Workflow Templates

How it works This workflow automatically discovers industry conferences and provides AI-powered networking intelligence to maximize your event ROI. Key Steps Scheduled Discovery - Runs weekly to find new industry conferences from Eventbrite and other sources. AI-Powered Scraping - Uses ScrapeGraphAI to extract comprehensive conference information including speakers, agenda, and networking opportunities. Speaker Intelligence - Analyzes speakers to identify high-priority networking targets based on their role, company, and expertise. Agenda Analysis - Extracts and maps the complete conference schedule to optimize your time and networking strategy. Networking Strategy - Generates AI-powered recommendations for maximizing networking ROI with prioritized contact lists and approach strategies. Set up steps Setup time: 10-15 minutes Configure ScrapeGraphAI credentials - Add your ScrapeGraphAI API key for web scraping capabilities. Customize conference sources - Update the Eventbrite URL to target specific industries or locations. Adjust monitoring frequency - Modify the weekly trigger to match your conference discovery needs. Review networking priorities - The system automatically prioritizes speakers, but you can customize the criteria. Key Features Automated Conference Discovery** - Finds relevant industry events from multiple sources Speaker Intelligence Analysis** - Identifies high-value networking targets with contact priority scoring Strategic Agenda Mapping** - Optimizes your conference schedule for maximum networking impact AI-Powered Recommendations** - Provides personalized networking strategies and approach methods Priority Contact Lists** - Ranks speakers by business value and networking potential

Tagged with: , , , ,

📊 Description Automate LinkedIn profile enrichment and transform raw URLs into beautifully formatted candidate profile pages using n8n and the Apollo.io API 🔍. This workflow receives a LinkedIn URL via webhook, fetches enriched person and company data, normalizes the response, and generates a fully styled HTML profile card in real time. Perfect for recruiters, sales teams, and automation builders who want instant profile intelligence without manual research. Deliver structured contact insights, company details, and tech stack data directly in the browser 🤖. ⚙️ What This Template Does 📥 Receives a LinkedIn profile URL via a Webhook trigger. 🌐 Sends the URL to the Apollo People Match API to fetch enriched person and organization data. 🧹 Cleans and normalizes the raw API response into structured fields. 🖼️ Dynamically generates styled HTML profile cards with candidate and company details. 🚀 Returns a fully rendered HTML page as the webhook response for instant viewing in a browser. ✅ Key Benefits ✅ Instantly enrich LinkedIn profiles with verified business data ✅ Generate clean, structured candidate summaries automatically ✅ Deliver zero-manual research workflow for recruiters & sales teams ✅ Create branded HTML profile pages dynamically ✅ Streamline lead qualification and prospect research ✅ Reliable API-based enrichment with structured output 🧩 Features Webhook-triggered automation workflow Integration with Apollo.io People Match API Real-time LinkedIn profile enrichment JavaScript-based data normalization Dynamic HTML & CSS profile card generation Browser-rendered webhook response Graceful error handling when no profile data is found 🔐 Requirements Apollo.io API key Active n8n instance (Cloud or Self-Hosted) Webhook endpoint enabled Basic understanding of POST requests 🎯 Target Audience Recruitment agencies & talent acquisition teams B2B sales teams & SDRs Lead generation agencies Automation developers building AI-powered prospecting tools

Tagged with: , , , ,

What Is TWZ n8n MailPoet Integration? This workflow adds subscribers to MailPoet using n8n by bridging WordPress through a custom REST API and logging results in Google Sheets. MailPoet is a popular WordPress email marketing plugin, but it does not provide a public REST API. Because of this limitation, n8n cannot connect to MailPoet directly using native nodes or standard integrations. This workflow demonstrates a practical and production-ready solution for connecting n8n → WordPress → MailPoet using a custom WordPress REST API plugin called TWZ N8N MailPoet. 🚧 Problem This Workflow Solves ❌ MailPoet has no public REST API ❌ n8n cannot add MailPoet subscribers natively ❌ External forms and automations cannot push data into MailPoet ✅ Solution Architecture This workflow solves the problem by: Creating a secure REST API endpoint inside WordPress Using an n8n HTTP Request node to send subscriber data Adding subscribers directly to MailPoet Preventing duplicate subscribers Logging subscribers in Google Sheets for visibility This creates a reliable bridge between n8n and MailPoet, enabling automation workflows that were previously not possible. 🔌 How It Works (High Level) 📥 n8n receives form submission data 🔍 The workflow checks if the subscriber already exists 📧 The subscriber is added to MailPoet via the custom REST API 📊 Subscriber data is logged in Google Sheets ✅ The workflow returns a success or error response 🎯 Why This Workflow Is Useful Works around MailPoet’s missing API Enables full automation from external tools Uses standard n8n nodes (HTTP Request, IF, Google Sheets) Secure and reusable integration pattern Ideal for WordPress-based businesses 🧩 About the TWZ n8n MailPoet Plugin TWZ n8n MailPoet is a free, lightweight WordPress plugin designed to provide a simple and reliable integration between n8n (or any external service) and MailPoet. It implements a single MailPoet API operation: ➡ Add Subscriber This keeps the plugin lightweight, fast, and focused.

🔎 Automated Keyword Research Workflow with Google sheet logging & Semrush API Description: Easily collect keywords and country input, run automated keyword research via the Semrush Keyword Research API on RapidAPI, and store results in Google Sheets for seamless tracking and analysis. ⚙️ Node-by-Node Explanation 🟢 On form submission (formTrigger) Collects keyword and country inputs from the user via a simple form to start the research process. Triggers the workflow execution upon submission. 🌐 Keyword Research (httpRequest) Sends a POST request with user inputs (keyword and country) to the Semrush Keyword Research. Retrieves keyword suggestions, search volume, and related data for comprehensive keyword insights. 📄 Append Data to Google Sheet (googleSheets) Automatically appends the keyword research results into a connected Google Sheets document. Enables easy tracking, sharing, and further analysis of keyword data. 📈 Example Spreadsheet Structure | Keyword | Country | Search Volume | CPC | Competition | Keyword Difficulty | Related Keywords | Date of Research | |---------------|---------|---------------|------|-------------|--------------------|-------------------------------------|------------------| | keyword1 | US | 10,000 | $2.50| 0.75 | 45 | keyword2, keyword3 | 2025-09-09 | | example term | UK | 15,000 | $1.80| 0.60 | 38 | term1, example keyword | 2025-09-09 | 🌟 Benefits 🚀 Powered by **Semrush Keyword Research API on RapidAPI:** Reliable, up-to-date keyword insights accessible via a simple API integration. 🔄 Fully Automated: From user input to data storage, the process is seamless and requires no manual handling. 📊 Centralized Data Storage: Storing results in Google Sheets ensures accessibility and easy collaboration. 📈 Scalable & Repeatable: Run keyword research on-demand for multiple keywords and countries effortlessly. 🚀 Use Cases 🏢 SEO Agencies: Quickly gather keyword data for clients in different markets using the Semrush Keyword Research. 📱 Digital Marketing Teams: Monitor and expand keyword strategies by collecting keyword ideas and volume regularly through the Semrush Keyword Research. 🔎 Content Creators: Identify trending and high-traffic keywords tailored by country to optimize content via the Semrush Keyword Research API. 📅 Automated Reporting: Generate scheduled keyword research reports by integrating this workflow into larger marketing automation pipelines. 🔑 How to Get Your API Key for Semrush Keyword Research Visit the API Page: Go to the Semrush Keyword Research on RapidAPI. Sign Up/Login: Create an account or log in if you already have one. Subscribe to the API: Click "Subscribe to Test" and choose a plan (free or paid). Copy Your API Key: After subscribing, your API Key will be available in the "X-RapidAPI-Key" section under "Endpoints". Use the Key: Include the key in your API requests like this: -H "X-RapidAPI-Key: YOUR_API_KEY" 🛠 Customizing the Workflow To modify the automated workflow and adapt it to your specific use case, follow these guidelines: Adjust the Data Retrieval Process: You can modify the data you want to receive from the Semrush API. For example, if you’re only interested in search volume and CPC, you can filter out the other results in the API request. Add More Countries: If you work with multiple regions, modify the workflow to accept multiple country inputs. You could either pass in a list of countries or have a dropdown on the form that lets users select their country of choice. Expand Keyword Types: The workflow can be expanded to collect data for different types of keywords, such as long-tail or LSI (Latent Semantic Indexing) keywords, depending on your SEO needs. Set Up Scheduled Keyword Reporting: To automate reporting, you can schedule keyword research reports to run at regular intervals, such as monthly, using Google Apps Script or another task scheduler. This way, you’ll always have fresh data on hand for analysis. ✅ Tips for Smooth Workflow Integration Test Your API Integration: Run a test to check if data is properly flowing into your Google Sheet before automating the process. Set Up Notifications: Use Google Sheets' built-in notifications or an external automation tool (e.g., Zapier, Integromat) to notify you when new data is added or if there’s an issue with the workflow. Handle Errors Gracefully: Add error handling in your automated process to prevent issues like missing data or API request failures from disrupting your workflow.

Simple REST API with Google Sheets Introduction This workflow template demonstrates how to quickly and easily create a simple REST API using n8n and a Google Sheet as a no-code database. It's a perfect starting point for building a backend for small applications, prototypes, or internal tools without writing any code. Purpose The purpose of this template is to provide a complete, ready-to-use n8n workflow that handles all fundamental CRUD (Create, Read, Update, Delete) operations. The workflow uses a single Webhook trigger to handle POST, GET, PUT, and DELETE requests, allowing you to manage data in your Google Sheet through standard API calls. Setup Instructions To get started with this template, follow these steps: Prepare your Google Sheet: Create a new Google Sheet and add the following column headers in the first row: name, email, and status. You can use this example Google Sheet as a starting point. This sheet will serve as your database. Authenticate: In the n8n workflow, connect your Google Account credentials to the Google Sheets nodes. Select your data: Choose the Google Sheet and the corresponding sheet name from the drop-down lists in each of the Google Sheets nodes. Activate: Save and activate the workflow. Test the API: Use a tool like curl, Postman, or Insomnia to test your new API endpoints. The base URL will be your n8n webhook URL followed by /items. Example curl Commands: POST (Create):** curl -X POST YOUR_N8N_WEBHOOK_URL/items -H "Content-Type: application/json" -d '{"name": "Alice", "email": "alice@example.com", "status": "active"}' GET (Read All):** curl -X GET YOUR_N8N_WEBHOOK_URL/items/all GET (Read Single):** curl -X GET YOUR_N8N_WEBHOOK_URL/items?id=2 PUT (Update):** curl -X PUT YOUR_N8N_WEBHOOK_URL/items?id=2 -H "Content-Type: application/json" -d '{"status": "inactive"}' DELETE (Delete):** curl -X DELETE YOUR_N8N_WEBHOOK_URL/items?id=2 For more detailed instructions, including building the workflow in n8n, check out the full blog post: Build a Simple REST API in 10 Minutes with n8n & Google Sheets

This n8n automation connects your Typeform forms with Vapi AI, allowing you to immediately call new form respondents with a personalized message from a Vapi AI assistant, as soon as a form submission is received. 🧾 Requirements Typeform A Typeform account Typeform personal access token and credentials enabled in n8n A Typeform form published that includes a phone number field Vapi A Vapi account with credit A connected phone number to make calls An assistant created and ready to make calls Your Vapi API key 🔗 Useful Links n8n Typeform Credentials Setup Vapi Docs 🔄 Workflow Breakdown 1. Trigger: Typeform Submission Triggered when a new response is submitted to your Typeform. The form must include a phone number field. 2. Wait 2 Minutes Adds a short delay before proceeding. Useful to ensure form data is fully synced or to give time for related automations. 3. Set Vapi Fields (Manual Step) Set the required fields for the Vapi API call: phone number id - connected in Vapi assistant id - the assistant enabled in the call Vapi API key - your secure API key 4. Start Outbound Vapi Call Sends a POST request to https://api.vapi.ai/call Payload includes: Respondent’s phone number (from Typeform) Vapi assistant id Vapi phone number id to initiate the call ✏️ Template Customization Guidance How to Adapt for Your Specific Needs Personalize the Call Content:** Include additional fields in your Typeform (e.g., first name, interest, location). In n8n, map these form fields into the payload sent to Vapi. Update your Vapi assistant’s prompt/script to reference these variables for a highly personalized experience. Conditional Call Logic:** Use n8n's logic nodes (e.g., IF, Switch) to, for example: Only trigger calls if a respondent checks a checkbox (e.g., consent or interest). Use a different Vapi assistant or phone number based on responses (e.g., language preference or location). Advanced Routing:** Configure the workflow to choose different assistants, phone numbers, or call scripts based on the respondent’s answers. Store assistant IDs or numbers as environment variables or reference them from a lookup table for dynamic selection. 📞 Examples: Using Form Data to Personalize Calls Greeting by Name:** If your Typeform collects first_name, map it into the Vapi payload. Your assistant script can begin, "Hi {{first_name}}, thanks for your interest in XYZ!" Custom Message Based on Product Interest:** Add a product_interest field in Typeform. Pass its value to Vapi and have the assistant mention the product, e.g., “I see you’re interested in our Premium Plan…” Reference Appointment Times or Locations:** Collect appointment_time and/or city fields, and tailor the call to reconfirm booking details using these inputs. 🛠️ Troubleshooting & Tips Call Not Triggering:** Ensure your Typeform webhook connection and credentials are correctly set up in n8n. Check that your workflow is active and the trigger node is configured for the correct form. Invalid Phone Number Format:** Vapi requires numbers in full international format (e.g., +11234567890). Use n8n expressions to clean or verify the incoming number if needed. Missing Data in the Call:** Confirm that additional fields (e.g., first_name) exist in the Typeform response and that your mapping in n8n matches the exact field names. Failed API Call:** Double-check your Vapi phone number id, assistant id, and API key. Use n8n’s execution logs to inspect the payload sent to Vapi for debugging. Duplicate Calls:** If your Typeform allows multiple submissions, add logic in n8n to check for and avoid duplicate calls, for example by maintaining a record of called numbers. 🙋‍♂️ Need Help? Feel free to contact us at 1 Node Get instant access to a library of free resources we created.

Overview This workflow provides a universal webhook endpoint that dynamically routes incoming requests to different subflows. It allows you to manage multiple API-like endpoints from a single entry point, while ensuring proper error handling and consistent responses. How it works Webhook Receiver – A single URL accepts requests. Method Detection – Branches capture the request method. Route Resolver – Matches the action parameter and method against your route configuration. Execute Subflow – If valid, the matching workflow is executed. Error Handling – If invalid, the workflow responds with a clear status code and JSON error. About the action parameter The action query parameter is the key that controls routing: In your Routes Config, every route is defined with an action name, a list of allowed HTTP methods, and the target subflow ID. When a request comes in, the workflow looks up the provided action in this config. If the action is valid and the method is allowed, the corresponding subflow is executed. If not, the workflow returns a structured error. In other words: Config side** → map action → subflow ID Request side** → send ?action=... → determines which subflow runs This makes action both the mapping key in the configuration and the control key for triggering the correct logic. Setup steps Import the workflow into n8n. Define your routes in the Routes Config node. Each route contains: action name allowed HTTP methods target subflow ID This workflow is useful if you want to: Expose multiple clean API endpoints without creating many Webhook nodes Ensure consistent error handling across all endpoints Keep your n8n setup more structured and maintainable 👉 A practical solution to turn n8n into a flexible and maintainable API gateway.

Overview This n8n workflow provides seamless integration with Cerebras' high-performance inference platform to leverage OpenAI's open-source GPT-OSS-120B model. With industry-leading speeds of thousands of tokens per second and ultra-low latency under 0.5 seconds, this template enables developers and businesses to build responsive AI applications without the complexity of managing infrastructure or dealing with slow response times that plague traditional AI integrations. How it works This streamlined workflow establishes a direct connection to Cerebras' inference API through four simple nodes. When a chat message is received, the workflow processes it through the configured API key, sends it to the Cerebras endpoint with your specified parameters (temperature, completion tokens, top P, reasoning effort), and returns the AI-generated response. Detailed Workflow Explanation 1. When chat message received: This trigger node initiates the workflow whenever a new chat message is detected. It captures the user's input and passes it to the next node in the chain, supporting various input formats and message sources. 2. Set API Key: A manual configuration node where you securely store your Cerebras API key. This node handles authentication and ensures your requests are properly authorized when communicating with the Cerebras inference API. 3. Cerebras endpoint: The core HTTP request node that communicates with Cerebras' chat completions API. This node is pre-configured to work with the GPT-OSS-120B model and includes parameter settings for temperature, completion tokens, top P, and reasoning effort that can be customized based on your specific needs. 4. Return Output: The final node that processes and formats the AI response, delivering the generated text back to your application or user interface in a clean, usable format. Who is it for Developers building real-time chat applications, conversational AI systems, or interactive web applications who need consistent sub-second response times without managing complex AI infrastructure. Content creators and marketing teams who require rapid text generation for blogs, social media content, product descriptions, or marketing copy, enabling faster content production cycles and improved productivity. Businesses implementing customer service automation, lead qualification systems, or interactive FAQ solutions where response latency directly impacts user experience and conversion rates. SaaS companies looking to integrate AI features into existing products without the overhead of training models or managing inference servers, allowing them to focus on core business logic. Researchers and data scientists experimenting with high-performance language models for prototyping, A/B testing different prompting strategies, or conducting performance benchmarks against other AI providers. Startups and small teams seeking enterprise-grade AI capabilities without the infrastructure costs or technical complexity typically associated with large language model deployment. Comprehensive Setup Instructions 1. Cerebras Account Setup Visit Cerebras and create a new account Complete email verification and profile setup Navigate to the API Keys section in your dashboard Generate a new API key and securely store it Review the rate limits for free tier accounts and upgrade if needed 2. N8N Workflow Configuration Import the template into your n8n instance Click on the "Set API Key" node and enter your Cerebras API key Configure the trigger node based on your input source (webhook, manual, scheduled) Test the workflow using the built-in execution feature 3. Parameter Customization Open the "Cerebras endpoint" node to access the parameter configuration Adjust temperature, completion tokens, top P, and reasoning effort based on your use case Save and test the workflow to ensure proper functionality Customization and Configuration Guide Model Parameters in the Cerebras Endpoint Node: Temperature** (0.0-2.0): Lower values (0.1-0.3) for factual, consistent responses; higher values (0.7-1.5) for creative, varied content Completion Tokens**: Set based on expected response length - 150 for short answers, 500+ for detailed explanations, 1000+ for long-form content Top P** (0.1-1.0): Controls response diversity; 0.9 works well for most applications, lower values for more focused responses Reasoning Effort**: Adjusts the model's computational effort for complex reasoning tasks; higher values for analytical or problem-solving queries Use Case Specific Configurations: Customer Support**: Temperature 0.2, moderate completion tokens, consistent helpful responses Creative Writing**: Temperature 1.0-1.2, higher completion tokens for diverse, imaginative content Technical Documentation**: Temperature 0.3, structured output with examples and code snippets Casual Conversation**: Temperature 0.7, balanced creativity and coherence Integration Scenarios: Connect the trigger to webhooks for external application integration Modify the output node to format responses for specific platforms (Slack, Discord, web apps) Add conditional logic to handle different types of user queries Implement input validation and sanitization for production environments Possible Enhancements Multi-model support: Extend the workflow to switch between different Cerebras models based on query complexity or specific requirements. Response caching: Add caching mechanisms to store frequently requested responses, reducing API calls and improving performance. Advanced error handling: Implement retry logic and fallback mechanisms for improved reliability in production environments. Content filtering: Integrate moderation capabilities to ensure appropriate responses in customer-facing applications. Analytics integration: Connect monitoring tools to track usage patterns, response quality, and performance metrics. Multi-channel triggers: Set up automated responses for various platforms like Slack, Discord, or custom webhooks. Template management: Create reusable prompt templates for different scenarios and use cases. Output formatting: Add post-processing for specific output formats (HTML, Markdown, JSON) based on integration requirements.

Tagged with: , , , ,

Tagged with: , , , ,