Workflow Templates

Define Your ICP from Customer LinkedIn Profiles Use Case This automation helps marketing and sales teams define their Ideal Customer Profile (ICP) using real LinkedIn profiles of current high-fit customers. By enriching and analyzing profile data, it generates a clear ICP definition and scoring methodology for future targeting. What This Automation Does This automation analyzes LinkedIn profiles of your existing customers and produces: A structured ICP definition A scoring model to evaluate future prospects A Google Boolean search string to find similar prospects Input: LinkedIn profile URLs of existing high-fit customers (e.g., https://www.linkedin.com/in/amirashkenazi/) Output: A Google Doc containing the ICP analysis and scoring methodology How It Works Trigger: Waits for a chat message containing one or more LinkedIn profile URLs. AI Agent: Parses and processes the URLs. Airtop Data Enrichment: Uses Airtop to extract structured information from each LinkedIn profile (e.g., job title, company, experience, skills). Memory: Maintains state between inputs for consistent analysis. LLM Analysis: Uses Claude 3.7 Sonnet to synthesize enriched data into a meaningful ICP. Google Docs: Automatically creates a new doc with a timestamped title and appends the ICP definition. Setup Requirements Airtop Profile connected to LinkedIn, Insert the profile name in the Airtop Tool Airtop API credentials. Get it free here If you choose to activate saving the profiles in Google Docs you will need OAuth2 credentials (or just copy the ICP definition from the chat) Next Steps Use the ICP for Scoring**: Feed new LinkedIn profiles through the same Airtop enrichment and use the scoring function to evaluate fit. Automate Target Discovery**: Plug the Boolean search output into LinkedIn, Google, or People Data Labs for ICP-matching lead generation. Refine Continuously**: Repeat the workflow as your customer base grows or segments evolve. Read more about how to Define ICP from Customer Examples

Automated system to track and analyze technology stacks used by target companies, helping identify decision-makers and technology trends. 🚀 What It Does Tracks technology stack of target companies Identifies key decision-makers (CTOs, Tech Leads) Monitors technology changes and updates Provides competitive intelligence Generates actionable insights 🎯 Perfect For B2B SaaS companies Technology vendors Sales and business development teams Competitive intelligence analysts Market researchers ⚙️ Key Benefits ✅ Identify potential customers ✅ Stay ahead of technology trends ✅ Target decision-makers effectively ✅ Monitor competitor technology stacks ✅ Data-driven sales strategies 🔧 What You Need BuiltWith API key n8n instance CRM integration (optional) Email/Slack for alerts 📊 Data Tracked Company technologies Hosting providers Frameworks and libraries Analytics tools Marketing technologies 🛠️ Setup & Support Quick Setup Deploy in 20 minutes with our step-by-step guide 📺 Watch Tutorial 💼 Get Expert Support 📧 Direct Help Gain a competitive edge by understanding the technology landscape of your target market.

This workflow sends an automatic daily summary of your Microsoft Outlook calendar events into a Microsoft Teams channel. Perfect for team visibility or personal reminders. This automation is ideal for team leads, project managers, and remote workers who need to keep stakeholders informed of scheduled events without manual effort. It saves time, ensures consistent communication, and reduces the chance of missing important meetings. How it works Scheduled Trigger The workflow runs automatically every midnight (00:00 UTC). Create filter for "TODAY" value (Code Node) The code node generates the date value for "today" Calculates UTC start and end of the current day Builds a Microsoft Graph-compatible filter string Microsoft Outlook Node: Get Today’s Events Resource : Event Operation : Get Many Uses {{ $json.filter }}, which is generated from today's date, to retrieve only relevant entries Format Events as HTML (Code Node) Code node transforms each event into a formatted HTML message Meeting Time: 2025-07-08T10:00:00Z Subject: Weekly Sync Summary: Discuss project milestones and blockers. Microsoft Teams Node: Send Summary Message Chat Message | Create | Selected Channel | HTML content Uses the htmlMessage field from the previous node as the message body How to Use Import the Workflow Load the .json file into your n8n instance via “Import from File” or directly via the workflow UI. Set Up Credentials Go to Credentials in n8n. Add or configure your Microsoft Outlook OAuth2 API credential. Add or configure your Microsoft Teams OAuth2 API credential. Assign these credentials to the corresponding nodes in the workflow. Adjust Timezone and Schedule Edit the Schedule Trigger node to reflect your local timezone or preferred time. Configure the Microsoft Outlook Node Ensure the correct Outlook calendar is targeted. Confirm the Get Many node includes this expression in the filter field: {{ $json.filter }} Customize the HTML Output (Optional) Open the “Format Events” Code node to: Add new fields like Location, Organizer, or Attendees. Adjust date formatting to local time if needed. Target the Correct Teams Channel Open the Microsoft Teams node, select the team and channel where messages should be posted. Message type must be set to HTML if sending formatted content. Test the Workflow Run it manually to verify: Events are fetched correctly. The message is well-formatted and appears in the correct Teams channel. If you see no events, double-check the date filter logic or ensure events exist for today. Example Use Cases Team Syncs**: Automatically notify your project channel every morning with today's meetings. Remote Work**: Help remote teams stay aligned on shared calendars. Personal Assistant**: Keep track of your own day’s agenda with an automatic Teams message. Requirements Microsoft Outlook** Account must have permission to access calendar events via Graph API. OAuth2 credential must be configured in n8n Credential Manager. Microsoft Teams** Requires permission to post messages to specific channels. OAuth2 credential must be configured and authorized.

This workflow syncs Shopify customers to your HubSpot account as contacts. Whenever somebody makes a purchase on Shopify, it automatically adds them as a new customer to your Hubspot account if the customer doesn’t exist yet. Also, this workflow creates or updates contacts from new paid orders on Shopify by adding the amount and order close date of the deal. Prerequisites Shopify account and Shopify credentials HubSpot account and HubSpot credentials How it works Shopify trigger starts the workflow whenever an order is updated. HubSpot node creates or updates the contact who made the order update. Set node sorts and passes only the userid. Merge node merges data of both inputs, the order and the customer. Hubspot node looks up if the order already exists. If node splits the workflow conditionally, based on data received. If the order is new, the new deal is created in the Hubspot node.

Who is this for? Sales professionals looking to build lead lists from target company domains Business development teams conducting outreach campaigns Marketers building contact databases for account-based marketing Recruiters searching for potential candidates at specific companies Anyone needing to transform a list of company domains into actionable contact information What problem is this workflow solving? Finding business email addresses for outreach is a time-consuming process. The Apollo API doesn't provide a direct way to extract email contacts from domains in a single call. This workflow bridges that gap by: Automating the two-step process required by Apollo's API Processing multiple domains in batches without manual intervention Extracting, enriching, and storing contact information in a structured format Eliminating hours of manual data entry and API interaction What this workflow does This workflow creates an automated pipeline between Google Sheets and Apollo's API to: Pull a list of target domains from a Google Sheet Submit each domain to Apollo's search API to find associated people Loop through each person found and enrich their profile data Extract key information: name, title, email address, and LinkedIn URL Write the enriched contact information back to a results sheet Process the next domain automatically until all are complete Setup Prerequisites: An n8n instance (cloud or self-hosted) Apollo.io account with API access Google account with access to Google Sheets Google Sheets Setup: Create a new Google Sheet with two tabs: Tab 1: "Target Domains" with a column named "Domain To Enrich" Tab 2: "Results" with columns: Company, First Name, Last Name, Title, Email, LinkedIn n8n Setup: Import the workflow JSON into your n8n instance Set up Google Sheets credentials in n8n Update the Google Sheets document ID in both Google Sheets nodes Add your Apollo API key to both HTTP Request nodes Review and adjust API rate limits if needed Testing: Add a few test domains to your "Target Domains" sheet Run the workflow manually to verify it's working correctly Check the "Results" sheet to confirm data is being properly populated How to customize this workflow to your needs Adding More Contact Fields: Modify the "Clean Up" node to extract additional fields from the Apollo API response Add corresponding columns to your "Results" sheet Update the "Results To Results Sheet" node mapping to include the new fields Filtering Results: Add a Filter node after "Clean Up" to include only contacts with specific roles Create conditions based on title, seniority, or other fields returned by Apollo Automating Workflow Execution: Replace the manual trigger with a Schedule Trigger to run daily/weekly Add a Filter node to process only domains with "Not Processed" status Update the status field in Google Sheets after processing Additional Notes This workflow respects Apollo's API rate limits by processing one contact at a time The Apollo API may not return contact information for all domains or all employees Consider legal and privacy implications when collecting and storing contact information Made with ❤️ by Hueston

Scoring LinkedIn Profiles Against Your ICP Use Case This automation scores individual LinkedIn profiles against your Ideal Customer Profile (ICP) based on interest in AI, technical depth, and seniority level. It's ideal for prioritizing leads and understanding how well a person fits your ICP criteria. What This Automation Does Given a LinkedIn profile and an Airtop profile, it: Extracts relevant data from the person's profile Determines levels of AI interest, seniority, and technical depth Calculates an ICP score based on weighted criteria Returns the full enriched profile with the score Input parameters: LinkedIn Profile URL** (e.g., https://linkedin.com/in/janedoe) Airtop Profile** connected to LinkedIn ICP scoring method** in the Airtop node prompt Output fields in JSON format: Full name, job title, employer, company LinkedIn URL, location, number of connections and followers, about section content and more Calculated ICP Score (out of 100) How It Works Form Trigger or Workflow Trigger: Accepts input from either a form or another workflow. Parameter Assignment: Ensures proper variable names for downstream nodes. Airtop Enrichment Tool: Extracts and scores the person based on a detailed prompt. Scoring: Uses this point system: AI Interest: beginner (5), intermediate (10), advanced (25), expert (35) Technical Depth: basic (5), intermediate (15), advanced (25), expert (35) Seniority Level: junior (5), mid-level (15), senior (25), executive (30) Output Formatting: Cleans and returns the result as JSON. Setup Requirements IMPORTANT: Enter your ICP scoring method in the prompt field of the Airtop node Airtop Profile connected to LinkedIn. Airtop API credentials configured in n8n. Optional: a front-end form to collect profile URLs and trigger the automation. Next Steps Embed in CRM**: Trigger this automation on new leads to auto-score them. Batch Process Leads**: Run it over a list of profile URLs for segmentation. Customize Scoring**: Adjust point weights based on your sales priorities. Read more about Scoring LinkedIn Profiles Against Your ICP

This workflow enriches new accounts in Pipedrive using Datagma API by adding data about ICP (ideal customer profile). Instead of Pipedrive, you can use any other CRM. In this example, ideal buyers are heads of sales/business development. Prerequisites Pipedrive account and Pipedrive credentials How it works Pipedrive trigger node starts the workflow when a new company is created. HTTP Request node queries data from Datagma. Pipedrive node updates Pipedrive contact with new data from Datagma. The Item Lists node simplifies returned data from Datagma that contain lists (arrays), enabling you to easily modify the structure for further processing without the need to use Function nodes and write custom JavaScript. IF node identifies if the lead corresponds ICP. HTTP Request node searches for emails in Datagma. Set node prepares data for further merging. Merge node combines data from multiple streams. Pipedrive node adds a new person in Pipedrive.

Use Case When tracking your contacts and leads in Hubspot CRM, every new contact might be a potential customer. To guarantee that you're keeping the overview you'd normally need to look at every new lead that is coming in manually to identify high-quality leads to prioritize their engagement and optimize the sales process. This workflow saves the work and does it for you. What this workflow does The workflow runs every 5 minutes. On every run, it checks the Hubspot CRM for contacts that were added since the last check. It then checks if they meet certain criteria (in this case if they are making +5m annual revenue) and alerts you in Slack for every match. Setup Add Hubspot, and Slack credentials. Click on Test workflow. How to adjust this workflow to your needs Change the schedule interval Adjust the criteria to send alerts

AI LinkedIn Outreach Automation with Apollo, OpenAI & PhantomBuster Categories:* Sales Automation Lead Generation AI Personalization This workflow creates a complete LinkedIn outreach automation system that generates targeted lead lists from Apollo using natural language, enriches profiles with AI-personalized icebreakers, and automatically sends connection requests through PhantomBuster. Built by someone who's made over $1 million with AI automation, this system demonstrates the real-world approach to building profitable automation workflows. Benefits* Natural Language Lead Targeting - Describe your ideal prospects in plain English and automatically generate Apollo search URLs AI-Powered Personalization - Creates custom icebreakers based on LinkedIn profile data, employment history, and professional background Complete Outreach Pipeline - From lead discovery to personalized connection requests, fully automated end-to-end Smart Data Management - Automatically tracks all prospects in Google Sheets with deduplication and status tracking Cost-Effective Scraping - Uses Apify to extract Apollo data without expensive subscription costs Scalable Architecture - Processes hundreds of leads while respecting LinkedIn's connection limits How It Works* Natural Language Lead Generation: Form input accepts audience descriptions in plain English AI converts descriptions into properly formatted Apollo search URLs Automatically includes location, company size, job titles, and keyword filters Apollo Data Extraction: Uses Apify actor to scrape targeted lead lists from Apollo Extracts LinkedIn URLs, email addresses, employment history, and profile data Processes 500+ leads per run with detailed professional information AI Personalization Engine: Analyzes LinkedIn profile data including job history and company information Generates personalized icebreakers using proven connection request templates Creates human-like messages that reference specific career details and achievements Google Sheets Integration: Automatically stores all lead data in organized spreadsheet format Tracks prospect information, contact details, and generated icebreakers Provides easy data management and campaign tracking PhantomBuster Automation: Connects to PhantomBuster API to trigger LinkedIn connection campaigns Sends personalized connection requests with custom icebreakers Respects LinkedIn's daily limits and mimics human behavior patterns Business Use Cases* Sales Teams - Automate prospecting for B2B outreach campaigns Agencies - Scale client acquisition through targeted LinkedIn outreach Recruiters - Find and connect with qualified candidates efficiently Entrepreneurs - Build professional networks in specific industries Business Development - Generate qualified leads for partnership opportunities Revenue Potential This system can replace expensive LinkedIn outreach tools that cost $200-500/month. Users typically see: 400% improvement in response rates through personalization 10x faster lead generation compared to manual prospecting Ability to process 500+ leads per hour vs. 10-20 manually Difficulty Level: Intermediate Estimated Build Time: 1-2 hours Monthly Operating Cost: ~$50 (Apollo + PhantomBuster + AI APIs) Watch My Complete 1-Hour Build* Want to see exactly how I built this system from scratch? I walk through the entire development process live, including all the debugging, API integrations, and real-world testing that goes into building profitable automation systems. 🎥 See My Live Build Process: "Build This Automated AI LinkedIn DM System in 1 Hour (N8N)" This comprehensive tutorial shows my actual development approach - including the detours, problem-solving, and iterative testing that real automation building involves. Required Google Sheets Setup* Create a Google Sheet with these exact column headers: Essential Lead Columns: id - Unique prospect identifier first_name - Contact's first name last_name - Contact's last name name - Full name linkedin_url - LinkedIn profile URL title - Current job title email_status - Email verification status photo_url - Profile photo URL icebreaker - AI-generated personalized message Setup Instructions: Create Google Sheet with these headers in row 1 Connect Google Sheets OAuth in n8n Update the document ID in the "Add to Google Sheet" node PhantomBuster will read from this sheet for automated outreach Set Up Steps* Apollo & Apify Configuration: Set up Apify account and obtain API credentials Configure Apollo scraper actor with proper parameters Test lead extraction with sample audience descriptions AI Personalization Setup: Configure OpenAI API for natural language processing and personalization Set up prompt templates for audience targeting and icebreaker generation Test personalization quality with sample LinkedIn profiles Google Sheets Integration: Create lead tracking spreadsheet with proper column structure Configure Google Sheets API credentials and permissions Set up data mapping for automatic lead storage PhantomBuster Connection: Set up PhantomBuster account and LinkedIn connection Configure LinkedIn auto-connect agent with custom message templates Connect API for automated campaign triggering Form and Workflow Setup: Configure form trigger for audience input collection Set up data flow between all components Add proper error handling and rate limiting Testing and Optimization: Start with small batches (5-10 connections daily) Monitor LinkedIn account health and response rates Optimize icebreaker templates based on performance data Important Compliance Notes* LinkedIn Limits: Respect 100 connection requests per week limit Account Safety: Use PhantomBuster's human-like behavior patterns Message Quality: Regularly update templates to avoid automation detection Response Management: Monitor and respond to replies within 24 hours Advanced Extensions* This system can be enhanced with: Multi-channel Outreach: Add email sequences for comprehensive campaigns A/B Testing: Test different icebreaker templates automatically CRM Integration: Connect to Salesforce, HubSpot, or other sales systems Response Tracking: Monitor reply rates and optimize messaging Explore My Channel* For more advanced automation systems that generate real business results, check out my YouTube channel where I share the exact strategies I've used to make over $1 million with AI automation.

⚡️ How It Works This workflow captures form submissions from your website, formats the data, and automatically creates a new entry in your Notion CRM database. It eliminates manual copy-pasting and keeps your leads or requests organised in one place. 🛠 Setup Steps Webhook Node • Create a webhook in n8n. • Connect your website form to POST submissions to this webhook URL. Code Node • Formats the incoming data to match your Notion database structure. • You can customise the fields in the code to suit your specific form inputs. Notion Node (Create Page) • Connect your Notion account. • Choose your target database. • Map each field from the Code node output to your Notion database properties. Test • Submit a test form entry. • Confirm the data appears correctly in Notion. ⸻ 👥 Who It’s For ✅ Freelancers collecting project inquiries ✅ Agencies managing client onboarding forms ✅ Business owners wanting organised lead capture ✅ Teams that use Notion as their central CRM or task manager ✅ Anyone tired of manually transferring form data into Notion

🧑‍💼 Who is this for? If you’re using Notion to manage a database (like saving links, tasks, notes, or anything really), and it’s starting to get messy with duplicate entries, this workflow is for you. It’s especially useful if you want to keep things tidy without doing any manual cleanup. 🧠 What problem is this workflow solving? Notion doesn’t have a built-in way to find or remove duplicates, so you either clean them up manually 😩 or just let them pile up. This workflow automatically finds entries that share the same property (like a URL or title) and archives the extra copies, keeping just one. ⚙️ What this workflow does Pulls all pages from a Notion database. Identifies duplicates based on a property you choose. Archives the duplicate pages (which is like soft-deleting them). Keeps one version of each duplicate group. It includes two optional triggers: Run it every day ⏰ Or trigger it automatically when a new page is added to the database ⚡ 🛠️ Setup Connect your Notion account in n8n. Select your database in the Notion nodes. In the “Format items properly” node, replace "SET YOUR PROPERTY HERE" with a reference to the property you want to use for detecting duplicates. I recommend using the n8n property drag-and-drop feature. Enable whichever trigger you prefer — or both. And that’s it. It runs on its own after that. 🧩 How to customize this workflow to your needs Use a different property for detecting duplicates by updating the Set node. Want to tag duplicates instead of archiving them? Just replace the last Notion node with an update operation. Adjust the schedule to run it hourly, weekly, or whenever suits your setup.

This workflow will archive your Spotify Discover Weekly playlist to an archive playlist named "Discover Weekly Archive" which you must create yourself. If you want to change the name of the archive playlist, you can edit value2 in the "Find Archive Playlist" node. It is configured to run at 8am on Mondays, a conservative value in case you forgot to set your GENERIC_TIMEZONE environment variable (see the docs here). Special thanks to erin2722 for creating the Spotify node and harshil1712 for help with the workflow logic. To use this workflow, you'll need to: Create then select your credentials in each Spotify node Create the archive playlist yourself Optionally, you may choose to: Edit the archive playlist name in the "Find Archive Playlist" node Adjust the Cron node with an earlier time if you know GENERIC_TIMEZONE is set Setup an error workflow like this one to be notified if anything goes wrong