Automate multi-platform social media lookup from Google Sheets with Gemini AI
๐ Whoโs it for This template is designed for campaigners, researchers, and organizers who need to enrich spreadsheets of contacts with publicly available social media profiles. Ideal for advocacy campaigns, outreach, or digital organizing where fast, scalable people lookup is needed. โ๏ธ What it does This workflow scans a Google Sheet for rows marked as unanalysed ("Analysed?" = false), sends each contact to a dedicated AI-powered research agent, and returns structured public profile links across major platforms like: Twitter/X LinkedIn Facebook Instagram GitHub TikTok YouTube Reddit Threads Medium Substack And more (18+ total) It processes one contact per run for clarity and stability, appending the results back to the original Google Sheet. ๐ ๏ธ How to set it up Copy the Google Sheet template โ This sheet includes sample columns and headers for contacts and social profile fields. Paste your contact list at the end of the sheet. For each new contact, make sure the "Analysed?" column is set to false. Clone this workflow and the AI Research Agent subworkflow. Connect your Google Sheets account in n8n. Update the workflow with your sheet ID and sheet name (Sheet1 by default). Trigger the workflow on a schedule (e.g. every 15 minutes) or run it manually. โ Requirements Google Sheets integration set up in n8n Access to this AI research subworkflow OpenRouter API key n8n (self-hosted or cloud) ๐งฉ How to customize the workflow Modify the research agent to prioritize specific platforms or return only verified profiles. Add more profile columns to the Google Sheet and schema to match your custom fields. Add logic to send alerts (email, Slack, etc.) for specific contacts. Use an n8n webhook instead of a schedule to run the process on demand. Use a loop over all items to process all rows sequentially (only recommended for small datasets due to memory constraints)
By Open PawsAi lead scoring & enrichment from Mailchimp to HubSpot and Pipedrive with GPT-4o
How it works This workflow captures new subscribers from a Mailchimp list and extracts their key details. It then enriches the subscriber data using AI, predicting professional attributes and assigning a lead score. Based on the score, high-value leads are identified, and all leads are synced into HubSpot and Pipedrive. For top-priority leads, the workflow automatically creates new deals in Pipedrive for sales follow-up. Step-by-step Step-by-step Capture subscriber data Mailchimp Subscriber Trigger โ Detects new signups in a Mailchimp list. Extract Subscriber Data โ Normalizes payload into clean fields like name, email, and timestamp. Enrich with AI Lead Enrichment AI โ Uses AI to infer company, role, industry, intent, LinkedIn, and lead score. Parse & Merge Enrichment โ Merges AI output with subscriber info and sets defaults if parsing fails. Qualify leads High-Value Lead Check โ Filters leads with a score โฅ70 to flag them as priority. Create High-Value Deal โ Opens a new deal in Pipedrive for high-value leads. Sync to CRMs HubSpot Contact Sync โ Updates enriched lead data in HubSpot CRM. Pipedrive Person Create โ Adds lead as a person in Pipedrive. Why use this? Automatically enrich raw Mailchimp subscribers with valuable professional insights. Score and qualify leads instantly for prioritization. Keep HubSpot and Pipedrive updated with enriched lead records. Automate deal creation for high-value opportunities, saving sales team effort. Build a seamless pipeline from marketing signups to CRM-ready opportunities.
By Avkash KakdiyaAutomated LinkedIn lead enrichment pipeline using Apollo.io & Google Sheets
LinkedIn to Apollo.io Lead Enrichment System with Google Sheets Automatically capture company and store details from LinkedIn posts, enrich them with domain names and key decision-maker (KDM) data from Apollo.io, and store everything neatly in Google Sheets. This workflow turns LinkedIn post data into a complete, structured lead database โ fully automated from detection to enrichment. --- ๐งพ Summary This workflow reads LinkedIn post data (in JSON format) received via a webhook, extracts company and location information using an AI agent, and progressively enriches the data in three stages: Find Company Domain using Apollo.io Fetch Key Decision Makers (KDMs) using the company domain Find Corporate Emails for those KDMs All results are automatically updated in Google Sheets, ensuring your lead list remains fresh, structured, and actionable. --- โ๏ธ Prerequisites Before running the workflow, make sure you have: An Apollo.io API Key with company and people search access A connected Google Sheets account (OAuth2) A Webhook URL or LinkedIn scraper that feeds JSON-formatted post data (Optional) An OpenAI / AI Agent node to extract company names and store locations from post text --- ๐งฉ Example Input (Webhook JSON) Each LinkedIn post is received as a JSON object containing key clues: json { "index": 1, "text": "Excited to announce the opening of our new KFC store at Sky City Mall, Borivali East ๐๐\n\nLooking forward to welcoming you all to experience the Finger Lickinโ Good taste at our newest location!\n\nKFCIndia NewStoreOpening Borivali SkyCityMall Sapphirefoods", "CompanyName": "MockCompany", "NewStoreLocation": "optional", "PersonPosted": "https://linkedin.com/in/mockperson", "PostImage": null, "PostLink": "https://www.linkedin.com/search/results/all/?keywords=%23kfcindia&origin=HASHTAGFROM_FEED", "extracted_at": "2025-09-08T12:05:40.044101" } ๐ง Workflow Overview This workflow runs in three main stages, moving from LinkedIn data โ company domain โ people โ emails. --- Stage 1: Company Name to Company Domain ๐ Goal: Convert each company name into its website domain using Apollo.io. Nodes & Flow Schedule Trigger โ Runs automatically (e.g., once a week) to check your Google Sheet for companies missing a domain. IF Node (Check for Missing Domain) โ Filters only companies without a website. Loop Over Items โ Iterates through each company record. HTTP Request โ Find Domain โ Calls the Apollo.io Company API to find the companyโs domain (e.g., kfc.com). Update Row in Google Sheets โ Writes the found domain back into the corresponding company row. Wait Node โ Delay Between API Calls โ Adds a small pause to avoid hitting rate limits. --- Stage 2: Domain to Top 10 KDMs ๐ฅ Goal: Fetch key decision-makers (KDMs) from each company using Apollo.io. Nodes & Flow Schedule Trigger โ Runs on a weekly cadence to check for companies with a domain but no KDMs. Get Rows from Google Sheets โ Pulls company records ready for enrichment. IF Node (Check for Missing KDMs) โ Ensures only companies without people data are processed. Loop Over Items โ Processes one company at a time. HTTP Request โ Find KDMs โ Searches Apollo.io People API for top roles such as Founder, CEO, Head of Retail, etc. Update Row in Google Sheets โ Saves the top 10 names and their LinkedIn profiles into your sheet. Wait Node โ Adds a delay to manage rate limits safely. --- Stage 3: KDM Profile to Email Enricher ๐ง Goal: Find and store verified corporate email addresses for each KDM. Nodes & Flow Schedule Trigger โ Weekly automation trigger. Get Rows from Google Sheets โ Pulls KDMs that have LinkedIn profiles but no email yet. IF Node (Check for Missing Emails) โ Ensures only valid records are processed. Code Node โ Prepare Data โ Organizes LinkedIn profile and domain information. HTTP Request โ Find Email โ Queries Apollo.ioโs email enrichment endpoint using the LinkedIn URL and domain. Code Node โ Format Response โ Cleans and formats the email result. Wait Node โ Adds delay to avoid request bursts. Update Row in Google Sheets โ Writes the verified email address back to the corresponding KDM entry and marks it as โUpdated โ email search.โ ๐ --- ๐งฐ Setup Instructions Connect APIs & Credentials Add your Apollo.io API Key under HTTP Request credentials. Connect your Google Sheets account (OAuth2). Customize Sheet Structure Add columns for: CompanyName, Domain, KDMs, LinkedInProfile, Email, Status Set Schedule Frequency Each Schedule Trigger can be configured separately (e.g., Stage 1 every Monday, Stage 2 every Wednesday). Optional: AI Extraction Node Use an AI model (like OpenAI or Gemini) to extract company name and location from LinkedIn post text before enrichment. --- ๐งฐ Custom Node Names (Recommended for Clarity) | Node Type | Recommended Name | Description | |------------|------------------|-------------| | HTTP Request (Company) | Find Company Domain (Apollo.io) | Searches for the companyโs official domain | | HTTP Request (People) | Find Key Decision Makers (Apollo.io) | Retrieves top company contacts | | HTTP Request (Emails) | Find Corporate Emails (Apollo.io) | Gets verified email addresses for each contact | | Wait Node | API Delay (Rate Limit Buffer) | Adds delay to avoid hitting API rate limits | | Code Node | Prepare KDM Data | Organizes input data for API calls | --- โ๏ธ Customization Tips Multiple Campaigns: Duplicate the workflow for different industries or store categories, updating parameters as needed. Batch Size: Adjust API request limits (e.g., 100 per batch) based on your Apollo.io plan. Filtering: Add IF conditions to skip records already marked as โCompleted.โ Dashboards: Build visual analytics directly in Google Sheets or connect to Looker Studio. Enrichment: Combine with CRM systems (like HubSpot or Close) using company domain or lead email as the linking key. --- ๐ Security and Publishing Notes ๐ Never hardcode API keys in workflow exports. Use n8n credentials or environment variables instead. ๐ซ Replace sensitive values (like API keys or Sheet IDs) with placeholders before sharing. ๐ Keep your Google Sheet private unless intentionally shared. --- ๐งฉ Troubleshooting No Data in Sheets: Check API response for data[] and verify Split Out configuration. Duplicate Rows: Ensure the โMatching Columnโ in Google Sheets is correctly set (e.g., CompanyName or LinkedInProfile). Rate Limits: Add Wait Nodes or reduce batch size. Mapping Errors: Confirm Google Sheet headers exactly match node field mappings. Timezone Adjustments: Apollo.io timestamps are in UTC โ convert to local time if needed. --- ๐ฏ Example Use Case Every week, this workflow scans new LinkedIn store-opening posts. It extracts company names (like KFC India), finds their domains and top executives through Apollo.io, retrieves their emails, and logs everything in a Google Sheet โ ready for your sales team to reach out. --- Tags: LinkedIn Apollo Automation LeadGeneration GoogleSheets MarketingOps DataEnrichment
By Rahi Uppal