{"workflow":{"id":13772,"name":"Analyze Google Forms feedback with Gemini AI and send weekly reports","views":128,"recentViews":1,"totalViews":128,"createdAt":"2026-02-28T05:57:39.925Z","description":"## Who is this for\n\nProduct managers, customer success teams, and small business owners who collect feedback via Google Forms and want automated sentiment analysis without manual review. Ideal for teams processing 10-100+ responses weekly.\n\n## What this workflow does\n\nThis workflow reads new Google Forms responses from a linked Google Sheets spreadsheet, sends them to Gemini AI for sentiment analysis and topic categorization, then writes results back to the sheet, logs weekly insights in a Notion database, and emails an HTML summary report to your team. Each response gets a sentiment label (positive, neutral, negative), a 1-10 score, a category tag, and a key theme extraction.\n\n## How to set up\n\n1. Create a Google Form and link responses to a Google Sheet. Add four columns to the sheet: Processed, Sentiment, Category, Score.\n2. Connect your Google Sheets OAuth2 credential and select the responses sheet.\n3. Connect your Google Gemini API credential (requires a Google AI Studio API key).\n4. Create a Notion database with columns: Date, Total Responses, Positive Rate, Top Themes, Recommendation. Connect your Notion API credential.\n5. Connect your Gmail OAuth2 credential and set the recipient email address.\n6. Activate the workflow.\n\n## Requirements\n\n- Google Sheets OAuth2 credentials (linked to a Google Form)\n- Google Gemini API key (Google AI Studio)\n- Notion API integration token\n- Gmail OAuth2 credentials\n\n## How to customize\n\n- Change the schedule trigger interval for more or less frequent analysis runs.\n- Edit the AI prompt in the Analyze feedback node to add custom categories relevant to your product.\n- Modify the email HTML template in the Parse results node to match your branding.\n- Add a Slack notification node after the email for real-time team alerts.","workflow":{"meta":{"instanceId":"0fd24758e45cbed1f63c03b9ca7326acab4b855985945af441ee95f8874d3e22"},"nodes":[{"id":"27c5a163-c0e8-4a6e-8a92-46ef3c8858c5","name":"Workflow Overview","type":"n8n-nodes-base.stickyNote","position":[-464,-176],"parameters":{"width":540,"height":820,"content":"## Customer feedback analyzer\n\nAutomatically analyze new Google Forms responses using Gemini AI for sentiment analysis, categorization, and actionable insights. Results are logged in Google Sheets, saved to a Notion database, and emailed as a weekly summary.\n\n### How it works\n1. A schedule trigger checks Google Sheets for new unprocessed feedback rows (linked to a Google Form).\n2. A code node filters responses that have not been analyzed yet.\n3. Gemini AI performs sentiment analysis (positive, neutral, negative), categorizes each response by topic, and extracts key themes.\n4. A code node parses the AI output and calculates aggregate statistics like average sentiment score.\n5. Results are written back to the Google Sheets feedback log with sentiment and category columns.\n6. A Notion database entry is created with weekly insight summaries for long-term tracking.\n7. A Gmail message delivers an HTML report with charts-ready data to your team.\n\n### Setup steps\n1. Create a Google Form and link it to a Google Sheet. Add columns: Processed, Sentiment, Category, Score.\n2. Add a **Google Sheets OAuth2** credential.\n3. Add a **Google Gemini API** credential.\n4. Add a **Notion API** credential and create a database with columns: Date, Total Responses, Positive %, Negative %, Top Themes.\n5. Add a **Gmail OAuth2** credential and set the report recipient.\n6. Activate the workflow and test with sample form responses.\n\n### Customization\n- Change the schedule interval in the trigger node (default: daily at 9 AM).\n- Edit the AI prompt to add your own categories or scoring criteria.\n- Adjust the email template in the report formatting code node."},"typeVersion":1},{"id":"3d727898-8861-4866-8e57-f2ebd97ddd94","name":"Collection section note","type":"n8n-nodes-base.stickyNote","position":[96,-176],"parameters":{"color":7,"width":500,"height":380,"content":"## Data collection\nReads new form responses from Google Sheets and filters unprocessed rows."},"typeVersion":1},{"id":"2f5950c9-a722-4929-ad86-9b4b7187f351","name":"AI section note","type":"n8n-nodes-base.stickyNote","position":[608,-176],"parameters":{"color":7,"width":344,"height":552,"content":"## AI analysis\nGemini analyzes each response for sentiment, category, and key themes."},"typeVersion":1},{"id":"3e83b5be-0f6e-4861-a4d9-d5f3fa496214","name":"Output section note","type":"n8n-nodes-base.stickyNote","position":[976,-176],"parameters":{"color":7,"width":788,"height":556,"content":"## Reporting\nWrites results back to Sheets, logs insights in Notion, and emails the summary."},"typeVersion":1},{"id":"7d6011fd-40c0-491b-ba28-4a51147ac23f","name":"Daily feedback check","type":"n8n-nodes-base.scheduleTrigger","position":[128,0],"parameters":{"rule":{"interval":[{"triggerAtHour":9}]}},"typeVersion":1.2},{"id":"dcc02c60-9600-4bcd-a772-655ce3d937b5","name":"Read feedback responses","type":"n8n-nodes-base.googleSheets","position":[304,0],"parameters":{"sheetName":{"__rl":true,"mode":"list","value":""},"documentId":{"__rl":true,"mode":"list","value":""}},"typeVersion":4.5},{"id":"fa7eb92a-48f6-4b06-b270-aeb2510e12cd","name":"Filter unprocessed responses","type":"n8n-nodes-base.code","position":[464,0],"parameters":{"jsCode":"// Filter unprocessed rows and batch them for AI analysis\nvar items = $input.all();\nvar unprocessed = [];\nfor (var i = 0; i < items.length; i++) {\n var row = items[i].json;\n if (!row.Processed || row.Processed === '' || row.Processed === 'no') {\n unprocessed.push({\n rowIndex: i + 2,\n timestamp: row.Timestamp || '',\n response: row.Feedback || row.Response || row['Your feedback'] || '',\n rating: row.Rating || row.Score || ''\n });\n }\n}\nif (unprocessed.length === 0) {\n return { json: { skip: true, message: 'No new responses to analyze' } };\n}\nvar feedbackText = unprocessed.map(function(r, idx) {\n return 'Response ' + (idx + 1) + ' (row ' + r.rowIndex + '): ' + r.response + (r.rating ? ' [Rating: ' + r.rating + ']' : '');\n}).join('\\n');\nreturn { json: { skip: false, count: unprocessed.length, feedbackText: feedbackText, rows: unprocessed } };"},"typeVersion":2},{"id":"91bd04ed-60f2-448e-8031-4a33616f78a0","name":"Analyze feedback with Gemini","type":"@n8n/n8n-nodes-langchain.chainLlm","position":[672,0],"parameters":{"text":"=Analyze the following customer feedback responses. For each response, determine:\n1. Sentiment: positive, neutral, or negative\n2. Sentiment score: 1-10 (1=very negative, 10=very positive)\n3. Category: product, service, pricing, usability, support, or other\n4. Key theme: a short phrase summarizing the main point\n\nAlso provide an overall summary with:\n- Total responses analyzed\n- Sentiment distribution (count of positive/neutral/negative)\n- Top 3 recurring themes\n- One actionable recommendation\n\nReturn valid JSON with this structure:\n{\n \"responses\": [{\"rowIndex\": number, \"sentiment\": string, \"score\": number, \"category\": string, \"theme\": string}],\n \"summary\": {\"total\": number, \"positive\": number, \"neutral\": number, \"negative\": number, \"topThemes\": [string], \"recommendation\": string}\n}\n\nFeedback data:\n{{ $json.feedbackText }}","promptType":"define"},"typeVersion":1.4},{"id":"bd24942e-1d59-4a95-9f7f-ac9e64835737","name":"Gemini Chat Model","type":"@n8n/n8n-nodes-langchain.lmChatGoogleGemini","position":[672,144],"parameters":{"options":{"temperature":0.3},"modelName":"models/gemini-2.0-flash"},"typeVersion":1},{"id":"ea186a1a-6d32-458b-b715-911a6fd551c0","name":"Parse results and build report","type":"n8n-nodes-base.code","position":[1120,0],"parameters":{"jsCode":"// Parse AI response and prepare data for Sheets and email\nvar aiResponse = $input.first().json;\nvar text = aiResponse.text || aiResponse.response || JSON.stringify(aiResponse);\nvar parsed;\ntry {\n var jsonMatch = text.match(/\\{[\\s\\S]*\\}/);\n parsed = JSON.parse(jsonMatch ? jsonMatch[0] : text);\n} catch(e) {\n parsed = { responses: [], summary: { total: 0, positive: 0, neutral: 0, negative: 0, topThemes: [], recommendation: 'Could not parse AI response' } };\n}\nvar responses = parsed.responses || [];\nvar summary = parsed.summary || {};\nvar rows = [];\nfor (var i = 0; i < responses.length; i++) {\n var r = responses[i];\n rows.push({\n rowIndex: r.rowIndex || 0,\n sentiment: r.sentiment || 'unknown',\n score: r.score || 5,\n category: r.category || 'other',\n theme: r.theme || ''\n });\n}\nvar positiveRate = summary.total > 0 ? Math.round((summary.positive / summary.total) * 100) : 0;\nvar negativeRate = summary.total > 0 ? Math.round((summary.negative / summary.total) * 100) : 0;\nvar emailBody = '

Customer Feedback Analysis Report

';\nemailBody += '

Date: ' + new Date().toISOString().split('T')[0] + '

';\nemailBody += '

Responses analyzed: ' + (summary.total || 0) + '

';\nemailBody += '

Sentiment Distribution

';\nemailBody += '';\nemailBody += '

Top Themes

';\nemailBody += '

Recommendation

' + (summary.recommendation || 'N/A') + '

';\nreturn { json: { rows: rows, summary: summary, positiveRate: positiveRate, negativeRate: negativeRate, emailBody: emailBody, topThemes: (themes).join(', '), recommendation: summary.recommendation || 'N/A', total: summary.total || 0 } };"},"typeVersion":2},{"id":"305d9aa9-e043-412a-a8ef-ec5c807960ba","name":"Update feedback sheet with results","type":"n8n-nodes-base.googleSheets","position":[1344,0],"parameters":{"operation":"update","sheetName":{"__rl":true,"mode":"list","value":""},"documentId":{"__rl":true,"mode":"list","value":""}},"typeVersion":4.5},{"id":"46137cfe-cb9a-4851-911b-d2baae8e840b","name":"Log insights to Notion","type":"n8n-nodes-base.notion","position":[1568,0],"parameters":{"options":{},"resource":"databasePage","databaseId":{"__rl":true,"mode":"list","value":""},"propertiesUi":{"propertyValues":[{"key":"Date"},{"key":"Total Responses","numberValue":"={{ $json.total }}"},{"key":"Positive Rate","numberValue":"={{ $json.positiveRate }}"},{"key":"Top Themes"},{"key":"Recommendation"}]}},"typeVersion":2.2},{"id":"f3aa5cef-9c71-483a-9ed0-0d5f5bd0c00f","name":"Email report to team","type":"n8n-nodes-base.gmail","position":[1568,224],"webhookId":"cb3b96ee-7615-470b-9552-a6daf5c1067a","parameters":{"message":"={{ $json.emailBody }}","options":{},"subject":"=Customer Feedback Report - {{ new Date().toISOString().split('T')[0] }}"},"typeVersion":2.1}],"pinData":{},"connections":{"Gemini Chat Model":{"ai_languageModel":[[{"node":"Analyze feedback with Gemini","type":"ai_languageModel","index":0}]]},"Daily feedback check":{"main":[[{"node":"Read feedback responses","type":"main","index":0}]]},"Read feedback responses":{"main":[[{"node":"Filter unprocessed responses","type":"main","index":0}]]},"Analyze feedback with Gemini":{"main":[[{"node":"Parse results and build report","type":"main","index":0}]]},"Filter unprocessed responses":{"main":[[{"node":"Analyze feedback with Gemini","type":"main","index":0}]]},"Parse results and build report":{"main":[[{"node":"Update feedback sheet with results","type":"main","index":0},{"node":"Log insights to Notion","type":"main","index":0}]]},"Update feedback sheet with results":{"main":[[{"node":"Email report to team","type":"main","index":0}]]}}},"lastUpdatedBy":1,"workflowInfo":{"nodeCount":13,"nodeTypes":{"n8n-nodes-base.code":{"count":2},"n8n-nodes-base.gmail":{"count":1},"n8n-nodes-base.notion":{"count":1},"n8n-nodes-base.stickyNote":{"count":4},"n8n-nodes-base.googleSheets":{"count":2},"n8n-nodes-base.scheduleTrigger":{"count":1},"@n8n/n8n-nodes-langchain.chainLlm":{"count":1},"@n8n/n8n-nodes-langchain.lmChatGoogleGemini":{"count":1}}},"status":"published","readyToDemo":null,"user":{"name":"Oka Hironobu","username":"okp29","bio":"https://okp29.net/","verified":true,"links":[""],"avatar":"https://gravatar.com/avatar/d57c7a2cb027c144079388f3ca6c4204696dbee6f1995242748dccd9619fdc09?r=pg&d=retro&size=200"},"nodes":[{"id":18,"icon":"file:googleSheets.svg","name":"n8n-nodes-base.googleSheets","codex":{"data":{"alias":["CSV","Sheet","Spreadsheet","GS"],"resources":{"generic":[{"url":"https://n8n.io/blog/love-at-first-sight-ricardos-n8n-journey/","icon":"❀️","label":"Love at first sight: Ricardo’s n8n journey"},{"url":"https://n8n.io/blog/why-business-process-automation-with-n8n-can-change-your-daily-life/","icon":"🧬","label":"Why business process automation with n8n can change your daily life"},{"url":"https://n8n.io/blog/automatically-adding-expense-receipts-to-google-sheets-with-telegram-mindee-twilio-and-n8n/","icon":"🧾","label":"Automatically Adding Expense Receipts to Google Sheets with Telegram, Mindee, Twilio, and n8n"},{"url":"https://n8n.io/blog/supercharging-your-conference-registration-process-with-n8n/","icon":"🎫","label":"Supercharging your conference registration process with n8n"},{"url":"https://n8n.io/blog/creating-triggers-for-n8n-workflows-using-polling/","icon":"⏲","label":"Creating triggers for n8n workflows using polling"},{"url":"https://n8n.io/blog/no-code-ecommerce-workflow-automations/","icon":"store","label":"6 e-commerce workflows to power up your Shopify s"},{"url":"https://n8n.io/blog/migrating-community-metrics-to-orbit-using-n8n/","icon":"πŸ“ˆ","label":"Migrating Community Metrics to Orbit using n8n"},{"url":"https://n8n.io/blog/automate-google-apps-for-productivity/","icon":"πŸ’‘","label":"15 Google apps you can combine and automate to increase productivity"},{"url":"https://n8n.io/blog/your-business-doesnt-need-you-to-operate/","icon":" πŸ–₯️","label":"Hey founders! 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