by David Olusola
🚀 Automated Lead Scraper Workflow (Apify + n8n + Google Sheets) 🧠 What It Does This n8n workflow automates the process of scraping leads using Apify, cleaning the extracted data, and exporting it to Google Sheets—ready for use in outreach, prospecting, or CRM pipelines. 🔄 Workflow Steps ✅ Start – Manually triggers the workflow. 🧩 Set Variables – Stores required Apify credentials: APIFY_TOKEN: Your Apify token. APIFY_TASK_ID: The Apify task to run. 🕸️ Run Apify Scraper – Launches the scraper and fetches the dataset. 🧹 Clean Data – Processes scraped results to: ✂️ Strip non-numeric characters from phone numbers. ✉️ Format emails (lowercase + trimmed). 📊 Export to Google Sheets – Appends clean data to your spreadsheet: 🏢 company name → from title 📞 phone → cleaned number 📍 address → from scraped info 🛠️ Requirements 🕷️ Apify Account A valid APIFY_TOKEN An existing Apify task (APIFY_TASK_ID) 📗 Google Sheets Access OAuth2 credentials set up in n8n (e.g., "Google Sheets account 2") 🚦 How to Use ⚙️ Open the Variables node and plug in your Apify credentials. 📄 Confirm the Google Sheets node points to your desired spreadsheet. ▶️ Run the workflow manually from the Start node. 📥 Output A ready-to-use sheet of cleaned lead data containing: Company names Phone numbers Addresses 💼 Perfect For: Sales teams doing outbound prospecting Marketers building lead lists Agencies running data aggregation tasks
by n8n Team
This workflow demonstrates how to export SQL to XML and present the data nicely formatted using an XSL Template. The upper part of the workflow starts with a webhook. Then it gets several random records from the SQL table and converts them into an XML string. Then a final XML file is created that contains a link to the XML Stylesheet file. The lower part of the workflow contains a helper Webhook that reads an XSL Template from the GitHub gist and serves it back via the Respond to Webhook node. This is required to comply with the CORS rules of modern browsers. These rules dictate that both XML data and a stylesheet file should come from the same domain.
by Yaron Been
Bytedance Seededit 3.0 Image Generator Description Text-guided image editing model that preserves original details while making targeted modifications like lighting changes, object removal, and style conversion Overview This n8n workflow integrates with the Replicate API to use the bytedance/seededit-3.0 model. This powerful AI model can generate high-quality image content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters prompt** (string): Text prompt for image generation image** (string): Input image to edit Optional Parameters seed** (integer, default: None): Random seed. Set for reproducible generation guidance_scale** (number, default: 5.5): Prompt adherence. Higher = more literal. How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate image content Access the generated output from the final node API Reference Model: bytedance/seededit-3.0 API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of image generation parameters
by Yaron Been
Description This workflow automatically generates comprehensive property market reports by scraping real estate listings and market data from multiple sources. It helps real estate professionals save time and provide data-driven insights to clients without manual research. Overview This workflow automatically generates property market reports by scraping real estate listings and market data. It uses Bright Data to access multiple real estate websites and compiles the data into comprehensive reports. Tools Used n8n:** The automation platform that orchestrates the workflow. Bright Data:** For scraping real estate websites and property data without getting blocked. Spreadsheets/Databases:** For storing and analyzing property data. Document Generation:** For creating professional PDF reports. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Configure Bright Data: Add your Bright Data credentials to the Bright Data node. Set Up Data Storage: Configure where you want to store the property data. Customize: Specify locations, property types, and report format. Use Cases Real Estate Agents:** Generate market reports for clients. Property Investors:** Track market trends in target areas. Market Analysts:** Automate data collection for property market analysis. Connect with Me Website:** https://www.nofluff.online YouTube:** https://www.youtube.com/@YaronBeen/videos LinkedIn:** https://www.linkedin.com/in/yaronbeen/ Get Bright Data:** https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #realestate #propertymarket #brightdata #marketreports #propertyanalysis #realestatedata #markettrends #propertyinvestment #n8nworkflow #workflow #nocode #realestateanalysis #propertyreports #realestateintelligence #marketresearch #propertyscraping #realestateautomation #investmentanalysis #propertytrends #datadriven #realestatetech #propertyinsights #marketanalysis #realestateinvesting
by Lucas Walter
Who's it for This template is perfect for sales professionals, marketers, and business developers who need to quickly gather contact information from company websites. Whether you're building prospect lists, researching potential partners, or collecting leads for outreach campaigns, this automation saves hours of manual email hunting. What it does This workflow automatically discovers and extracts email addresses from any website by: Taking a website URL as input through a simple form Using Firecrawl's mapping API to find relevant pages (about, contact, team pages) Batch scraping those pages to extract email addresses Intelligently handling common email obfuscations like "(at)" and "(dot)" Returning a clean, deduplicated list of valid email addresses The automation handles rate limiting, retries failed requests, and filters out invalid or hidden email addresses to ensure you get quality results. How to set up Get Firecrawl API access: Sign up at firecrawl.dev and obtain your API key Configure credentials: In n8n, create a new HTTP Header Auth credential named "Firecrawl" with: Header Name: Authorization Header Value: Bearer YOUR_API_KEY Import the workflow: Copy the workflow JSON into your n8n instance Test the form: Activate the workflow and test with a sample website URL How to customize the workflow Search parameters: Modify the search parameter in the map_website node to target different page types (currently searches for "about contact company authors team") Extraction limits: Adjust the limit parameter to scrape more or fewer pages per website Retry logic: The workflow includes retry logic with a 12-attempt limit - modify the check_retry_count node to change this Output format: The set_result node formats the final output - customize this to match your preferred data structure Email validation: The JSON schema in start_batch_scrape defines how emails are extracted - modify the prompt or schema for different extraction rules The workflow is designed to be reliable and handle common edge cases like rate limiting and failed requests, making it production-ready for regular use.
by Yaron Been
Ndreca Hunyuan3d 2 Test AI Generator Description None Overview This n8n workflow integrates with the Replicate API to use the ndreca/hunyuan3d-2-test model. This powerful AI model can generate high-quality other content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters image** (string): Input image for generating 3D shape Optional Parameters seed** (integer, default: 1234): Random seed for generation steps** (integer, default: 50): Number of inference steps num_chunks** (integer, default: 200000): Number of chunks for mesh generation max_facenum** (integer, default: 40000): Maximum number of faces for mesh generation guidance_scale** (number, default: 5.5): Guidance scale for generation octree_resolution** (string, default: 512): Octree resolution for mesh generation remove_background** (boolean, default: True): Whether to remove background from input image How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate other content Access the generated output from the final node API Reference Model: ndreca/hunyuan3d-2-test API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of other generation parameters
by n8n Team
This workflow imports multiple CSV files and appends or updates them to a Google Sheets document. Here's a step-by-step breakdown: When clicked "Execute Workflow", the process starts. The "Read Binary Files" node reads all the '.csv' files from the specified directory. The files are then split into batches (one file in a batch) by the "Split In Batches" node. For each file, the "Read CSV" node reads the data from the CSV file. The "Assign source file name" node assigns the source file name to the data. The data is then processed by the "Remove duplicates" node. This removes any duplicate entries based on the 'user_name' field. The "Keep only subscribers" node filters the data to keep only those entries where the 'subscribed' field is set to 'TRUE'. The data is then sorted by the 'date_subscribed' field using the "Sort by date" node. Finally, the processed data is appended or updated to a specified Google Sheets document using the "Upload to spreadsheet" node. It checks for the 'user_name' field, if the data corresponding to that 'user_name' already exists, it updates the data, otherwise appends the new data.
by Yaron Been
Google Veo 3 Fast Video Generator Description A faster and cheaper version of Google’s Veo 3 video model, with audio Overview This n8n workflow integrates with the Replicate API to use the google/veo-3-fast model. This powerful AI model can generate high-quality video content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters prompt** (string): Text prompt for video generation Optional Parameters seed** (integer, default: None): Random seed. Omit for random generations resolution** (string, default: 720p): Resolution of the generated video negative_prompt** (string, default: None): Description of what to discourage in the generated video How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate video content Access the generated output from the final node API Reference Model: google/veo-3-fast API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of video generation parameters
by Strategiflows
Who Is This For? E-commerce managers, data analysts, and n8n beginners who need a hands-off way to pull all Shopify orders—even stores with thousands of orders—into Google Sheets for reporting or BI. What Problem Does It Solve? Shopify’s GraphQL API only returns up to 250 orders per call, forcing you to manually manage cursors and loops. This template handles the “get next 250” logic for you, so you never miss an order. What This Workflow Does Schedule Trigger – Runs at your chosen cadence (daily, hourly, or manual). Set Date Range – Defines startDay and endDay based on $now. GraphQL Loop – Fetches orders 250 at a time, using pageInfo.hasNextPage and endCursor until complete. Code Node – Flattens orders into line-item rows and summarizes by SKU/vendor. Google Sheets – Appends results to your sheet for easy analysis.
by Viktor Klepikovskyi
Base64 Encode Multiple Binary Files with a Code Node This template demonstrates how to handle multiple binary files in n8n by using a Code node to convert them into a Base64 encoded string. It's particularly useful when an API requires file uploads in this format and the standard 'Extract From File' node is not sufficient for batch processing. The workflow starts by downloading a ZIP file, unzipping it to get multiple binary files, and then uses a Code node with custom JavaScript to encode each file individually. Instructions Download and import this template into your n8n instance. Run the workflow once to see how it downloads, unzips, and then encodes multiple files. Modify the 'HTTP Request' node to download your own binary file or a ZIP file containing multiple files. Update the 'Code' node if you need to adjust the output format or file paths. Use the output of the 'Code' node in a subsequent node, such as another 'HTTP Request' to send the Base64-encoded files to your desired API. A link to the full blog post is available here
by Clown Mutiny
What It Does The Chef Agent is your AI-powered kitchen companion—ready to turn leftover ingredients into meal inspiration. It's a simple, fun n8n automation that: Accepts a list of ingredients via webhook Uses Ollama AI to suggest 5 creative recipes or food ideas Recommends up to 3 missing ingredients to improve the dish Returns a fallback message if the AI is unavailable Includes setup notes for beginners Requirements An active n8n instance (local or hosted) Ollama AI running locally (or another LLM via HTTP request) A webhook endpoint (defaults to /lets-cook) Why You’ll Love It Fully customizable for your use case or favorite LLM Great intro to AI + workflow automation Comes with playful Clown Mutiny flair: > “Powered by Clown Mutiny’s taste-bud liberation division.” Installation Import the provided JSON template into your n8n workspace. Configure your AI node to match your local Ollama instance. Trigger the flow by sending a POST request to the webhook: { "ingredients": "eggs, rice, spinach" }
by Yaron Been
Wan Video Wan 2.2 I2v A14b Video Generator Description Image-to-video at 720p and 480p with Wan 2.2 A14B Overview This n8n workflow integrates with the Replicate API to use the wan-video/wan-2.2-i2v-a14b model. This powerful AI model can generate high-quality video content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters prompt** (string): Prompt for video generation image** (string): Input image to generate video from Optional Parameters seed** (integer, default: None): Random seed. Leave blank for random num_frames** (integer, default: 81): Number of video frames. 81 frames give the best results resolution** (string, default: 480p): Resolution of video. 832x480px corresponds to 16:9 aspect ratio, and 480x832px is 9:16 sample_shift** (number, default: 5): Sample shift factor sample_steps** (integer, default: 30): Number of generation steps. Fewer steps means faster generation, at the expensive of output quality. 30 steps is sufficient for most prompts frames_per_second** (integer, default: 16): Frames per second. Note that the pricing of this model is based on the video duration at 16 fps How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate video content Access the generated output from the final node API Reference Model: wan-video/wan-2.2-i2v-a14b API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of video generation parameters