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 SpaGreen Creative
WhatsApp Bulk Message Broadcast via Google Sheets (n8n Workflow) Use Case This workflow enables automated bulk WhatsApp message broadcasting using the WhatsApp Business Cloud API. It pulls recipient and message data from a Google Sheet, sends templated messages (optionally with image headers), and updates the sheet with the message status. It is ideal for marketing teams, support agents, and businesses handling high-volume outreach. Who Is This For? Businesses conducting WhatsApp marketing or outreach campaigns Customer support or notification teams Administrators seeking an automated, no-code message distribution system using Google Sheets What This Workflow Does Triggers automatically every minute to scan for pending messages Fetches unsent entries from a Google Sheet Limits the number of messages processed per execution to comply with API usage guidelines Sanitizes WhatsApp numbers for proper formatting Sends messages using a pre-approved WhatsApp template (text and optional image) Marks the row as "Sent" in the sheet upon successful delivery Workflow Breakdown (Node by Node) 1. Trigger Every 5 Minutes Initiates the workflow every minute using a scheduled trigger to continuously monitor pending rows. 2. Fetch All Pending Queries for Messaging Reads rows from a Google Sheet where the Status column is empty, indicating they havenโt been processed yet. 3. Limit Restricts processing to 2 rows per execution to manage API throughput. 4. Loop Over Items Uses SplitInBatches to iterate through each row individually. 5. Clean WhatsApp Number A code node that strips non-numeric characters from the WhatsApp No field, ensuring the format is valid for the API. 6. Send Message to 300 Phone No Sends a WhatsApp message using the WhatsApp Cloud API and a pre-approved template. Template includes: An image from the Image URL column (as header, optional) Dynamic variables for the recipient's Name and Message fields Template variables must be pre-defined and approved in the Meta Developer Portal, such as {{1}}, {{2}}. 7. Change State of Rows in Sent1 Updates the Status column to Sent for each successfully processed row using the row number as a reference. Google Sheet Format Structure your Google Sheet as shown below: | WhatsApp No | Name | Message | Image URL | Status | |--------------|------------|---------------------------|---------------------|--------| | +8801XXXXXXX | John Doe | Hello, your order shipped | https://.../img.jpg | | Leave the Status column empty for rows that need to be processed. Requirements WhatsApp Business Cloud API access via Meta for Developers A properly structured Google Sheet as described above Active OAuth2 credentials configured in n8n for: googleSheetsOAuth2Api whatsAppApi Customization Options Update the Limit node to control how many rows are processed in each run Adjust the trigger schedule (e.g., change to every 5 minutes) Replace the message template ID with your own custom-approved one from Meta Add error-handling logic (e.g., IF or Try/Catch nodes) to log failures or set Status = Failed Sample Sheet Template View Sample Google Sheet Workflow Highlights Automated execution every 1 minute Reads and processes only pending records Verifies WhatsApp numbers and delivers templated messages Updates Google Sheet after each attempt Support & Community Need help setting up or customizing the workflow? WhatsApp: Contact Support Discord: Join SpaGreen Server Facebook Group: SpaGreen Community Website: Visit SpaGreen Creative
by Itamar
๐ง ICP Scoring Agent (n8n + Explorium + LLM) This workflow automates Ideal Customer Profile (ICP) scoring for any company using a combination of Explorium data and an LLM-driven evaluation framework. ๐ง How It Works Input: Company name is submitted via form. Data Enrichment: Explorium's MCP Server is used to fetch firmographic, hiring, and tech data about the company. Scoring Logic: An AI agent (LLM) applies a 3-pillar framework to assess and score the company. Output: A structured JSON or Google Doc summary is generated using the AgentGeeks formatter. ๐ Scoring System (100 points total) | Pillar | Max Points | |------------------------------|------------| | Strategic Fit | 40 | | AI / Tech Readiness | 40 | | Engagement & Reachability | 20 | ๐ง Scoring Criteria Strategic Fit**: Industry, size, use case, buyer roles Tech Readiness**: AI maturity, hiring trends, stack visibility Reachability**: Geography, contactability, data quality ๐ฏ Verdict Scale ๐ฉ 90โ100: Ideal ICP โ 70โ89: Good Fit ๐จ 40โ69: Medium Fit โ < 40: Poor Fit ๐ฆ Workflow Components Trigger**: Form submission via webhook MCP Client**: Pulls enriched company data via Explorium's MCP API AI Agent**: Uses Anthropic Claude (or other LLM) to calculate scores Output**: Results are posted to a structured endpoint (e.g. Google Doc or JSON API) ๐งฐ Dependencies n8n (self-hosted or cloud) Explorium MCP credentials and access LLM API (e.g., Anthropic Claude, OpenAI, etc.) Optional: AgentGeeks formatter or similar doc generator ๐ผ Use Case This ICP scoring system is designed for GTM and sales teams to: Automate lead prioritization Qualify accounts before outbounding Sync ICP data into CRMs, routing systems, or reporting layers ๐ Example Output in Google Doc { "company": "Acme Inc.", "score": 87, "verdict": "Good Fit", "pillars": { "strategic_fit": 35, "tech_readiness": 37, "reachability": 15 }, "summary": "Acme Inc. is a mid-sized SaaS company with strong AI hiring activity and a buyer profile aligned to enterprise IT. Moderate reachability via firmographic signals." }
by Yang
This workflow helps digital marketers and outreach specialists automate the research and creation of cold email icebreakers for local businesses. What it does: Starts with a Form Trigger, where you input a search keyword (e.g., โDentist in New Yorkโ). Uses Dumpling AIโs Google Maps API to search for local businesses matching the keyword. Extracts individual business data, including website URLs. Sends each website to Dumpling AI to extract: A website summary for personalization An email address (if available) Sends the summary and business info to GPT-4 via OpenAI to write a short, warm, and customized icebreaker message. Filters out results with missing email addresses. Logs the business name, email, website, phone number, website summary, and generated icebreaker into Google Sheets. Optionally pushes the lead and personalization to Instantly.ai for automated cold outreach. Tools Used: Form Trigger (n8n) Dumpling AI (Search & Extraction APIs) OpenAI GPT-4 (via LangChain Node) Google Sheets Instantly.ai (optional lead delivery) ๐ ๏ธ How to Customize the Workflow Change the search region or business type:* Adjust the default keyword in the *Form Trigger** or connect a different input source (like Google Sheets). Customize the prompt:* Modify the *GPT-4 node prompt** to match your agency tone or outreach style. Add or remove data fields:* Edit the *Google Sheets node** to store additional business data or remove unnecessary ones. Connect to your CRM or outreach tool:* Replace or extend the *Instantly API node** with your own CRM (e.g., HubSpot, Close, Pipedrive) using HTTP Request or native integrations. Control batching size:* The *Split In Batches node** is set to 2 by default. You can increase this to speed up processing or reduce it to avoid rate limits. This automation is ideal for sales teams, digital marketing freelancers, and agencies who want to scale lead generation while keeping emails personal and relevant.
by Belmont Digital
Description This n8n workflow verifies the deliverability of mailing addresses stored in Keap/Infusionsoft by integrating with Lobโs address verification service. Who is this for? This template is designed for Keap/Infusionsoft users who need to ensure the accuracy of mailing addresses stored in their CRM systems. What problem is this workflow solving? / Use Case This workflow addresses the challenge of maintaining accurate mailing addresses in CRM databases by verifying the deliverability of addresses. What this workflow does A new contact is created in Keap/Infusionsoft Webhook sent to n8n Verify if the address is deliverable via LOB Report back to Keap/Infusionsoft Set Up Steps Watch this setup video: https://www.youtube.com/watch?v=T7Baopubc-0 Takes 10-30 minutes to set up Accounts Needed: Keap/Infusionsoft LOB Account (https://www.lob.com $0.00/mo 300 US addresses Verifications) n8n Before using this template, ensure you have API keys for your Keap/Infusionsoft app and Lob. Set up authentication for both services within n8n. How to customize this workflow to your needs You can customize this workflow by adjusting the trigger settings to match Keap/Infusionsoftโs workflow configuration. Additionally, you can modify the actions taken based on the deliverability outcome, such as updating custom fields or sending notifications.
by Friedemann Schuetz
Welcome to my Automated Image Metadata Tagging Workflow! This workflow automatically analyzes the image content with the help of AI and writes it directly back into the image file as keywords. This workflow has the following sequence: Google Drive trigger (scan for new files added in a specific folder) Download the added image file Analyse the content of the image and extract the file as Base64 code Merge Metadata and Base64 Code Code Node to write the Keywords into the Metadata (dc:subject) Convert to file and update the original file in the Google Drive folder The following accesses are required for the workflow: Google Drive: Documentation AI API access (e.g. via OpenAI, Anthropic, Google or Ollama) You can contact me via LinkedIn, if you have any questions: https://www.linkedin.com/in/friedemann-schuetz
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
๐ Automated Lead Scraper Workflow (Apify + n8n + Google Sheets) ๐ง What It Does This n8n workflow automates the process of scraping leads using Apify, cleaning the extracted data, and exporting it to Google Sheetsโready for use in outreach, prospecting, or CRM pipelines. ๐ Workflow Steps โ Start โ Manually triggers the workflow. ๐งฉ Set Variables โ Stores required Apify credentials: APIFY_TOKEN: Your Apify token. APIFY_TASK_ID: The Apify task to run. ๐ธ๏ธ Run Apify Scraper โ Launches the scraper and fetches the dataset. ๐งน Clean Data โ Processes scraped results to: โ๏ธ Strip non-numeric characters from phone numbers. โ๏ธ Format emails (lowercase + trimmed). ๐ Export to Google Sheets โ Appends clean data to your spreadsheet: ๐ข company name โ from title ๐ phone โ cleaned number ๐ address โ from scraped info ๐ ๏ธ Requirements ๐ท๏ธ Apify Account A valid APIFY_TOKEN An existing Apify task (APIFY_TASK_ID) ๐ Google Sheets Access OAuth2 credentials set up in n8n (e.g., "Google Sheets account 2") ๐ฆ How to Use โ๏ธ Open the Variables node and plug in your Apify credentials. ๐ Confirm the Google Sheets node points to your desired spreadsheet. โถ๏ธ Run the workflow manually from the Start node. ๐ฅ Output A ready-to-use sheet of cleaned lead data containing: Company names Phone numbers Addresses ๐ผ 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 Jonathan | NEX
Stop manually checking suspicious links. This free n8n workflow provides the foundation for a powerful, automated URL analysis pipeline. Using the NixGuard AI engine, you can instantly analyze suspicious URLs from emails, logs, or tickets to uncover phishing attempts, malware hosting sites, and malicious redirects. What You Will Automate: ๐ค Instant Threat Triage: Get an immediate AI-powered summary of why a URL is malicious, saving you critical investigation time. ๐ฏ Actionable IOC Extraction: Automatically extract the final redirected URL, malicious domains, and IPs to fuel your threat hunting and blocking rules. ๐ SOAR-Ready Foundation: This workflow is the perfect starting point for your security playbooks. Use the output to: Alert: Send instant notifications to Slack or Teams. Respond: Create tickets in Jira or TheHive. Block: Add malicious domains to your firewall or DNS filter. Download this free template and automate your first line of defense against web-based threats in minutes! Don't have the main workflow yet? Get it HERE! ๐ Learn more about NixGuard: thenex.world ๐ Get started with a free security subscription: thenex.world/security/subscribe For search: URL Scanning, Phishing, Threat Intelligence, SOAR, SOC Automation, NixGuard, Free, AI, Incident Response, Cybersecurity, Automation, Link Analysis, MTTR, Malware, VirusTotal
by n8n Team
This workflow is designed for dynamic and intelligent conversational capabilities. It incorporates OpenAI's GPT-4o model for natural language understanding and generation. Additional tools include SerpAPI and Wikipedia for enriched, data-driven responses. The workflow is triggered manually, and utilizes a 'Window Buffer Memory' to maintain the context of the last 20 interactions for better conversational continuity. All these components are orchestrated through n8n nodes, ensuring seamless interconnectivity. To use this template, you need to be on n8n version 1.50.0 or later.