HumationHuman + Automation
Back to Catalog

B2B lead follow-up automation with Gemini AI, Gmail and Google Sheets

Priyanka RanaPriyanka Rana
204 views
2/3/2026
AirtableMeeting ManagementAutomationProductivityZoom
Official Page

Overview

This n8n workflow template automates your B2B marketing follow-up process. It tracks which introductory emails have received a reply, identifies leads who haven't responded within a set time, uses Gemini AI to draft a personalized, casual reminder, sends the follow-up as a reply on the original thread, and updates your lead tracker in Google Sheets.

Best if used with preivously created workflow that sends an automated introductory email with templatized subject.

Requirements

To use this workflow, you need the following accounts and credentials:

Gmail Account: To check for replies and send the reminder emails.

Google Sheets Account: To manage your lead tracking spreadsheet (the workflow uses a sheet with ID). Below are the Sheet columns First Name Last Name Email ID Company Name Company Information (optional) Designation (optional) Message - the main form enquiry Location (optional) Status (auto) Intro email Date (auto) Reminder 1 needed? (auto) Reminder 1 Email Date (auto)

Google Gemini (PaLM) API Key: For the AI Agent node to generate the personalized email content.

How It Works

This automation is broken down into three main stages:

Stage 1: Check for Replies and Update Tracker

This stage excludes leads who have already replied to your introductory email and updates the status in your tracker.

When clicking ‘Execute workflow’ (Manual Trigger): The workflow starts manually or can be scheduled.

Get many messages (Gmail): The node searches your inbox (CATEGORY_PERSONAL) for replies to your introductory email (using the search query subject: <template of your introductory email>).

Update row in sheet (Google Sheets): For every incoming reply found, the workflow matches the lead by Email ID and updates the column Reminder 1 needed? to No.

Stage 2: Identify Who Needs a Reminder

This stage finds leads who have not yet received a reminder and checks if the introductory email was sent over 5 days ago.

Get row(s) in sheet (Google Sheets): The workflow retrieves all leads from the tracker where the column Reminder 1 needed? is not set to No (i.e., they haven't replied and a reminder status hasn't been logged).

If: A condition checks if the Intro email Date is older than 5 days (DateTime.now().minus({ days: 5 })). Only leads that meet this age criteria are passed forward.

Stage 3: Send Personalized Reminder and Final Update

For eligible leads, the AI generates a follow-up, finds the original email thread, sends the reply, and logs the action.

AI Agent: The AI Agent acts as a B2B marketing assistant to write a short, friendly first reminder email. It uses lead data (First Name, Company Name, Message) to personalize the content, referencing the original introductory email and the client's pain point.

Note: The AI is instructed to format its output into ClientEmail and ClientEmailBody using the Structured Output Parser.

Edit Fields (Set): The structured output from the AI is mapped to workflow fields.

Get many messages1 (Gmail): The workflow searches the SENT label for the original email using the client's email and the introductory subject line to find the correct threadId and messageId.

Reply to a message (Gmail): The personalized body is sent as a reply on the original thread to maintain context.

Update row in sheet1 (Google Sheets): The final step updates the lead's row in the tracker, setting Status to Reminder 1 Drafted, Reminder 1 needed? to Yes, and recording the current date in the Reminder 1 Email Date column.

Customization Currently it has option to send first reminder. This can be extended to add another reminder.

Write to priyanka@buildmyaiflow.agency for more customizations.

B2B Lead Follow-Up Automation with Gemini AI, Gmail, and Google Sheets

This n8n workflow automates the process of following up with B2B leads. It leverages Google Sheets to manage lead data, Google Gemini AI to generate personalized follow-up emails, and Gmail to send them. The workflow includes a conditional logic to ensure emails are only sent to leads who haven't been contacted yet, and a waiting period between follow-ups.

What it does

  1. Triggers Manually: The workflow is initiated manually, allowing you to control when the follow-up process begins.
  2. Reads Lead Data from Google Sheets: It fetches a list of B2B leads from a specified Google Sheet.
  3. Filters for Uncontacted Leads: It checks if a lead has already been contacted by looking at a "Contacted" column in the Google Sheet. Only leads marked as "No" proceed.
  4. Generates Personalized Follow-Up Email with Gemini AI: For each uncontacted lead, it uses the Google Gemini AI Chat Model to generate a personalized follow-up email based on lead information.
  5. Parses AI Output: It uses a Structured Output Parser to extract the generated email content from the AI's response.
  6. Sends Email via Gmail: The personalized email is then sent to the lead using Gmail.
  7. Updates Google Sheet: After sending the email, the "Contacted" status for that lead in the Google Sheet is updated to "Yes" to prevent duplicate follow-ups.
  8. Waits for a Period: A "Wait" node introduces a pause, allowing for a delay before the next lead is processed or a subsequent follow-up stage (if expanded upon).
  9. Prepares Data for Next Iteration (Optional): An "Edit Fields" (Set) node is present, which could be used to transform or prepare data for further processing or for the next loop iteration, though its specific configuration isn't detailed in the provided JSON.

Prerequisites/Requirements

  • n8n Instance: A running n8n instance.
  • Google Sheets Account: To store and manage your B2B lead data.
  • Gmail Account: To send follow-up emails.
  • Google Gemini AI (or compatible Langchain Chat Model): For generating personalized email content. You will need API access and credentials for this service.
  • n8n Credentials:
    • Google Sheets credentials (OAuth 2.0 recommended).
    • Gmail credentials (OAuth 2.0 recommended).
    • Google Gemini AI credentials (API Key or similar).

Setup/Usage

  1. Import the Workflow:
    • Download the provided JSON file.
    • In your n8n instance, click on "Workflows" in the left sidebar.
    • Click "New" and then "Import from JSON".
    • Paste the JSON content or upload the file.
  2. Configure Credentials:
    • Locate the "Google Sheets" node and click on its settings. Configure your Google Sheets credentials.
    • Locate the "Gmail" node and configure your Gmail credentials.
    • Locate the "Google Gemini Chat Model" node and configure your Gemini AI credentials.
  3. Configure Google Sheets Node:
    • Specify the Spreadsheet ID and Sheet Name where your lead data is stored.
    • Ensure your sheet has columns for lead information (e.g., Name, Company, Email, and a "Contacted" column with "Yes" or "No" values).
  4. Configure AI Agent and Structured Output Parser:
    • Review the prompt in the "Google Gemini Chat Model" node to ensure it aligns with your desired email personalization.
    • Adjust the "Structured Output Parser" if the AI output format changes.
  5. Configure Gmail Node:
    • Map the recipient email address from your Google Sheet data.
    • Map the subject and body of the email from the output of the "Structured Output Parser" node.
  6. Configure If Node:
    • Ensure the condition correctly checks your "Contacted" column in Google Sheets to filter for leads that haven't been contacted yet.
  7. Configure Wait Node:
    • Adjust the wait duration as needed (e.g., to space out email sends).
  8. Activate the Workflow:
    • Once configured, activate the workflow by toggling the "Active" switch in the top right corner.
  9. Execute Manually:
    • Click "Execute Workflow" on the "Manual Trigger" node to run the workflow.

Note: The "Edit Fields" (Set) node (ID 38) is present but its specific configuration is not detailed in the provided JSON. You may need to configure it based on your specific data transformation needs.

Related Templates

Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets

This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitor’s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger — Manually start the workflow or schedule it to run periodically. Input Setup — Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) — Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring — Clean and convert GPT output into JSON format. Data Storage (Google Sheets) — Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the “Set Input Fields” node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors → Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection → Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report → Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization → Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs → Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting It’s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.

Ranjan DailataBy Ranjan Dailata
161

Two-way property repair management system with Google Sheets & Drive

This workflow automates the repair request process between tenants and building managers, keeping all updates organized in a single spreadsheet. It is composed of two coordinated workflows, as two separate triggers are required — one for new repair submissions and another for repair updates. A Unique Unit ID that corresponds to individual units is attributed to each request, and timestamps are used to coordinate repair updates with specific requests. General use cases include: Property managers who manage multiple buildings or units. Building owners looking to centralize tenant repair communication. Automation builders who want to learn multi-trigger workflow design in n8n. --- ⚙️ How It Works Workflow 1 – New Repair Requests Behind the Scenes: A tenant fills out a Google Form (“Repair Request Form”), which automatically adds a new row to a linked Google Sheet. Steps: Trigger: Google Sheets rowAdded – runs when a new form entry appears. Extract & Format: Collects all relevant form data (address, unit, urgency, contacts). Generate Unit ID: Creates a standardized identifier (e.g., BUILDING-UNIT) for tracking. Email Notification: Sends the building manager a formatted email summarizing the repair details and including a link to a Repair Update Form (which activates Workflow 2). --- Workflow 2 – Repair Updates Behind the Scenes:\ Triggered when the building manager submits a follow-up form (“Repair Update Form”). Steps: Lookup by UUID: Uses the Unit ID from Workflow 1 to find the existing row in the Google Sheet. Conditional Logic: If photos are uploaded: Saves each image to a Google Drive folder, renames files consistently, and adds URLs to the sheet. If no photos: Skips the upload step and processes textual updates only. Merge & Update: Combines new data with existing repair info in the same spreadsheet row — enabling a full repair history in one place. --- 🧩 Requirements Google Account (for Forms, Sheets, and Drive) Gmail/email node connected for sending notifications n8n credentials configured for Google API access --- ⚡ Setup Instructions (see more detail in workflow) Import both workflows into n8n, then copy one into a second workflow. Change manual trigger in workflow 2 to a n8n Form node. Connect Google credentials to all nodes. Update spreadsheet and folder IDs in the corresponding nodes. Customize email text, sender name, and form links for your organization. Test each workflow with a sample repair request and a repair update submission. --- 🛠️ Customization Ideas Add Slack or Telegram notifications for urgent repairs. Auto-create folders per building or unit for photo uploads. Generate monthly repair summaries using Google Sheets triggers. Add an AI node to create summaries/extract relevant repair data from repair request that include long submissions.

Matt@VeraisonLabsBy Matt@VeraisonLabs
208

Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax

Spark your creativity instantly in any chat—turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. 📋 What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing 🔧 Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation 🔑 Required Credentials OpenAI API Setup Go to platform.openai.com → API keys (sidebar) Click "Create new secret key" → Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai → Dashboard → API Keys Generate a new API key → Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) ⚙️ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflow—chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" 🎯 Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration ⚠️ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions

Daniel NkenchoBy Daniel Nkencho
601