Automated animal advocacy news research & weekly digest using Claude AI & Serper
Who’s it for 🎯
This workflow is designed for animal advocacy organizations, activists, and campaigners who want to automatically receive a weekly email update summarizing the latest news and developments related to animal rights, welfare, vegetarianism, and veganism. It can also be easily altered to allow daily updates.
How it works / What it does ⚙️
Runs on a weekly schedule and uses a multi-tool research agent subworkflow to gather verified news strictly from the past week. It compiles the information and URLs into a clean, well-structured HTML email, then sends it to the specified recipient. URLs are never altered or omitted.
How to set up 🛠️
- Import this workflow into your n8n instance.
- Add and install the required research subworkflow:
Multi-tool Research Agent for Animal Advocacy - Configure API keys in n8n credentials.
- Set your topics, instructions, and recipient email in the “Set Preferences” node.
- Adjust the schedule node to control when emails are sent.
- Test the full workflow to ensure proper operation.
Requirements 📋
- n8n instance with internet access
- Valid API keys
- The Multi-tool Research Agent subworkflow installed
- SMTP or email sending configured
How to customize 🔧
- Update Topics: Change topics in the “Set Preferences” node to focus the research.
- Update Instructions: Tailor summary style and focus in the preferences node.
- Email Recipient: Set who receives the update email.
- Scheduling: Change frequency or time in the Schedule node. Duplicate for daily versions with adjusted research parameters.
- HTML Styling: Modify the “Write HTML” node’s template for custom branding or layout.
- Error Handling: Add workflows to capture and alert on errors for robustness.
Adapt and extend as needed for your advocacy goals!
n8n Workflow: Basic LLM Chain with OpenRouter Chat Model
This n8n workflow demonstrates a fundamental use case for integrating Large Language Models (LLMs) into your automation flows, specifically utilizing the OpenRouter service for chat model interactions. It sets up a basic LLM chain that can be triggered manually or on a schedule, processes input, interacts with an AI chat model, and then sends the generated output via email.
What it does
This workflow automates the following steps:
- Triggers on Schedule: The workflow is set to run periodically based on a defined schedule (e.g., weekly, daily, hourly).
- Prepares Input: An "Edit Fields (Set)" node allows for defining or modifying the input data that will be sent to the LLM. This could be a prompt, context, or other relevant information.
- Executes Sub-workflow (Optional/Placeholder): Includes an "Execute Sub-workflow" node, suggesting modularity. While not connected in this JSON, it indicates the potential to call other workflows for more complex pre-processing or data enrichment.
- Interacts with AI Chat Model: A "Basic LLM Chain" node, configured with an "OpenRouter Chat Model," sends the prepared input to the OpenRouter service for AI processing. This is where the core AI logic (e.g., summarization, text generation, question answering) would occur.
- Sends Email: The final output from the AI model is then sent as an email, delivering the results to a specified recipient.
- Sticky Note: A sticky note is included for documentation or temporary notes within the workflow.
Prerequisites/Requirements
To use this workflow, you will need:
- n8n Instance: A running instance of n8n.
- OpenRouter Account & API Key: An account with OpenRouter and an associated API key for accessing their chat models.
- Email Sending Credentials: SMTP server details or an email service credential configured in n8n to send emails.
Setup/Usage
- Import the Workflow: Download the provided JSON and import it into your n8n instance.
- Configure Credentials:
- OpenRouter Chat Model: Configure the "OpenRouter Chat Model" node with your OpenRouter API key.
- Send Email: Configure the "Send Email" node with your SMTP credentials or select an existing email service credential.
- Customize Input:
- Edit Fields (Set): Modify the "Edit Fields" node to define the input data or prompt you want to send to the LLM.
- Configure LLM Chain:
- Basic LLM Chain: Adjust the "Basic LLM Chain" node's settings, including the prompt template and any other parameters for the OpenRouter model, to achieve your desired AI interaction.
- Set Schedule:
- Schedule Trigger: Configure the "Schedule Trigger" node to define how often you want the workflow to run (e.g., once a week, daily at a specific time).
- Customize Email:
- Send Email: Update the "Send Email" node with the recipient's email address, subject, and body content, using expressions to include the output from the AI model.
- Activate the Workflow: Once configured, activate the workflow to enable it to run on its schedule.
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Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets
This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitor’s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger — Manually start the workflow or schedule it to run periodically. Input Setup — Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) — Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring — Clean and convert GPT output into JSON format. Data Storage (Google Sheets) — Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the “Set Input Fields” node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors → Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection → Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report → Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization → Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs → Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting It’s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.
By Ranjan DailataSend WooCommerce discount coupons to customers via WhatsApp using Rapiwa API
Who is this for? This workflow is ideal for WooCommerce store owners who want to automatically send promotional WhatsApp messages to their customers when new coupons are created. It’s designed for marketers and eCommerce managers looking to boost engagement, streamline coupon sharing, and track campaign performance effortlessly through Google Sheets. Overview This workflow listens for WooCommerce coupon creation events (coupon.created) and uses customer billing data to send promotional WhatsApp messages via the Rapiwa API. The flow formats the coupon data, cleans phone numbers, verifies WhatsApp registration with Rapiwa, sends the promotional message when verified, and logs each attempt to Google Sheets (separate sheets for verified/sent and unverified/not sent). What this Workflow Does Listens for new coupon creation events in WooCommerce via the WooCommerce Trigger node Retrieves all customer data from the WooCommerce store Processes customers in batches to control throughput Cleans and formats customer phone numbers for WhatsApp Verifies if phone numbers are valid WhatsApp accounts using Rapiwa API Sends personalized WhatsApp messages with coupon details to verified numbers Logs all activities to Google Sheets for tracking and analysis Handles both verified and unverified numbers appropriately Key Features Automated coupon distribution: Triggers when new coupons are created in WooCommerce Customer data retrieval: Fetches all customer information from WooCommerce Phone number validation: Verifies WhatsApp numbers before sending messages Personalized messaging: Includes customer name and coupon details in messages Dual logging system: Tracks both successful and failed message attempts Rate limiting: Uses batching and wait nodes to prevent API overload Data formatting: Structures coupon information for consistent messaging Google Sheet Column Structure A Google Sheet formatted like this ➤ sample The workflow uses a Google Sheet with the following columns to track coupon distribution: | name | number | email | address1 | couponCode | couponTitle | couponType | couponAmount | createDate | expireDate | validity | status | | ----------- | ------------- | --------------------------------------------------- | --------- | ---------- | -------------- | ---------- | ------------ | ------------------- | ------------------- | ---------- | -------- | | Abdul Mannan | 8801322827799 | contact@spagreen.net | mirpur-DOHS | 62dhryst | eid offer 2025 | percent | 20.00 | 2025-09-11 06:08:02 | 2025-09-15 00:00:00 | unverified | not sent | | Abdul Mannan | 8801322827799 | contact@spagreen.net | mirpur-DOHS | 62dhryst | eid offer 2025 | percent | 20.00 | 2025-09-11 06:08:02 | 2025-09-15 00:00:00 | verified | sent | Requirements n8n instance with the following nodes: WooCommerce Trigger, Code, SplitInBatches, HTTP Request, IF, Google Sheets, Wait WooCommerce store with API access Rapiwa account with API access for WhatsApp verification and messaging Google account with Sheets access Customer phone numbers in WooCommerce (stored in billing.phone field) Important Notes Phone Number Format: The workflow cleans phone numbers by removing all non-digit characters. Ensure your WooCommerce phone numbers are in a compatible format. API Rate Limits: Rapiwa and WooCommerce APIs have rate limits. Adjust batch sizes and wait times accordingly. Data Privacy: Ensure compliance with data protection regulations when sending marketing messages. Error Handling: The workflow logs unverified numbers but doesn't have extensive error handling. Consider adding error notifications for failed API calls. Message Content: The current message template references the first coupon only (coupons[0]). Adjust if you need to handle multiple coupons. Useful Links Dashboard: https://app.rapiwa.com Official Website: https://rapiwa.com Documentation: https://docs.rapiwa.com Support & Help WhatsApp: Chat on WhatsApp Discord: SpaGreen Community Facebook Group: SpaGreen Support Website: https://spagreen.net Developer Portfolio: Codecanyon SpaGreen
By RapiwaCreate personalized email outreach with AI, Telegram bot & website scraping
Demo Personalized Email This n8n workflow is built for AI and automation agencies to promote their workflows through an interactive demo that prospects can try themselves. The featured system is a deep personalized email demo. --- 🔄 How It Works Prospect Interaction A prospect starts the demo via Telegram. The Telegram bot (created with BotFather) connects directly to your n8n instance. Demo Guidance The RAG agent and instructor guide the user step-by-step through the demo. Instructions and responses are dynamically generated based on user input. Workflow Execution When the user triggers an action (e.g., testing the email demo), n8n runs the workflow. The workflow collects website data using Crawl4AI or standard HTTP requests. Email Demo The system personalizes and sends a demo email through SparkPost, showing the automation’s capability. Logging and Control Each user interaction is logged in your database using their name and id. The workflow checks limits to prevent misuse or spam. Error Handling If a low-CPU scraping method fails, the workflow automatically escalates to a higher-CPU method. ⚙️ Requirements Before setting up, make sure you have the following: n8n — Automation platform to run the workflow Docker — Required to run Crawl4AI Crawl4AI — For intelligent website crawling Telegram Account — To create your Telegram bot via BotFather SparkPost Account — To send personalized demo emails A database (e.g., PostgreSQL, MySQL, or SQLite) — To store log data such as user name and ID 🚀 Features Telegram interface using the BotFather API Instructor and RAG agent to guide prospects through the demo Flow generation limits per user ID to prevent abuse Low-cost yet powerful web scraping, escalating from low- to high-CPU flows if earlier ones fail --- 💡 Development Ideas Replace the RAG logic with your own query-answering and guidance method Remove the flow limit if you’re confident the demo can’t be misused Swap the personalized email demo with any other workflow you want to showcase --- 🧠 Technical Notes Telegram bot created with BotFather Website crawl process: Extract sub-links via /sitemap.xml, sitemap_index.xml, or standard HTTP requests Fall back to Crawl4AI if normal requests fail Fetch sub-link content via HTTPS or Crawl4AI as backup SparkPost used for sending demo emails --- ⚙️ Setup Instructions Create a Telegram Bot Use BotFather on Telegram to create your bot and get the API token. This token will be used to connect your n8n workflow to Telegram. Create a Log Data Table In your database, create a table to store user logs. The table must include at least the following columns: name — to store the user’s name or Telegram username. id — to store the user’s unique identifier. Install Crawl4AI with Docker Follow the installation guide from the official repository: 👉 https://github.com/unclecode/crawl4ai Crawl4AI will handle website crawling and content extraction in your workflow. --- 📦 Notes This setup is optimized for low cost, easy scalability, and real-time interaction with prospects. You can customize each component — Telegram bot behavior, RAG logic, scraping strategy, and email workflow — to fit your agency’s demo needs. 👉 You can try the live demo here: @emaildemobot ---
By Michael A Putra