 to avoid API rate limits. | | 8 | Regenerate Ad Copy with Insights (Relevance AI) | Rewrites ad copy with the latest product and performance data. | | 9 | Save Optimized Ads to Sheets | Writes output to your “Optimized Ads” Google Sheet. | | 10 | Generate Performance Report | Summarizes the AI analysis, CTR trends, and key insights. | | 11 | Email Performance Report (Slack) | Sends report directly to your Slack channel/team. | 🧰 Requirements Before running the workflow, make sure you have: A Google Ads account with API access and OAuth2 credentials. A Relevance AI project (with one Agent and one Tool setup). A Channable account with API key and project feed. A Google Sheets document for saving results. A Slack webhook URL for sending performance summaries. ⚙️ Environment Variables Add these environment variables to your n8n instance (via .env or UI): | Variable | Description | | -------------------------------- | ------------------------------------------------------------------- | | GOOGLE_ADS_API_VERSION | API version (e.g., v17). | | GOOGLE_ADS_CUSTOMER_ID | Your Google Ads customer ID. | | RELEVANCE_AI_API_URL | Base Relevance AI API URL (e.g., https://api.relevanceai.com/v1). | | RELEVANCE_AGENT_PERFORMANCE_ID | ID of your Relevance AI Agent for performance analysis. | | RELEVANCE_KNOWLEDGE_SOURCE_ID | Knowledge base or dataset ID used to store insights. | | RELEVANCE_TOOL_AD_COPY_ID | Relevance AI tool ID for generating ad copy. | | CHANNABLE_API_URL | Channable API endpoint (e.g., https://api.channable.com/v1). | | CHANNABLE_COMPANY_ID | Your Channable company ID. | | CHANNABLE_PROJECT_ID | Your Channable project ID. | | FEED_ID | The feed ID for product data. | | GOOGLE_SHEET_ID | ID of your Google Sheet to store optimized ads. | | SLACK_WEBHOOK_URL | Slack Incoming Webhook URL for sending reports. | 🔐 Credentials Setup in n8n | Credential | Type | Usage | | ----------------------------------------------- | ------- | --------------------------------------------------- | | Google Ads OAuth2 API | OAuth2 | Authenticates your Ads API queries. | | HTTP Header Auth (Relevance AI & Channable) | Header | Uses your API key as Authorization: Bearer <key>. | | Google Sheets OAuth2 API | OAuth2 | Writes optimized ads to Sheets. | | Slack Webhook | Webhook | Sends monthly reports to your team channel. | 🧠 Example AI Insight Output { "insights": [ "Ad groups using 'vegan' and 'organic' messaging achieved +23% CTR.", "'Budget' keyword ads underperformed (-15% CTR).", "Campaigns featuring 'new' or 'bestseller' tags showed higher conversion rates." ], "recommendations": [ "Increase ad spend for top-performing 'vegan' and 'premium' categories.", "Revise copy for 'budget' and 'sale' ads with low CTR." ] } 📊 Output Example (Google Sheet) | Product | Category | Old Headline | New Headline | CTR Change | Theme | | ------------------- | -------- | ------------------------ | -------------------------------------------- | ---------- | ------- | | Organic Protein Bar | Snacks | “Healthy Energy Anytime” | “Organic Protein Bar — 100% Natural Fuel” | +12% | Organic | | Eco Face Cream | Skincare | “Gentle Hydration” | “Vegan Face Cream — Clean, Natural Moisture” | +17% | Vegan | 📤 Automation Flow Run Automatically on the first of every month (cron: 0 0 1 * *). Fetch Ads Data → Analyze & Learn → Generate New Ads → Save & Notify. Every iteration updates the AI’s knowledge base — improving your campaigns progressively. ⚡ Scalability The flow is batch-optimized (50 items per request). Works for large ad accounts with up to 10,000 ad records. AI analysis & regeneration steps are asynchronous-safe (timeouts extended). Perfect for agencies managing multiple ad accounts — simply duplicate and update the environment variables per client. 🧩 Best Use Cases Monthly ad creative optimization for eCommerce stores. Marketing automation for Google Ads campaign scaling. Continuous learning ad systems powered by Relevance AI insights. Agencies automating ad copy refresh cycles across clients. 💬 Slack Report Example 30-Day Performance Optimization Report Date: 2025-10-01 Analysis Period: Last 30 days Ads Analyzed: 842 Top Performing Themes Vegan: 5.2% CTR (34 ads) Premium: 4.9% CTR (28 ads) Underperforming Themes Budget: 1.8% CTR (12 ads) AI Insights “Vegan” and “Premium” themes outperform baseline by +22% CTR. “Budget” ads underperform due to lack of value framing. Next Optimization Cycle: 2025-11-01 🛠️ Maintenance Tips Update your GAQL query occasionally to include new metrics or segments. Refresh Relevance AI tokens every 90 days (if required). Review generated ads in Google Sheets before pushing them live. Test webhook and OAuth connections after major n8n updates. 🧩 Import Instructions Open n8n → Workflows → Import from File / JSON. Paste this workflow JSON or upload it. Add all required environment variables and credentials. Execute the first run manually to validate connections. Once verified, enable scheduling for automatic monthly runs. 🧾 Credits Developed for AI-driven marketing teams leveraging Google Ads, Channable, and Relevance AI to achieve continuous ad improvement — fully automated via n8n.