Automate sales cold calling pipeline with Apify, GPT-4o, and WhatsApp
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Cold Calling Automation - End-to-End Automated Cold Calling with Apify, RAG, and WhatsApp The "Cold Calling Automation" workflow is designed to fully automate the end-to-end cold calling process by intelligently combining web scraping, AI-powered research, and WhatsApp messaging. Leveraging key technologies such as Apify for data scraping, RAG (Retrieval-Augmented Generation) for intelligent content creation, and WhatsApp integration for automated outreach, this workflow transforms raw prospect data into personalized, high-converting cold calling campaigns with minimal manual intervention. 💡 Why Use Cold Calling Automation? Scale Your Outreach: Automate hundreds of personalized cold calls without manual effort or hiring additional staff. Intelligent Personalization: RAG technology creates highly relevant, personalized messages based on prospect research. Multi-Channel Approach: Seamlessly integrate WhatsApp messaging with traditional cold calling methods. Real-Time Optimization: Continuously improve message performance and conversion rates through AI analysis. Cost-Effective: Reduce cold calling costs while dramatically increasing reach and response rates. ⚡ Who Is This For? Sales Teams: Looking to scale their cold calling efforts with intelligent automation and personalization. Lead Generation Agencies: Needing to deliver high-volume, high-quality cold calling services to clients. Business Development Professionals: Seeking to maximize outreach efficiency while maintaining personal touch. Small Business Owners: Who want professional-grade cold calling capabilities without hiring expensive sales teams. Marketing Agencies: Offering comprehensive lead generation and conversion services to clients. ❓ What Problem Does It Solve? Traditional cold calling is time-consuming, expensive, and often ineffective due to lack of personalization and poor timing. Manual prospect research, script writing, and call execution create bottlenecks that limit outreach scale. Generic messages result in low response rates and damaged brand reputation. This workflow solves these problems by automating the entire cold calling pipeline - from prospect identification and research to personalized message creation and delivery - while maintaining high quality and relevance that converts prospects into qualified leads. 🔧 What This Workflow Does ⏱ Prospect Scraping: Uses Apify to automatically scrape and identify high-quality prospects based on your target criteria. 🔍 Intelligent Research: Employs RAG technology to research each prospect and gather relevant business intelligence. ✍️ Personalized Content: Automatically generates custom messages, scripts, and talking points for each prospect. 📱 WhatsApp Integration: Delivers personalized messages through WhatsApp automation for maximum engagement. 📊 Performance Tracking: Monitors response rates, engagement metrics, and conversion data for continuous optimization. 🤖 AI-Powered Follow-up: Automatically handles initial responses and schedules appropriate follow-up actions. 📈 Campaign Analytics: Provides detailed insights on campaign performance and ROI metrics. 🔄 Continuous Learning: Improves message effectiveness and targeting based on campaign results. This workflow also using community node: @devlikeapro/n8n-nodes-waha 🔐 Setup Instructions Import the provided workflow JSON into your n8n instance (Cloud or self-hosted). Set up credentials: Apify API credentials for prospect scraping OpenAI API key for RAG and content generation WhatsApp Business API credentials or WAHA integration Database credentials for prospect and campaign tracking Email credentials for notifications and reporting Customize parameters: Target prospect criteria and scraping parameters Message templates and personalization rules Campaign timing and frequency settings Response handling and follow-up logic Performance tracking and reporting preferences Test the complete workflow with a small prospect list to verify scraping, personalization, and delivery. 🧩 Pre-Requirements Active n8n instance (Cloud or Self-hosted) Apify account with appropriate scraping credits OpenAI API key with sufficient usage limits WhatsApp Business account or WAHA setup Database system for prospect and campaign management Basic understanding of your target audience and value proposition 🛠️ Customize It Further Integrate with CRM systems to sync prospects and track conversion through sales pipeline. Add voice calling capabilities using VoIP services for complete omnichannel outreach. Implement A/B testing for message templates and timing optimization. Connect with social media platforms for multi-channel prospecting and engagement. Add sentiment analysis to optimize message tone and approach for different prospect types. Integrate with calendar systems for automatic meeting scheduling from qualified responses. 🧠 Nodes Used Apify nodes for prospect scraping and data collection OpenAI Chat Model and Embeddings for RAG implementation WhatsApp/WAHA nodes for message delivery and response handling Database nodes for prospect storage and campaign tracking HTTP Request nodes for API integrations and webhooks Code nodes for data processing and personalization logic Schedule Trigger for automated campaign execution Conditional nodes for response handling and follow-up logic Set nodes for parameter configuration and data transformation Split In Batches for efficient bulk processing 📊 Expected Results 50-80% increase in cold calling efficiency and prospect reach 25-40% higher response rates compared to generic cold calling 60-75% reduction in manual research and message preparation time Real-time insights into campaign performance and prospect engagement Scalable system that grows with your business needs 📞 Support Made by: khaisa Studio Tag: automation, cold calling, lead generation, apify, RAG, whatsapp, AI, sales automation, outreach Category: Sales Automation & Lead Generation Need a custom? contact me for more tailored templates
By Khairul MuhtadinAuto-generate virtual AI try-on images for WooCommerce with Gemini Nano Banana
This workflow automates the creation of AI-generated virtual try-on images for fashion eCommerce stores. Instead of relying on expensive and time-consuming photoshoots, the system uses AI to generate realistic images of models wearing selected clothing items. This n8n workflow automates the process of generating AI-powered virtual try-on images for a WooCommerce store. It fetches product data from a Google Sheet, uses the Fal.ai Nano Banana model to create an image of a model wearing the clothing item, and then updates both the Google Sheet and the WooCommerce product with the final generated image. --- Advantages ✅ Cost Reduction: Eliminates the need for professional photo shoots, saving on models, photographers, and studio expenses. ✅ Time Efficiency: Automates the entire workflow—from data input to product update—minimizing manual work. ✅ Scalability: Works seamlessly across large product catalogs, making it easy to update hundreds of products quickly. ✅ Enhanced eCommerce Experience: Provides shoppers with realistic previews of clothing on models, boosting trust and conversion rates. ✅ Marketing Flexibility: The generated images can also be repurposed for ads, social media, and promotional campaigns. ✅ Centralized Management: Google Sheets acts as the control center, making it easy to manage inputs and track results. --- How It Works The workflow operates in a sequential, loop-based manner to process multiple products from a spreadsheet. Here is the logical flow: Manual Trigger & Data Fetch: The workflow starts manually (e.g., by clicking "Test workflow"). It first reads data from a specified Google Sheet, looking for rows where the "IMAGE RESULT" column is empty. Loop Processing: It loops over each row of data fetched from the sheet. Each row should contain URLs for a model image and a product image, along with a WooCommerce product ID. API Request to Generate Image: For each item in the loop, the workflow sends a POST request to the Fal.ai Nano Banana API. The request includes the two image URLs and a prompt instructing the AI to create a photo of the model wearing the submitted clothing item. Polling for Completion: The AI processing is asynchronous. The workflow enters a polling loop: it waits for 60 seconds and then checks the status of the processing request. If the status is not COMPLETED, it waits and checks again. This loop continues until the image is ready. Fetching and Storing the Result: Once the status is COMPLETED, the workflow retrieves the URL of the generated image, downloads the image file, and uploads it to a designated folder in Google Drive. Updating Systems: The workflow then performs two crucial update steps: It updates the original Google Sheet row, writing the URL of the final generated image into the "IMAGE RESULT" column. It updates the corresponding product in WooCommerce, adding the generated image to the product's gallery. Loop Continuation: After processing one item, the workflow loops back to process the next row in the Google Sheet until all items are complete. --- Set Up Steps To make this workflow functional, you need to configure three main connections: Step 1: Prepare the Google Sheet Create a Google Sheet with the following columns: IMAGE MODEL, IMAGE PRODUCT, PRODUCT ID, and IMAGE RESULT. Populate the first three columns for each product. The IMAGE RESULT column must be left blank; the workflow will fill it automatically. In the n8n workflow, configure the "Google Sheets" node to point to your specific Google Sheet and worksheet. Step 2: Configure the Fal.ai API Key Create an account at fal.ai and obtain your API key. In the n8n workflow, locate the three "HTTP Request" nodes named "Get Url image", "Get status", and "Create Image". Edit the credentials for these nodes (named "Fal.run API") and update the Value field in the Header Auth to be Key YOURAPIKEY (replacing YOURAPIKEY with your actual key). Step 3: Set Up WooCommerce API Ensure you have the API keys (Consumer Key and Consumer Secret) for your WooCommerce store's REST API. In the n8n workflow, locate the "WooCommerce" node. Edit its credentials and provide the required information: your store's URL and the API keys. This allows the workflow to authenticate and update your products. --- Need help customizing? Contact me for consulting and support or add me on Linkedin.
By DavideAutomate SEO blog creation + social media with GPT-4, Perplexity and WordPress
🚀 AI Blog & Social Media Publisher – Fully Automated Workflow This workflow is ideal for individuals, marketers, agencies, and brands who want to effortlessly automate the entire blogging and social media process—from idea generation to promotion. Its primary goal is to consistently deliver engaging, SEO-optimized blog posts directly to WordPress, accompanied by professionally crafted social media content ready for Instagram, Facebook, and X (Twitter). No writers, editors, designers, or social media managers required. Save countless hours and resources while boosting your brand's online presence. 🔧 Workflow Capabilities: -Automated Blog Topic Generation: Instantly generates unique, high-value blog ideas tailored to your brand. -SEO Content Creation: Produces comprehensive, 2000–2500 word articles optimized for search engines. -Real-Time Research: Integrates Perplexity AI to ensure factually accurate, authoritative content. -Visual Content Generation: Creates custom, AI-generated featured images via GPT-4, with automatic fallback to Pexels. -WordPress Publishing: Automatically publishes articles directly to WordPress with complete formatting (HTML), meta descriptions, featured images, and proper categorization. -Social Media Automation: Generates and schedules engaging, platform-specific posts for Instagram, Facebook, and X, complete with relevant hashtags, calls-to-action, and links. -Detailed Logging & Reporting: Logs every step transparently into Google Sheets and optionally sends publication reports to Gmail. ⚙️ How It Works: When activated, the workflow checks your content calendar in Google Sheets to avoid duplicate topics. It generates fresh, brand-aligned blog ideas, conducts live research, and creates complete, ready-to-publish articles. It then automatically designs and sources appropriate visuals, publishes content seamlessly to WordPress, and prepares engaging social media posts optimized for each platform. 🛠️ Easy Setup Steps: -Connect your APIs: OpenAI, WordPress, Google Sheets, Gmail, and optionally Pexels. -Replace placeholders (WordPress URLs, Google Sheets ID/tab, workflow IDs). -Customize AI prompts with your brand’s tone, keywords, and CTAs for personalized content. -Configure scheduling to automate daily, weekly, or custom publishing intervals. 📌 Additional Features: -Modular workflow design for easy customization and scalability. -Comprehensive Markdown and PDF setup guides included. -Bonus: Reference placeholders and quick-edit Sticky Notes for effortless adjustments. Launch today. Automate permanently. Amplify your reach effortlessly.
By LukaszBExtract Title tag and Meta description from url for SEO analysis with Airtable
Extract Title tag and meta description from url for SEO analysis. How it works The workflows takes records from Airtable, get the url in the records and extract from the related webpage the title tag (<title>) and meta description (<meta name="description" content="Some content">). If title tag and/or meta description tag isn't available on the webpage, the result will be empty. Setup Set a Base in Airtable with a table with the following structure: url (field type url), title tag (field type text string), meta desc (field type text field) Minimum suggested table structure is: url (https://example.com), title (Title example), meta desc* (This is the meta description of the example page) Connect Airtable to both Airtable nodes in the template and, with the following formula, get all the records that miss title tag and meta desc. Formula: AND(url != "", {title tag} = "", {meta desc} = "") Insert the url to be analyzed in the table in the field url and let the workflow do the rest. Extra You can also calculate the length for title tag and meta desc using formula field inside Airtable. This is the formula: LEN({title tag}) or LEN({meta desc}) You can automate the process calling a Webhook from Airtable. For this, you need an Airtable paid plan.
By Giacomo LanziFetch a YouTube playlist and send new items Raindrop
This simple workflow will fetch a YouTube playlist every n minutes and send the new items s to a collection in Raindrop. You can connect any application at the end of the flow. Make sure to authenticate to YouTube using Google Auth, and to Raindrop using an API. Update the Playlist ID and the Raindrop collection.
By Alejandro ARGenerate Instagram reels with Veo3 and GPT for AI-powered ad creation
🎬 Veo3 Instagram Reel Generator – AI-Powered Ad Creation in Minutes Description: This no-code workflow transforms your creative brief into an engaging Instagram Reel using OpenAI and Veo3 API (via Wavespeed) — fully automated in n8n. Just type a product, theme, or trend via chat, and get a short-form video plus caption delivered and logged, ready to post. Perfect for marketers, creators, and content teams looking to scale their ad content output without hiring editors or creative agencies. Watch step-by-step build video tutorial here: https://www.youtube.com/@Automatewithmarc ⚙️ How It Works: 💬 Chat Trigger Start by sending a message like “Create an ad for a minimalist perfume brand using the ‘quiet luxury’ trend.” 🧠 Prompt Engineer (ChatGPT) Generates a 5–8 second descriptive video prompt suitable for Veo3 based on your input — including visual tone, motion, and hook. 📡 API Call to Veo3 via Wavespeed Submits the prompt to create a short video (9:16 ratio, ~8 seconds), then polls for the final video URL. ✍️ Caption Generator (GPT) Creates an Instagram-friendly caption to pair with the video, using a playful, impactful writing style. 📄 Google Sheets Integration Logs each generated video prompt, final video URL, caption, and status into a Google Sheet for easy management and scheduling. 🔌 Tools & Integrations: OpenAI GPT (Prompt generation & caption copywriting) Veo3 via Wavespeed API (Video generation) Google Sheets (Content tracking and publishing queue) Telegram / Chat UI trigger (Optional – easily swappable) 💡 Use Cases: Instagram & TikTok ad generation Creative automation for digital agencies Short-form UGC testing at scale Trend-driven campaign ideation
By Automate With MarcParse Ycombinator news page
Extract data from a webpage (Ycombinator news page) and create a nice list using itemList node. It seems that current version in n8n (0.141.1) requires to extract each variable one by one. Hopefully in a futute it will be possible to create the table using just one itemList node. Another nice feature of the workflow is an automatically generated file name with the resulting table. Check out the "fileName" option of the Spreadsheet File node: "Ycombinatornews{{new Date().toISOString().split('T', 1)[0]}}.{{$parameter[\"fileFormat\"]}}" The resulting table is saved as .xls file and delivered via email
By EduardLead research report emails
Overview This workflow auto-generates a personalized research report on any prospect who books a call with you—using their LinkedIn profile and advanced web research. When a call is booked in your calendar, the system looks up the lead’s LinkedIn URL from a Google Sheets database. That profile is then scraped using Relevance AI to extract posts, experiences, and education. It also runs a deep-dive query on the person using Perplexity to uncover relevant news, insights, and context. This structured data is passed to an AI model that produces a clean profile summary, suggested pain points, and solution ideas. Finally, the system builds and sends you a fully formatted HTML report via email—ready to review before your meeting. Who’s it for Founders taking high-stakes sales calls SDRs/BDRs booking back-to-back meetings Agencies and consultants who want to personalize discovery calls Teams doing high-touch enterprise sales or B2B outreach How it works Triggered when a new call is booked via Cal.com Finds matching LinkedIn URL from a local database (Google Sheets) Scrapes public LinkedIn data via Relevance AI Runs a Perplexity query on the prospect for deeper context Formats the scraped data using Code nodes Sends structured info to AI to generate: A company + person profile Suggested pain points and solutions Formats everything into a clean HTML report Emails you the final summary to prep for the call Example use case > Someone books a call. You receive a report 2 minutes later in your inbox with: > - Their role, company, and latest posts > - What their business does > - Recent news and context from Perplexity > - Predicted pain points and how you might help > > You show up to the call prepped and ready How to set up Connect your Cal.com trigger (or replace with any booking tool) Set up your Google Sheet(s) with contact info + LinkedIn profiles Add Relevance AI API key and configure LinkedIn scraping (they have free credits) Link Perplexity API for web research Customize the AI prompts and report formatting Connect Gmail or preferred email provider to send reports Requirements Cal.com or other booking platform Google Sheets for lead storage Relevance AI account and API access Perplexity API key OpenAI or similar LLM for summarization Email integration (e.g. Gmail) How to customize Replace Cal.com with Calendly, SavvyCal, etc. Change AI prompt tone and structure of the report Add CRM push (e.g. log into HubSpot, Notion, or Airtable) Add Slack or Telegram notifications for call alerts Format reports as PDF instead of HTML for download
By Abdul MirCreate dynamic Twitter profile banner
This workflow updates your Twitter profile banner when you have a new follower. To use this workflow: Configure Header Auth in the Fetch New Followers to connect to your Twitter account. Update the URL of the template image in the Fetch BG node. Create and configure your Twitter OAuth 1.0 credentials in the last HTTP Request node. You can configure the size, and position of the avatar images in the Edit Image nodes. Check out this video to learn how to build it from scratch: How to automatically update your Twitter Profile Banner
By Harshil AgrawalBuild a RAG system with automatic citations using Qdrant, Gemini & OpenAI
This workflow implements a Retrieval-Augmented Generation (RAG) system that: Stores vectorized documents in Qdrant, Retrieves relevant content based on user input, Generates AI answers using Google Gemini, Automatically cites the document sources (from Google Drive). --- Workflow Steps Create Qdrant Collection A REST API node creates a new collection in Qdrant with specified vector size (1536) and cosine similarity. Load Files from Google Drive The workflow lists all files in a Google Drive folder, downloads them as plain text, and loops through each. Text Preprocessing & Embedding Documents are split into chunks (500 characters, with 50-character overlap). Embeddings are created using OpenAI embeddings (text-embedding-3-small assumed). Metadata (file name and ID) is attached to each chunk. Store in Qdrant All vectors, along with metadata, are inserted into the Qdrant collection. Chat Input & Retrieval When a chat message is received, the question is embedded and matched against Qdrant. Top 5 relevant document chunks are retrieved. A Gemini model is used to generate the answer based on those sources. Source Aggregation & Response File IDs and names are deduplicated. The AI response is combined with a list of cited documents (filenames). Final output: AI Response Sources: ["Document1", "Document2"] --- Main Advantages End-to-end Automation: From document ingestion to chat response generation, fully automated with no manual steps. Scalable Knowledge Base: Easy to expand by simply adding files to the Google Drive folder. Traceable Responses: Each answer includes its source files, increasing transparency and trustworthiness. Modular Design: Each step (embedding, storage, retrieval, response) is isolated and reusable. Multi-provider AI: Combines OpenAI (for embeddings) and Google Gemini (for chat), optimizing performance and flexibility. Secure & Customizable: Uses API credentials and configurable chunk size, collection name, etc. --- How It Works Document Processing & Vectorization The workflow retrieves documents from a specified Google Drive folder. Each file is downloaded, split into chunks (using a recursive text splitter), and converted into embeddings via OpenAI. The embeddings, along with metadata (file ID and name), are stored in a Qdrant vector database under the collection negozio-emporio-verde. Query Handling & Response Generation When a user submits a chat message, the workflow: Embeds the query using OpenAI. Retrieves the top 5 relevant document chunks from Qdrant. Uses Google Gemini to generate a response based on the retrieved context. Aggregates and deduplicates the source file names from the retrieved chunks. The final output includes both the AI-generated response and a list of source documents (e.g., Sources: ["FAQ.pdf", "Policy.txt"]). --- Set Up Steps Configure Qdrant Collection Replace QDRANTURL and COLLECTION in the "Create collection" HTTP node to initialize the Qdrant collection with: Vector size: 1536 (OpenAI embedding dimension). Distance metric: Cosine. Ensure the "Clear collection" node is configured to reset the collection if needed. Google Drive & OpenAI Integration Link the Google Drive node to the target folder (Test Negozio in this example). Verify OpenAI and Google Gemini API credentials are correctly set in their respective nodes. Metadata & Output Customization Adjust the "Aggregate" and "Response" nodes if additional metadata fields are needed. Modify the "Output" node to format the response (e.g., changing Sources: {{...}} to match your preferred style). Testing Trigger the workflow manually to test document ingestion. Use the chat interface to verify responses include accurate source attribution. Note: Replace placeholder values (e.g., QDRANTURL) with actual endpoints before deployment. --- Need help customizing? Contact me for consulting and support or add me on Linkedin.
By Davide📦 Electronic data interchange (EDI) message parsing with Gmail and Google Sheet
Tags: Supply Chain Management, Logistics, Transportation, Data Transmission Context Hey! I'm Samir , a Supply Chain Engineer and Data Scientist from Paris founder of LogiGreen Consulting We help small and medium businesses improve their logistics processes using AI, Data Analytics and Automation. > Sustainable and Efficient supply chains with N8N! 📬 For business inquiries, you can add me on Here What is an EDI Message? Electronic Data Interchange (EDI) is a standardized method of automatically transferring data between computer systems. They ensure the smooth flow of essential transactional data, such as purchase orders, invoices, shipping notices, and more. [](https://youtu.be/-phwXeYk7Es) For instance, a manufacturing company can receive purchase orders from a retailer via EDI. [](https://youtu.be/-phwXeYk7Es) However, they need complex integration for the transmission and processing of the messages. Who is this template for? This workflow template is designed for small companies that cannot connect to their customers and need to manually process the EDI messages received. How does it work? This workflow uses a Gmail Trigger that analyzes all the incoming emails. 📧 Gmail Trigger → Detects emails with "EDI" in the subject. 📜 Parses EDI Message → Uses a JavaScript Code Node to extract structured data. 📊 Formats the Data → Converts it into a table-friendly format. 📑 Updates Google Sheets → Automatically logs the processed orders. Prerequisite This workflow does not require any additional paying subscription. A Google Drive Account with a folder including a Google Sheet API Credentials: Google Drive API, Google Sheets API and Gmail API A Google sheet to store the shipment records. You do not need to prepare the columns. Next Steps Follow the sticky notes to set up the parameters inside each node and get ready to improve your logistics operations! 📺 Watch the Step-by-Step Guide [](https://youtu.be/-phwXeYk7Es) 🎥 Check My Tutorial 🚀 Interested in applications of N8N for Logistics & Supply Chain Management? Let's connect on Linkedin Notes This template includes an example of EDI message to test the workflow. If you want to learn more about Electronic Data Interchange: 🚚 Blog Article about Electronic Data Interchange (EDI) This workflow has been created with N8N 1.82.1 Submitted: March 19th, 2025
By Samir SaciCreate screenshots with uProc, save to Dropbox and send by email
Do you want to create a website screenshot without browser extensions? This workflow creates screenshots of any website using the uProc Get Screenshot by URL tool and sends an email with the screenshots. You need to add your credentials (Email and API Key - real -) located at Integration section to n8n. Node "Create Web + Email Item" can be replaced by any other supported service returning Website and Email values, like Google Sheets, Mailchimp, MySQL, or Typeform. Every "uProc" node returns an image URL of the captured website. This generated URL will remain only 24 hours in our server. You can set up the uProc node with several parameters: width: you can choose one of the predefined values to generate the screenshot, or you can set up a custom width you want. full-page: the tool will return a screenshot of the website from top to bottom with the defined width. In our workflow, we generate two screenshots: 1) One screenshot of 640 pixels width. 2) One full-page screenshot of 640 pixels width. Screenshots are downloaded by "Get File" nodes and saved to the screenshots folder in Dropbox. Finally, we use the Amazon SES node to send an HTML email with both screenshots to the specified email. We will receive the next email:
By Miquel Colomer