Workflow Templates

🚀 Automated LinkedIn Post Generator from Article Links (Telegram → AI → Google Sheets → LinkedIn) This workflow lets you collect article links through a Telegram bot, automatically analyze and summarize them with AI, store everything neatly in Google Sheets, and generate polished LinkedIn posts on demand whenever the user types “generate”. Perfect for creators, marketers, and founders who want to post consistently without spending hours analyzing articles or writing drafts. 🧠 How It Works 1️⃣ User Sends Articles via Telegram Your Telegram bot is the main input point. Whenever the user drops a link, the workflow: Detects the URL Fetches the content Sends it to AI for analysis This keeps the process simple. 2️⃣ AI Analyzes & Summarizes the Article The workflow uses your LLM (OpenAI, Anthropic, etc.) to: Summarize the article Extract key insights Identify main arguments Capture tone and context It produces a clean, structured dataset for each link. 3️⃣ Everything is Saved into Google Sheets Each article becomes a new row in your Google Sheet. The sheet serves as your content library with fields like: Date Title Link Summary Insights Commentary You can save dozens of articles and generate posts from any of them later. 4️⃣ User Requests a Post with “generate” When the user types “generate”, the workflow will: Pull the latest article(s) from Google Sheets (or any selection logic you choose) Build a LinkedIn-ready post using AI Apply the requested tone/style Format it as a clean, professional post The final post is sent right back to Telegram — ready to copy/paste into LinkedIn. 🛠️ Setup Steps 🔧 1. Create a Telegram Bot Go to @BotFather on Telegram Create a new bot Copy the API token Paste the token into the Telegram Trigger node in n8n 🔧 2. Add Your AI Credentials Go to Credentials → OpenAI (or your provider) Add your API key Select this credential in all AI nodes You can switch to GPT-4o, GPT-4o-mini, or any model you prefer. 🔧 3. Connect Google Sheets Go to Credentials → Google Authenticate with your Google account Make sure the sheet contains the required columns: Date Title Link Summary Insights Commentary You can customize or add additional columns as needed. 🔧 4. Adjust Workflow Logic (Optional) You can modify: How the AI summarizes The LinkedIn post style How posts are selected (latest, random, specific tone, etc.) Whether you store more metadata Multi-language support Everything is modular. 🔧 5. Test the Flow Send yourself a link via the Telegram bot Check that it appears in Google Sheets Type “generate” Receive your LinkedIn post instantly 🎉 You’re Ready! This workflow helps you build a personal content pipeline that: Collects links Saves ideas Summarizes insights Generates LinkedIn posts on demand All directly from your phone, inside Telegram. If you remix or extend this template, I’d love to see what you build!

About This Template Turn every sales meeting into a coaching opportunity. This workflow automatically analyzes tldv meeting recordings using OpenAI (GPT-4) to provide instant, actionable feedback to your sales team. It acts as a virtual sales coach, evaluating key performance metrics like listening skills, question quality, and customer engagement without requiring a manager to listen to every call. How It Works Trigger: The workflow starts automatically when a meeting transcript is ready in tldv (via Webhook). Data Retrieval: It fetches the full meeting details and transcript from the tldv API. AI Analysis: GPT-4 analyzes the conversation to score the sales rep's performance (e.g., Speaking vs. Listening balance, Clarity, Next Steps). Delivery: Slack: Sends a summary notification and a detailed markdown report to the team channel. Google Sheets: Archives the scores and meeting data for long-term tracking. Who It’s For Sales Managers:** To monitor team performance and identify coaching needs at scale. Account Executives:** To get immediate feedback on their calls and self-correct. Sales Enablement:** To track KPI trends over time. Requirements n8n** (Cloud or Self-hosted) tldv (Business Plan)** for API/Webhook access OpenAI API Key** (GPT-4 access recommended) Slack** Workspace Google Sheets** Setup Steps Credentials: Configure "Header Auth" for tldv (x-api-key) and OpenAI (Authorization). Connect OAuth for Slack and Google Sheets. Webhook: Copy the Production URL from the first node (Webhook) and add it to your tldv Settings > Integrations > Webhooks (select Event: TranscriptReady). Google Sheets: Create a sheet (e.g., named Sales Feedback) with columns for Meeting Name, Score, Summary, etc. Note: Be sure to update the Google Sheets node in the workflow to match your specific Sheet Name and Column headers.

Description Automate your financial reporting by pulling charge and refund data from Stripe, calculating key revenue and risk metrics, and delivering professional reports directly into Slack. This workflow runs on a monthly or quarterly schedule, processes Stripe data into insights, and formats a rich Slack message with revenue breakdowns, top customers, refund analysis, and payment method insights. 📊💰💬 What This Template Does Runs automatically on a monthly (1st day) or quarterly schedule (every 3 months) at 9 AM. ⏱️ Fetches Stripe charges and refunds for the reporting period. 💳 Merges charge and refund data for a unified dataset. 🔄 Calculates financial metrics: total revenue, net revenue, average transaction value, refund rate. 📈 Estimates growth metrics: Monthly Recurring Revenue (MRR) and Annual Recurring Revenue (ARR). 🚀 Identifies top 3 customers by revenue. 🏆 Breaks down payment methods used (e.g., Visa, Mastercard, etc.). 💳 Performs risk analysis on transactions by Stripe’s risk scores. ⚠️ Analyzes refund reasons and generates insights. 🔄 Formats all results into a clear, structured Slack message with sections for finance, growth, risk, and customers. 💬 Key Benefits Eliminates manual Stripe report exports. ⚡ Ensures timely financial reporting (monthly or quarterly). 📅 Provides instant visibility of revenue, refunds, and risks in Slack. 📲 Surfaces top customers and payment methods for strategic insights. 🏅 Helps finance and ops teams catch anomalies early (high refunds or risky transactions). 🛡️ Keeps leadership and teams aligned with automated reporting. 👩‍💻👨‍💻 Features Schedule Triggers – Automates reporting on monthly or quarterly cycles. Stripe Charges & Refunds – Pulls transaction and refund data directly from Stripe API. Merge Node – Combines charges and refunds into a single dataset. Custom Code Metrics – Calculates revenue, net revenue, refund rates, and growth metrics. Top Customer Analysis – Highlights top revenue-generating customers. Payment Breakdown – Shows revenue split by card brand/payment method. Refund Analysis – Summarizes refund reasons and rates. Risk Analysis – Categorizes payments by low, medium, or high risk scores. Slack Integration – Delivers insights in a professional report format. Requirements n8n instance (cloud or self-hosted). Stripe API credentials with read access to charges and refunds. Slack Bot token with chat:write permission. Target Audience Finance teams needing automated recurring Stripe reports. 💼 SaaS companies monitoring MRR, ARR, and refunds. 🚀 Founders/Execs who want financial dashboards in Slack. 👩‍💼 Operations teams tracking risk and refund trends. 🛠️ Remote teams relying on Slack for reporting. 🌍 Step-by-Step Setup Instructions Connect your Stripe API credentials in n8n. 🔑 Connect your Slack API credentials and select your target channel. 💬 Adjust the schedule triggers (monthly/quarterly) if needed. ⏱️ Customize the Slack message formatting if you want branding or tone changes. 🎨 Test the workflow with sample data to confirm financial metrics. ✅

This n8n template demonstrates how to automatically generate and publish SEO/AEO-optimized Shopify blog articles from a list of keywords using AI for content creation, image generation, and metadata optimization. Who’s it for Shopify marketers, content teams, and solo founders who want consistent, hands-off blog production with built-in SEO/AEO hygiene and internal linking. What it does The workflow picks a keyword from your Google Sheet based on priority, search volume, and difficulty. It then checks your Shopify blog for existing slugs to avoid duplicate, drafts a 900+ word article optimized for SEO/AEO, generates a hero image, creates the article in Shopify, sets SEO metafields (title/description), and logs the result to your Sheets for tracking and future internal links. How it works Google Sheets → Candidate selection:* Reads *Keywords, **Links, and Published tabs: ranks by priority → volume → difficulty. (In the workflow it is explained how to exactly set up the Google Sheets) De-dupe slugs:** Paginates your blog via Shopify GraphQL to collect existing handles and make sure to use a different one. OpenAI content + image:** Builds a structured prompt (SEO/AEO and internal linking), calls Chat Completions and Image Generation for a hero image. Shopify publish:** Creates the article via REST and updates title_tag / description_tag metafields via GraphQL. Log + link graph:* Appends to *Published* tab to keep track of articles posted and *Links** tab for ongoing internal-link suggestions. How to set up Open Set – Config and fill: shopDomain, siteBaseUrl, blogId, blogHandle, sheetId, author. Optional: autoPublish, maxPerRun, tz. Create the Google Sheet with Keywords, Links, Published tabs using the provided column structure. I have personally used Semrush to generate that list of keywords. Add credentials: Shopify Admin token (Header/Bearer), OpenAI API key, and Google Service Account. Requirements Shopify store with Blog API access OpenAI API key Google Service Account with access to Google Sheets API (can be activated here here) How to customize Change the cron in Schedule Trigger for different days/times. Adjust maxPerRun, autoPublish, language or any other variables in the "Set - Config" node. Adjust the prompt from the "Code - Build Prompt" node. Extend the Sheets schema with extra scoring signals if needed.

This workflow fetches deals and their notes from Pipedrive, cleans up stage IDs into names, aggregates the information, and uses OpenAI to generate a daily summary of your funnel. ⚙️ Setup Instructions 1️⃣ Set Up OpenAI Connection Go to OpenAI Platform Navigate to OpenAI Billing Add funds to your billing account Copy your API key into the OpenAI credentials in n8n 2️⃣ Connect Pipedrive In Pipedrive → Personal preferences → API → copy your API token URL shortcut: https://{your-company}.pipedrive.com/settings/personal/api In n8n → Credentials → New → Pipedrive API Company domain: {your-company} (the subdomain in your Pipedrive URL) API Token: paste the token from step 1 → Save In the Pipedrive nodes, select your Pipedrive credential and (optionally) set filters (e.g., owner, label, created time). 🧠 How It Works Trigger**: Workflow runs on manual execution (can be scheduled). Get many deals**: Pulls all deals from your Pipedrive. Code node**: Maps stage_id numbers into friendly stage names (Prospecting, Qualified, Proposal Sent, etc.). Get many notes**: Fetches notes attached to each deal. Combine Notes**: Groups notes by deal, concatenates content, and keeps deal titles. Set Field Names**: Normalizes the fields for summarization. Aggregate for Agent**: Collects data into one object. Turn Objects to Text**: Prepares text data for AI. OpenAI Chat Model + Summarize Agent: Generates a **daily natural-language summary of deals and their current stage. 💬 Example Prompts “Summarize today’s deal activity.” “Which deals are still in negotiation?” “What updates were added to closed-won deals this week?” 📬 Contact Need help extending this (e.g., send summaries by Slack/Email, or auto-create tasks in Pipedrive)? 📧 rbreen@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com

Who’s it for Learners, teachers, and content creators who track German vocabulary in Google Sheets and want automatic enrichment with synonyms, example sentences, and basic lexical info—without copy-and-paste. How it works / What it does When a new row is added to your sheet (column vocabulary), the workflow looks up the word in OpenThesaurus and checks if any entries are found. If so, an LLM generates a strict JSON object containing: natural_sentence (a clear German example), part_of_speech, translation_ja (concise Japanese gloss), and level (CEFR estimate). The JSON is parsed and written back to the same row, keeping your spreadsheet the single source of truth. If no entry is found, the workflow writes a helpful “not found” note. How to set up Connect Google Sheets and select your spreadsheet/tab. Confirm a vocabulary column exists. Configure OpenThesaurus (no API key required). Add your LLM credentials and keep the prompt’s “JSON only” constraint. Rename nodes clearly and add a yellow sticky note with this description. Requirements Access to Google Sheets LLM credentials (e.g., OpenAI) A tab containing a vocabulary column How to customize the workflow Adjust the If condition (e.g., require terms.length > 1 or fall back to the headword). Tweak the LLM prompt for tone, length, or level policy. Map extra fields in the Set node; add columns for difficulty tags or usage notes. Follow security best practices (no hardcoded secrets in HTTP nodes).

Automatically gather hundreds of real customer reviews from five major platforms in one run using Thordata API and Proxy — Trustpilot, Capterra, Chrome Web Store, TrustRadius, and Product Hunt — then let GPT-4.1 perform deep collective sentiment analysis, uncover common praises & complaints, flag critical issues, assess churn risk, and deliver actionable recommendations straight to your inbox as a stunning executive HTML report. Who’s it for Product managers & founders Growth and marketing teams Customer success & support leads Agencies delivering competitor or product review reports How it works Submit product URLs via form, webhook, or use defaults Smart, Cloudflare-safe scraping with automatic pagination Universal parser standardizes every review format Global deduplication using deterministic unique IDs GPT-4.1 analyzes all reviews collectively (not one-by-one) Beautiful responsive HTML email with sentiment badges, stats, and recommendations Requirements Thordata API key (free tier works) → set as HTTP Header Auth credential OpenAI API key Gmail account (or replace with any email node) How to set up Add your Thordata and OpenAI credentials Connect Gmail Click “Execute Workflow” – instantly tests with Thordata’s own reviews How to customize Edit default product in “Prepare Review Sources” node Modify the AI prompt or email design anytime Add more sources or change the output format easily Zero browser automation · Rate-limit safe · Fully deduplicated · Plug-and-play in minutes.

Instagram Hashtag Generator Workflow This workflow automatically generates optimal hashtags for your Instagram posts by analyzing captions and fetching real-time engagement data. Key Features 100% Official API & Free**: Uses ONLY the official Instagram Graph API. No expensive third-party tools or risky scraping methods are required. Safe & Reliable**: Relying on the official API ensures compliance and long-term stability. Smart Caching**: Includes a Google Sheets caching mechanism to maximize the value of the official API's rate limits (30 searches/7 days). Workflow Overview Caption Input: Set your caption manually or via a workflow trigger. AI Suggestions: GPT-4o-mini analyzes the caption and suggests 10 relevant hashtags, balancing popular (big words) and niche keywords. Official API Search (Instagram Graph API): Fetches Hashtag IDs using the ig_hashtag_search endpoint. Retrieves engagement metrics (Average Likes, Average Comments) using the ID. Selection & Sorting: Sorts candidates by engagement metrics. Selects the top 5 most effective hashtags that balance relevance and engagement. Output: Returns the final list of hashtags as text. Setup Steps Import to n8n: Copy the content of workflow_hashtag_generator.json and paste it into your n8n canvas, or import the file directly. Credentials: OpenAI account: Connect your OpenAI credentials. Facebook Graph account: Connect your Facebook Graph API credentials. Configuration: Instagram Business ID: Update the YOUR_INSTAGRAM_BUSINESS_ACCOUNT_ID placeholder in the Get Hashtag Info and Get Hashtag Metrics nodes with your actual Business Account ID. Google Spreadsheet ID: Update the YOUR_SPREADSHEET_ID placeholder in the Fetch Cached Hashtags and Save to Cache nodes. Adjustments: Filter Logic: You can adjust the sorting or filtering logic in the Aggregate & Rank Candidates node's JavaScript code (e.g., exclude tags with fewer than 1000 posts) if needed. Important Notes on API Limits The official Instagram Hashtag Search API (ig_hashtag_search) allows for 30 unique hashtag queries per rolling 7-day period. Why this is fine**: This workflow caches results in Google Sheets. Once a tag is fetched, it doesn't need to be queried again for a while, allowing you to build up a large database of tags over time without hitting the limit. Recommendation**: Use mock data during initial testing to save your API quota.

How it works This workflow captures idea submissions from a webhook and enriches them using AI. It extracts key fields like Title, Tags, Submitted By, and Created date in IST format. The cleaned data is stored in a Notion database for centralized tracking. Finally, a confirmation message is posted in Slack to notify the team. Step-by-step Step-by-step 1. Capture and process submission Webhook** – Receives idea submissions with text and user ID. AI Agent & OpenAI Model** – Enrich and structure the input into Title, Tags, Submitted By, and Created fields. Code** – Extracts clean data, formats tags, and prepares the entry for Notion. 2. Store in Notion Add to Notion** – Creates a new database entry with mapped fields: Title, Submitted By, Tags, Created. 3. Notify in Slack Send Confirmation (Slack)** – Posts a confirmation message with the submitted idea title. Why use this? Centralizes idea collection directly into Notion for better organization. Eliminates manual formatting with AI-powered data structuring. Ensures consistency in tags, submitter info, and timestamps. Provides instant team-wide visibility via Slack notifications. Saves time while keeping idea management streamlined and transparent.

Template Description This description details the template's purpose, how it works, and its key features. You can copy and use it directly. Overview This is a powerful n8n "meta-workflow" that acts as a Supervisor. Through a simple Telegram bot, you can dynamically create, manage, and delete countless independent, AI-driven market monitoring agents (Watchdogs). This template is a perfect implementation of the "Workflowception" (workflow managing workflows) concept in n8n, showcasing how to achieve ultimate automation by leveraging the the n8n API. How It Works ? Telegram Bot Interface: Execute all operations by sending commands to your own Telegram Bot: /add SYMBOL INTERVAL PROMPT: Add a new monitoring task. /delete SYMBOL: Delete an existing monitoring task. /list: List all currently running monitoring tasks. /help: Get help information. Use Telegram Bot to control The watchdog workfolw created in the below Dynamic Workflow Management: Upon receiving an /add command, the Supervisor system reads a "Watchdog" template, fills in your provided parameters (like trading pair and time interval), and then automatically creates a brand new, independent workflow via the n8n API and activates it. Persistent Storage: All monitoring tasks are stored in a PostgreSQL database, ensuring your configurations are safe even if n8n restarts. The ID of each newly created workflow is also written back to the database to facilitate future deletion operations. AI-Powered Analysis: Each created "Watchdog" workflow runs on schedule. It fetches the latest candlestick chart by calling a self-hosted tradingview-snapshot service. This service, available at https://github.com/0xcathiefish/tradingview-snapshot, works by simulating a login to your account and then using TradingView's official snapshot feature to generate an unrestricted, high-quality chart image. An example of a generated snapshot can be seen here: https://s3.tradingview.com/snapshots/u/uvxylM1Z.png. To use this, you need to download the Docker image from the packages in the GitHub repository mentioned above, and run it as a container. The n8n workflow then communicates directly with this container via an HTTP API to request and receive the chart snapshot. After obtaining the image, the workflow calls a multimodal AI model (Gemini). It sends both the chart image and your custom text-based conditions (e.g., "breakout above previous high on high volume" or "break below 4-hour MA20") to the AI for analysis, enabling truly intelligent chart interpretation and alert triggering. Key Features Workflowception: A prime example of one workflow using an API to create, activate, and delete other workflows. Full Control via Telegram: Manage your monitoring bots from anywhere, anytime, without needing to log into the n8n interface. AI Visual Analysis: Move beyond simple price alerts. Let an AI "read" the charts for you to enable complex, pattern-based, and indicator-based intelligent alerts. Persistent & Extensible: Built on PostgreSQL for stability and reliability. You can easily add more custom commands.

How it works This workflow automatically generates and publishes marketing blog posts to WordPress using AI. It begins by checking your PostgreSQL database for unprocessed records, then uses OpenAI to create SEO-friendly, structured blog content. The content is formatted for WordPress, including categories, tags, and meta descriptions, before being published. After publishing, the workflow updates the original database record to track processing status and WordPress post details. Step-by-step Trigger workflow** Schedule Trigger – Runs the workflow at defined intervals. Fetch unprocessed record** PostgreSQL Trigger – Retrieves the latest unprocessed record from the database. Check Record Exists – Confirms the record is valid and ready for processing. Generate AI blog content** OpenAI Chat Model – Processes the record to generate blog content based on the title. Blog Post Agent – Structures AI output into JSON with title, content, excerpt, and meta description. Format and safeguard content** Code Node – Prepares structured data for WordPress, ensuring categories, tags, and error handling. Publish content and update database** WordPress Publisher – Publishes content to WordPress with proper categories, tags, and meta. Update Database – Marks the record as processed and stores WordPress post ID, URL, and processing timestamp. Why use this? Automates end-to-end blog content generation and publishing. Ensures SEO-friendly and marketing-optimized posts. Maintains database integrity by tracking published content. Reduces manual effort and accelerates content workflow. Integrates PostgreSQL, OpenAI, and WordPress seamlessly for scalable marketing automation.

Analyze email performance and optimize campaigns with AI using SendGrid and Airtable This n8n template creates an automated feedback loop that pulls email metrics from SendGrid weekly, tracks performance in Airtable, analyzes trends across the last 4 weeks, and generates specific recommendations for your next campaign. The system learns what works and provides data-driven insights directly to your email creation process. Who's it for Email marketers and growth teams who want to continuously improve campaign performance without manual analysis. Perfect for businesses running regular email campaigns who need actionable insights based on real data rather than guesswork. Good to know After 4-6 weeks, expect 15-30% improvement in primary metrics Requires at least 2 weeks of historical data to generate meaningful analysis System improves over time as it learns from your audience Implementation time: ~1 hour total How it works Schedule trigger runs weekly (typically Monday mornings) Pulls previous week's email statistics from SendGrid (delivered, opens, clicks, rates) Updates the previous week's record in Airtable with actual performance data GPT-4 analyzes trends across the last 4 weeks, identifying patterns and opportunities Creates a new Airtable record for the upcoming week with specific recommendations: what to test, how to change it, expected outcome, and confidence level Your email creation workflow pulls these recommendations when generating new campaigns After sending, the actual email content is saved back to Airtable to close the loop How to set up Create Airtable base: Make a table called "Email Campaign Performance" with fields for week_ending, delivered, unique_opens, unique_clicks, open_rate, ctr, decision, test_variable, test_hypothesis, confidence_level, test_directive, implementation_instruction, subject_line_used, email_body, icp, use_case, baseline_performance, success_metric, target_improvement Configure SendGrid: Add API key to the "SendGrid Data Pull" node and test connection Set up Airtable credentials: Add Personal Access Token and select your base/table in all Airtable nodes Add OpenAI credentials: Configure GPT-4 API key in the "Previous Week Analysis" node Test with sample data: Manually add 2-3 weeks of data to Airtable or run if you have historical data Schedule weekly runs: Set workflow to trigger every Monday at 9 AM (or after your weekly campaign sends) Integrate with email creation: Add an Airtable search node to your email workflow to retrieve current recommendations, and an update node to save what was sent Requirements SendGrid account with API access (or similar ESP with statistics API) Airtable account with Personal Access Token OpenAI API access (GPT-4) Customizing this workflow Use different email platform**: Replace SendGrid node with Mailchimp, Brevo, or any ESP that provides statistics API—adjust field mappings accordingly Add more metrics**: Extend Airtable fields to track bounce rate, unsubscribe rate, spam complaints, or revenue attribution Change analysis frequency**: Adjust schedule trigger for bi-weekly or monthly analysis instead of weekly Swap AI models**: Replace GPT-4 with Claude or Gemini in the analysis node Multi-campaign tracking**: Duplicate the workflow for different campaign types (newsletters, promotions, onboarding) with separate Airtable tables