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This n8n workflow template creates an intelligent data analysis chatbot that can answer questions about data stored in Google Sheets using OpenAI's GPT-5 Mini model. The system automatically analyzes your spreadsheet data and provides insights through natural language conversations. What This Workflow Does Chat Interface: Provides a conversational interface for asking questions about your data Smart Data Analysis: Uses AI to understand column structures and data relationships Google Sheets Integration: Connects directly to your Google Sheets data Memory Buffer: Maintains conversation context for follow-up questions Automated Column Detection: Automatically identifies and describes your data columns Try It Out! --- 1. Set Up OpenAI Connection Get Your API Key 1. Visit the OpenAI API Keys page. 2. Go to OpenAI Billing. 3. Add funds to your billing account. 4. Copy your API key into your OpenAI credentials in n8n (or your chosen platform). --- 2. Prepare Your Google Sheet Connect Your Data in Google Sheets Data must follow this format: Sample Marketing Data First row contains column names. Data should be in rows 2–100. Log in using OAuth, then select your workbook and sheet. --- 3. Ask Questions of Your Data You can ask natural language questions to analyze your marketing data, such as: Total spend across all campaigns. Spend for Paid Search only. Month-over-month changes in ad spend. Top-performing campaigns by conversion rate. Cost per lead for each channel. --- Need Help or Want to Customize This? rbreen@ynteractive.com LinkedIn n8n Automation Experts
by Robert BreenWorking with Large Documents In Your VLM OCR Workflow Document workflows are popular ways to use AI but what happens when your document is too large for your app or your AI to handle? Whether its context window or application memory that's grinding to a halt, Subworkflow.ai is one approach to keep you going. > Subworkflow.ai is a third party API service to help AI developers work with documents too large for context windows and runtime memory. Prequisites 1. You'll need a Subworkflow.ai API key to use the Subworkflow.ai service. 2. Add the API key as a header auth credential. More details in the official docs https://docs.subworkflow.ai/category/api-reference How it Works 1. Import your document into your n8n workflow 2. Upload it to the Subworkflow.ai service via the Extract API using the HTTP node. This endpoint takes files up to 100mb. 3. Once uploaded, this will trigger an Extract job on the service's side and the response is a "job" record to track progress. 4. Poll Subworkflow.ai's Jobs endpoint and keep polling until the job is finished. You can use the "IF" node looping back unto itself to achieve this in n8n. 5. Once the job is done, the Dataset of the uploaded document is ready for retrieval. Use the Datasets and DatasetItems API to retrieve whatever you need to complete your AI task. 6. In this example, all pages are retrieved and run through a multimodal LLM to parse into markdown. A well-known process when parsing data tables or graphics are required. How to use Integrate Subworkflow's Extract API seemlessly into your existing document workflows to support larger documents from 100mb+ to up to 5000 pages. Customising the workflow Sometimes you don't want the entire document back especially if the document is quite large (think 500+ pages!), instead, use query parameters on the DatasetItems API to pick individual pages or a range of pages to reduce the load. Need Help? Official API documentation: https://docs.subworkflow.ai/category/api-reference Join the discord: https://discord.gg/RCHeCPJnYw
by JimleukHow it Works This workflow automatically monitors your Google Ads campaigns every day, analyzing performance with AI-powered scoring to identify scaling opportunities and catch issues before they drain your budget. Each morning at 9 AM, it fetches all active campaign data including clicks, impressions, conversions, costs, and conversion rates from your Google Ads account. The AI analysis engine evaluates four critical dimensions: CTR (click-through rate) to measure ad relevance, conversion rate to assess landing page effectiveness, cost per conversion to evaluate profitability, and traffic volume to identify scale-readiness. Each campaign receives a performance score (0-100 points) and is automatically categorized as Excellent (75+), Good (55-74), Fair (35-54), or Underperforming (0-34). High-performing campaigns trigger instant Slack alerts to your PPC team with detailed scaling recommendations and projected ROI improvements, while underperforming campaigns generate urgent alerts with specific optimization actions. Every campaign is logged to your Google Sheets dashboard with daily metrics, and the system generates personalized email reports—action-oriented scaling plans for top performers and troubleshooting guides for campaigns needing attention. The entire analysis takes minutes, providing your team with daily intelligence reports that would otherwise require hours of manual spreadsheet work and data analysis. --- Who is this for? PPC managers and paid media specialists drowning in campaign data and manual reporting Marketing agencies managing multiple client accounts needing automated performance monitoring E-commerce brands running high-spend campaigns who can't afford budget waste Growth teams looking to scale winners faster and pause losers immediately Anyone spending $5K+ monthly on Google Ads who needs data-driven optimization decisions --- Setup Steps Setup time: Approx. 15-25 minutes (credential configuration, dashboard setup, alert customization) Requirements: Google Ads account with active campaigns Google account with a tracking spreadsheet Slack workspace SMTP email provider (Gmail, SendGrid, etc.) Create a Google Sheets dashboard with two tabs: "Daily Performance" and "Campaign Log" with appropriate column headers. Set up these nodes: Schedule Daily Check: Pre-configured to run at 9 AM daily (adjust timing if needed). Fetch Google Ads Data: Connect your Google Ads account and authorize API access. AI Performance Analysis: Review scoring thresholds (CTR, conversion rate, cost benchmarks). Route by Performance: Automatically splits campaigns into high-performers vs. issues. Update Campaign Dashboard: Connect Google Sheets and select your "Daily Performance" tab. Log All Campaigns: Select your "Campaign Log" tab for historical tracking. Slack Alerts: Connect workspace and configure separate channels for scaling opportunities and performance issues. Generate Action Plan: Customize email templates with your brand voice and action items. Email Performance Report: Configure SMTP and set recipient email addresses. Credentials must be entered into their respective nodes for successful execution. --- Customization Guidance Scoring Weights: Adjust point values for CTR (30), conversion rate (35), cost efficiency (25), and volume (10) in the AI Performance Analysis node based on your business priorities. Performance Thresholds: Modify the 75-point Excellent threshold and 55-point Good threshold to match your campaign quality distribution and industry benchmarks. Benchmark Values: Update CTR benchmarks (5% excellent, 3% good, 1.5% average) and conversion rate targets (10%, 5%, 2%) for your industry. Alert Channels: Create separate Slack channels for different alert types or route critical alerts to Microsoft Teams, Discord, or SMS via Twilio. Email Recipients: Configure different recipient lists for scaling alerts (executives, growth team) vs. optimization alerts (campaign managers). Schedule Frequency: Change from daily to hourly monitoring for high-spend campaigns, or weekly for smaller accounts. Additional Platforms: Duplicate the workflow structure for Facebook Ads, Microsoft Ads, or LinkedIn Ads with platform-specific nodes. Budget Controls: Add nodes to automatically pause campaigns exceeding cost thresholds or adjust bids based on performance scores. --- Once configured, this workflow will continuously monitor your ad spend, identify opportunities worth thousands in additional revenue, and alert you to issues before they waste your budget—transforming manual reporting into automated intelligence. --- Built by Daniel Shashko Connect on LinkedIn
by Daniel Shashko