by Lorena
This workflow allows you to collect tweets, store them in MongoDB, analyse their sentiment, insert them into a Postgres database, and post positive tweets in a Slack channel. Cron node: Schedule the workflow to run every day Twitter node: Collect tweets MongoDB node: Insert the collected tweets in MongoDB Google Cloud Natural Language node: Analyse the sentiment of the collected tweets Set node: Extract the sentiment score and magnitude Postgres node: Insert the tweets and their sentiment score and magnitude in a Posgres database IF node: Filter tweets with positive and negative sentiment scores Slack node: Post tweets with a positive sentiment score in a Slack channel NoOp node: Ignore tweets with a negative sentiment score
by Tom
This workflow builds a valid RSS feed (which is an XML feed under the hood) for ARD Audiothek podcasts. This allows you to subscribe to such podcasts using your favourite podcatcher without using the ARD Audiothek app. The example builds a feed for Kalk & Welk, but the workflow can be easily adjusted by providing another podcast URL on the Get overview page HTTP Request node. To subscribe to the feed, active your n8n workflow and then use the Production URL from the intitial Feed Webhook node in your podcatcher. I've tested the resulting feed using Pocket Casts... ...and Miniflux: When using Miniflux, you can add your feed via this page to your account. Make sure you select Private when doing so to avoid sharing your n8n instance with the world. The resulting feed passes the W3C Feed Validation Service: The workflow can also be used as a foundation to free other podcasts from propriertary big media platforms, though not all of them will be as simple to deal with as the ARD Audiothek.
by PiAPI
What this workflow does? This workflow primarily uses the GPT-4o API from PiAPI and automatically creates front/side/top views of 3D models from commands. Who is this for? 3D Designers: Quickly generate standardized orthographic views for design review E-commerce Operators: Create multi-angle product display images 3D Modeling Beginners: Instantly produce basic reference views Step-by-step Instruction Fill in X-API-Key of your PiAPI account and the image prompt based on your inspiration. Click Test workflow. Get the image url in the final node. OutPut
by Sascha
Campaign tracking is pivotal; it enables marketers to evaluate the efficacy of various strategies and channels. UTM parameters are particularly essential as they provide granular details about the source, medium, and campaign effectiveness. However, when this data is not automatically integrated into a centralized system, it can become a tedious and error-prone process to manually collate and analyze it. Retrieving UTM data from Shopify and storing it in Baserow enables oy to do more with this data. For example you could build a campaign database in Baserow and automatically add campaign revenue to it using this workflow template. This template will help you: Automatically retrieve UTM parameters from Shopify orders using the Shopify Admin API Process marketing data through n8n Store this data into Baserow, providing you with a dynamic, responsive base for campaign tracking and decision-making This template will demonstrate the follwing concepts in n8n: use the Schedule trigger node use the GraphQL node to call the Shopify Admin API split larger incoming datasets into n8n items with the Split node transform the data structure with the Set node control flow with the If node store data in Baserow with the Baserow node How to get started? Create a custom app in Shopify get the credentials needed to connect n8n to Shopify This is needed for the Shopify Trigger Create Shopify Acces Token API credentials n n8n for the Shopify trigger node Create Header Auth credentials: Use X-Shopify-Access-Token as the name and the Acces-Token from the Shopify App you created as the value. The Header Auth is neccessary for the GraphQL nodes. You will need a running Baserow instance for this. You can also sign up for a free account at https://baserow.io/ Please make sure to read the notes in the template. For a detailed explanation please check the corresponding video: https://youtu.be/VBeN-3129RM
by Harshil Agrawal
This workflow allows you to add articles to a Notion reading list by accessing a Discord slash command. Prerequisites A Notion account and credentials, and a reading list similar to this template. A Discord account and credentials, and Discord Slash Command connected to n8n. Nodes Webhook node triggers the workflow whenever the Discord Slash command is issued. IF node checks the type returned by Discord. If the type is not equal to 1, it will return true, otherwise false. HTTP Request node makes an HTTP call to the link and gets the HTML of the webpage. HTML Extract node extracts the title from the HTML which we will use in the next node. Notion node adds the link to your Notion reading list. Set nodes set the reply values for Discord and register the Interaction Endpoint URL.
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 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