Workflow Templates

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

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.

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

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.

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.

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

Extracting LinkedIn Profile Information Use Case Manually copying data from LinkedIn profiles is time-consuming and error-prone. This automation helps you extract structured, detailed information from any public LinkedIn profile—enabling fast enrichment, hiring research, or lead scoring. What This Automation Does This automation extracts profile details from a LinkedIn URL using the following input parameters: airtop_profile**: The name of your Airtop Profile connected to LinkedIn. linkedin_url**: The URL of the LinkedIn profile you want to extract data from. How It Works Starts with a form trigger or via another workflow. Assigns the LinkedIn URL and Airtop profile variables. Opens the LinkedIn profile in a real browser session using Airtop. Uses an AI prompt to extract structured information, including: Name, headline, location Current company and position About section, experience, and education history Skills, certifications, languages, connections, and recommendations Returns structured JSON ready for further use or storage. Setup Requirements Airtop API Key — free to generate. An Airtop Profile connected to LinkedIn (requires one-time login). Next Steps Sync with CRM**: Push extracted data into HubSpot, Salesforce, or Airtable for lead enrichment. Combine with Search Automation**: Use with a LinkedIn search scraper to process profiles in bulk. Adapt to Other Platforms**: Customize the prompt to extract structured data from GitHub, Twitter, or company sites. Read more about the Extract Linkedin Profile Information automation.

You Don’t Need More Tools. You Just Need the Right Leads. Why spend $1,000s on lead gen when your perfect leads are already waiting in Apollo? You’ve already filtered the ideal prospects. You know who they are, where they work, and what they do. Now imagine turning that list into enriched, ready-to-contact leads—without paying pricey Apollo's recurring subscription (spoiler: you will pay only 0.60$ per 500 leads). From Filter to Outreach-Ready in Seconds With the Lead Generation System, you just drop your Apollo search URL. The workflow does the rest: ✅ Scrapes all matching contacts from your Apollo filter ✅ Enriches and organizes the data (names, roles, emails, LinkedIns, companies, etc.) ✅ Delivers the final lead list to Airtable—or your CRM of choice No more manual exports. No CSV mess. No VA needed. Just qualified leads, cleaned and ready to go. Perfect For Founders doing DIY outbound Growth marketers scaling cold email Agencies running lead-gen for clients Anyone tired of paying too much for messy, outdated lists Setup Guide I built a step-by-step guide to setup this workflow in 5 to 10 minutes, available here: https://notanothermarketer.gitbook.io/home/templates/lead-generation This template is free. Enjoy!

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

⚡️ 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

Automating LinkedIn Enrichment and ICP Scoring Use Case This automation enriches a person’s data using LinkedIn and calculates an Ideal Customer Profile (ICP) score based on their professional presence. It is particularly useful for lead qualification, contact research, and targeted outreach. What This Automation Does The automation processes the following input parameters: Person Name**: Full name of the individual. Work Email**: Business email address to validate corporate identity. Airtop Profile (connected to Linkedin)**: A LinkedIn-authenticated Airtop Profile for enrichment. How It Works Email Filtering: Checks if the email is corporate (excludes free and personal domains). LinkedIn Profile Discovery: Searches and verifies the correct LinkedIn URL using Airtop. Data Enrichment: Extracts professional details from the LinkedIn profile. ICP Scoring: Calculates an ICP score based on extracted data and profile context. Merge Outputs: Consolidates enriched profile data and ICP results into a single output. Setup Requirements Airtop API Key An Airtop Profile authenticated on LinkedIn. Next Steps Combine with CRM Integration**: Push enriched and scored data into CRMs like HubSpot or Salesforce. Batch Processing**: Automate for lists of leads using Airtop + n8n or Airtop SDK. Scoring Customization**: Adjust scoring logic to reflect your ideal customer attributes more precisely. Read more about data enrichment and ICP scoring

Automatically classify incoming leads based on the sentiment of their message using Google Gemini, store them in Supabase by category, and send tailored WhatsApp messages via the official WhatsApp Cloud API. ✅ Use Case: This workflow is ideal for sales, onboarding, and customer support teams who want to: Understand the tone and urgency of each lead Prioritize hot leads instantly Send smart, automatic WhatsApp replies based on user sentiment 🧠 How it works: Capture lead via a Typeform webhook Clean and structure the data (name, email, message, etc.) Run sentiment analysis using Google Gemini to classify the message as: Positive → Hot Lead Neutral → Warm Lead Negative → Cold Lead Store lead data in Supabase under the corresponding category Merge data to unify flow paths Send WhatsApp message using the official WhatsApp Cloud API, with a custom reply for each sentiment result 🔧 Tools used: Typeform (incoming data) Google Gemini (AI-based sentiment classification) Supabase (database) WhatsApp Cloud API (response automation) 🏷 Tags: AI, Sentiment Analysis, Lead Qualification, Supabase, WhatsApp, Gemini, Typeform, CRM, Automation, Customer Engagement