{"workflow":{"id":13587,"name":"Analyze Amazon review friction and revenue impact with Bright Data, OpenRouter and Google Sheets","views":34,"recentViews":0,"totalViews":34,"createdAt":"2026-02-22T14:39:57.773Z","description":"# \n\n## Description\nThis workflow automatically extracts Amazon product reviews and identifies hidden friction signals that are costing you conversions.  \nIt helps ecommerce and product teams turn customer complaints into measurable revenue opportunities.\n\n## Overview\nThis workflow uses Bright Data's Web Scraper API to collect Amazon reviews, then scans them for friction signals like delivery issues, return complaints, sizing problems, and product defects.  \n\nAI classifies each friction signal by revenue impact, scores severity, and prioritizes the most costly conversion leaks.  \n\nResults are split into:\n- **Checkout Optimization List**\n- **Delivery & Returns Risk Report**\n\nBoth are logged into Google Sheets for immediate action.\n\n## Tools Used\n- **n8n**: Automation platform that orchestrates the workflow  \n- **Bright Data**: Scrapes Amazon product reviews at scale without getting blocked  \n- **OpenRouter**: AI-powered friction classification, revenue impact estimation, and prioritization  \n- **Google Sheets**: Logs checkout optimization opportunities, delivery risks, and errors  \n\n## How to Install\n\n### 1. Import the Workflow\nDownload the `.json` file and import it into your n8n instance.\n\n### 2. Configure Bright Data\nAdd your Bright Data API credentials to all Bright Data nodes.\n\n### 3. Configure OpenRouter\nAdd your OpenRouter API key for AI friction analysis.\n\n### 4. Set Up Google Sheets\nCreate a spreadsheet following the **\"Google Sheets Setup\"** sticky note inside the workflow.  \nConnect each Google Sheets node to your document.\n\n### 5. Customize\nEdit the configuration node to define:\n- Target Amazon product URL  \n- Review scope  \n- Analysis depth  \n\n## Use Cases\n\n### Ecommerce Managers\nFind out exactly why customers are dropping off and fix the highest-impact issues first.\n\n### Product Teams\nIdentify recurring product defects or sizing issues from real customer feedback at scale.\n\n### CX / Support Teams\nSpot delivery and returns patterns before they become widespread complaints.\n\n### Conversion Rate Optimization\nPrioritize checkout and UX improvements based on actual revenue impact data.\n\n### Competitive Analysis\nAnalyze competitor product reviews to uncover weaknesses you can capitalize on.\n\n## Connect with Me\n- Website: https://www.nofluff.online  \n- YouTube: https://www.youtube.com/@YaronBeen/videos  \n- LinkedIn: https://www.linkedin.com/in/yaronbeen/  \n- Get Bright Data: https://get.brightdata.com/1tndi4600b25  \n  *(Using this link supports my free workflows with a small commission)*\n\n## Tags\n#n8n #automation #brightdata #webscraping #ecommerce #conversionrate #amazonreviews  \n#customerfriction #productreviews #revenueoptimization #checkoutoptimization  \n#deliveryissues #returnrates #cro #n8nworkflow #workflow #nocode #businessintelligence  \n#customerexperience #productfeedback #reviewanalysis #ecommerceautomation #amazondata  \n#sentimentanalysis #customerinsights","workflow":{"id":"VbwgyOwe5ImcwQXu","meta":{"instanceId":"c472dc5b77c39e85c24b6b0c69695b32e066723590f680ec56e2999b59319459"},"name":"Finding Customer Friction & Conversion Leaks with Bright Data & n8n","tags":[],"nodes":[{"id":"78e45031-ebab-4b2d-a094-d841ddb58fb7","name":"Run Friction Analysis","type":"n8n-nodes-base.manualTrigger","position":[-4432,1376],"parameters":{},"typeVersion":1},{"id":"a061d9e9-f6bc-4510-b073-764140c5e1bb","name":"Set Product URL","type":"n8n-nodes-base.set","position":[-4208,1376],"parameters":{"options":{},"assignments":{"assignments":[{"id":"4539b934-3e9f-4692-a398-0b1388476813","name":"url","type":"string","value":"https://www.amazon.com/Amazon-Basics-Micro-Foam-Nitrile-Coated/dp/B08DDZ1BDV/ref=sr_1_1?adgrpid=87137420328&dib=eyJ2IjoiMSJ9.TSfdhc3EZnn9H2llyVoZXzn6Mt0g1fqCSJpTXab0SD8x6YU9WZ2p72KbpJyDfwxxh5BNCBzULjb_5y7zhoLRB_iVL8czclcKAA_7_xmKkXZ9gYpoNd2lwRSz0oagsf-VvAbQC1hlVJkMdhO9MmnLoKYXpB5A-OEOcAy7cWej-XGIQJaBZR49M28Z1zntbeitNxrDMQ4YGQ5rOKAS1XzrFBuX1C4SRQzU1ePB2ypceERh4jNmti_ZVbQaOv-EyHkYpJS2PgXMjhAfkiXEB9ZC_9qIi5J4YqlgRmMrZKVGvBg.ZMnwoBOKQaX36cEuy0iI6R6v_WszSLdW_zsQjRePkqg&dib_tag=se&hvadid=585479824073&hvdev=c&hvlocphy=9075163&hvnetw=g&hvqmt=b&hvrand=1405474185371293561&hvtargid=kwd-2971+1234567890&hydadcr=29108_14573980&keywords=gloves+amazon&mcid=b731b334a709335cb77408996e3e4244&qid=1771246359&sr=8-1"}]}},"typeVersion":3.4},{"id":"f7c6ee46-231c-4add-b43a-7d7fbd12d1f5","name":"Start Review Scraping (Bright Data)","type":"@brightdata/n8n-nodes-brightdata.brightData","onError":"continueErrorOutput","position":[-3600,1376],"parameters":{"urls":"=[{\"url\":\"{{ $json.url }}\"}]","resource":"webScrapper","operation":"triggerCollectionByUrl","dataset_id":{"__rl":true,"mode":"list","value":"gd_le8e811kzy4ggddlq","cachedResultName":"Amazon Reviews"},"requestOptions":{}},"retryOnFail":false,"typeVersion":1},{"id":"fb1ce830-ceac-48f4-9870-8cb702c02bac","name":"Wait Before Status Check","type":"n8n-nodes-base.wait","position":[-3248,1360],"webhookId":"c262619e-11b8-490c-8170-ae9ab1a65216","parameters":{"amount":30},"typeVersion":1.1},{"id":"dfba77a2-e913-4e80-9290-d1489bf42560","name":"Check Scraping Status","type":"@brightdata/n8n-nodes-brightdata.brightData","position":[-3024,1360],"parameters":{"resource":"webScrapper","operation":"monitorProgressSnapshot","snapshot_id":"={{ $json.snapshot_id }}","requestOptions":{}},"typeVersion":1},{"id":"ef1d50cf-04b8-4ea7-b3e5-4fe5147385bb","name":"Is Snapshot Ready?","type":"n8n-nodes-base.if","position":[-2800,1360],"parameters":{"options":{},"conditions":{"options":{"version":3,"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"53b0d323-2400-4f38-a810-dd8b2a66dacf","operator":{"type":"string","operation":"equals"},"leftValue":"={{ $json.status }}","rightValue":"ready"}]}},"typeVersion":2.3},{"id":"7a7f7c2d-81f3-4dec-9145-5fc6b72784a1","name":"Download Review Data","type":"@brightdata/n8n-nodes-brightdata.brightData","position":[-2240,1344],"parameters":{"resource":"webScrapper","operation":"downloadSnapshot","snapshot_id":"={{ $json.snapshot_id }}","requestOptions":{}},"typeVersion":1},{"id":"28f4955b-81b1-4a60-bbe4-f9a904531641","name":"Detect Friction Signals","type":"n8n-nodes-base.code","position":[-2016,1344],"parameters":{"jsCode":"return items.map(item => {\n\n  let signals = [];\n  const review = (item.json.review_text || \"\").toLowerCase();\n\n  // Delivery Issues\n  if (\n    review.includes(\"late delivery\") ||\n    review.includes(\"arrived late\") ||\n    review.includes(\"shipping delay\") ||\n    review.includes(\"took too long\")\n  ) {\n    signals.push(\"delivery_delay\");\n  }\n\n  // Returns / Refund Issues\n  if (\n    review.includes(\"refund\") ||\n    review.includes(\"return\") ||\n    review.includes(\"money back\") ||\n    review.includes(\"refund denied\")\n  ) {\n    signals.push(\"returns_friction\");\n  }\n\n  // Quality / Durability Issues\n  if (\n    review.includes(\"fell apart\") ||\n    review.includes(\"doesn't last\") ||\n    review.includes(\"broke\") ||\n    review.includes(\"torn\") ||\n    review.includes(\"poor quality\")\n  ) {\n    signals.push(\"product_durability_issue\");\n  }\n\n  // Sizing Issues\n  if (\n    review.includes(\"run small\") ||\n    review.includes(\"too tight\") ||\n    review.includes(\"too loose\") ||\n    review.includes(\"size up\")\n  ) {\n    signals.push(\"sizing_issue\");\n  }\n\n  // Support Issues\n  if (\n    review.includes(\"no response\") ||\n    review.includes(\"customer service\") ||\n    review.includes(\"support didn't\")\n  ) {\n    signals.push(\"support_issue\");\n  }\n\n  return {\n    json: {\n      ...item.json,\n      frictionSignals: signals\n    }\n  };\n\n});\n"},"typeVersion":2},{"id":"ee60903e-c78a-4dda-b32c-a2324adb8bd8","name":"Any Friction Detected?","type":"n8n-nodes-base.if","position":[-1808,1344],"parameters":{"options":{},"conditions":{"options":{"version":3,"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"020b1422-1d58-44f2-baad-d575310ac940","operator":{"type":"array","operation":"notEmpty","singleValue":true},"leftValue":"={{ $json.frictionSignals }}","rightValue":""}]}},"typeVersion":2.3},{"id":"583e15c6-64bc-4412-a5f1-523e358099fc","name":"Prepare Review for AI Analysis","type":"n8n-nodes-base.set","position":[-1168,1328],"parameters":{"options":{},"assignments":{"assignments":[{"id":"5300ca2a-5c4d-49b8-90f8-9fc4be2d4534","name":"brand","type":"string","value":"={{$json.brand}}"},{"id":"2714bb1c-88e2-452d-af87-73400107bb5b","name":"productName","type":"string","value":"={{ $json.product_name }}"},{"id":"0d610520-afcc-4c50-9e76-87828c662c99","name":"asin","type":"string","value":"={{ $json.asin }}"},{"id":"930bd5fb-86cf-4a87-95f7-2d6877900af2","name":"frictionSignals","type":"array","value":"={{ $json.frictionSignals }}"},{"id":"240c0a8f-36ff-4c53-8739-c494c67f4ca4","name":"frictionType","type":"string","value":"={{$json.frictionSignals[0]}}\n"},{"id":"5af85e38-a897-4784-805e-c1ad2846610c","name":"reviewText","type":"string","value":"={{$json.review_text}}"},{"id":"71447117-856e-44be-89dc-8b609f8dbd4a","name":"reviewRating","type":"number","value":"={{ $json.rating }}"},{"id":"ca714089-aa7f-42c8-8929-6aea1606b1ef","name":"review_header","type":"string","value":"={{ $json.review_header }}"},{"id":"c532cd60-cb84-4d60-a892-d4fb907c000c","name":"revenueImpactScore","type":"number","value":0},{"id":"b715444c-1df9-49b1-bb85-95a2d986d7e0","name":"confidenceScore","type":"number","value":0},{"id":"87d83964-433f-48a0-a483-e696cf52abe2","name":"review_country","type":"string","value":"={{ $json.review_country }}"},{"id":"033ed87a-c755-4972-876c-26b597d44e5e","name":"review_posted_date","type":"string","value":"={{ $json.review_posted_date }}"}]}},"typeVersion":3.4},{"id":"c99ba0f1-d9ad-4e3d-8db0-089be31de580","name":"AI Friction Impact Analyzer","type":"@n8n/n8n-nodes-langchain.agent","position":[-944,1328],"parameters":{"text":"=Analyze the following ecommerce friction data:\n\nBrand: {{$json.brand}}\nProduct: {{$json.productName}}\nASIN: {{$json.asin}}\nFriction Signals: {{$json.frictionSignals}}\nReview Rating: {{$json.reviewRating}}\nReview Header: {{$json.review_header}}\nReview Text: {{$json.reviewText}}\n\n\nClassify:\n\n1. Friction category (Checkout / Delivery / Returns / Support / Product)\n2. Estimated revenue impact (Low / Medium / High)\n3. Numerical impact score (0-100)\n4. Confidence score (0-100)\n5. Short reasoning\n\nRespond strictly in this JSON format:\n\n{\n  \"brand\": \"\",\n  \"productName\": \"\",\n  \"asin\": \"\",\n  \"reviewHeader\": \"\",\n  \"reviewText\": \"\",\n  \"reviewRating\": 0,\n  \"frictionSignals\": [],\n  \"frictionCategory\": \"\",\n  \"estimatedImpact\": \"\",\n  \"impactScore\": 0,\n  \"confidenceScore\": 0,\n  \"reasoning\": \"\"\n}\n","options":{"systemMessage":"You are an ecommerce conversion intelligence engine.\n\nYou analyze product friction signals extracted from customer reviews.\n\nAlways respond strictly in valid JSON.\nNo explanations outside JSON.\n"},"promptType":"define","hasOutputParser":true},"typeVersion":3.1},{"id":"c140c590-19a8-4f6b-ae14-085e6156a03d","name":"Validate AI Friction Output","type":"@n8n/n8n-nodes-langchain.outputParserStructured","position":[-784,1600],"parameters":{"schemaType":"manual","inputSchema":"{\n  \"type\": \"object\",\n  \"properties\": {\n    \"brand\": {\n      \"type\": \"string\"\n    },\n    \"productName\": {\n      \"type\": \"string\"\n    },\n    \"asin\": {\n      \"type\": \"string\"\n    },\n    \"reviewHeader\": {\n      \"type\": \"string\"\n    },\n    \"reviewText\": {\n      \"type\": \"string\"\n    },\n    \"reviewRating\": {\n      \"type\": \"number\"\n    },\n    \"frictionSignals\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"string\"\n      }\n    },\n    \"frictionCategory\": {\n      \"type\": \"string\",\n      \"enum\": [\"Checkout\", \"Delivery\", \"Returns\", \"Support\", \"Product\"]\n    },\n    \"estimatedImpact\": {\n      \"type\": \"string\",\n      \"enum\": [\"Low\", \"Medium\", \"High\"]\n    },\n    \"impactScore\": {\n      \"type\": \"number\",\n      \"minimum\": 0,\n      \"maximum\": 100\n    },\n    \"confidenceScore\": {\n      \"type\": \"number\",\n      \"minimum\": 0,\n      \"maximum\": 100\n    },\n    \"reasoning\": {\n      \"type\": \"string\"\n    }\n  },\n  \"required\": [\n    \"brand\",\n    \"productName\",\n    \"asin\",\n    \"reviewHeader\",\n    \"reviewText\",\n    \"reviewRating\",\n    \"frictionSignals\",\n    \"frictionCategory\",\n    \"estimatedImpact\",\n    \"impactScore\",\n    \"confidenceScore\",\n    \"reasoning\"\n  ]\n}\n"},"typeVersion":1.3},{"id":"e36ed31e-190b-4188-a0f0-e14067cf4d23","name":"Calculate Correlated Friction Score","type":"n8n-nodes-base.code","position":[-576,1328],"parameters":{"jsCode":"return items.map(item => {\n\n  const data = item.json.output;\n\n  let frictionWeight = 0;\n\n  if (data.frictionSignals?.includes(\"checkout_failure\")) frictionWeight += 40;\n  if (data.frictionSignals?.includes(\"delivery_delay\")) frictionWeight += 25;\n  if (data.frictionSignals?.includes(\"returns_friction\")) frictionWeight += 20;\n  if (data.frictionSignals?.includes(\"support_issue\")) frictionWeight += 15;\n  if (data.frictionSignals?.includes(\"sizing_issue\")) frictionWeight += 20;\n  if (data.frictionSignals?.includes(\"product_durability_issue\")) frictionWeight += 30;\n\n  const impactComponent = (data.impactScore || 0) * 0.7;\n\n  const finalScore = Math.round(frictionWeight + impactComponent);\n\n  return {\n    json: {\n      ...data,\n      correlatedScore: finalScore\n    }\n  };\n\n});\n"},"typeVersion":2},{"id":"80332a79-1d65-4605-8edb-c5d66af75c19","name":"Is High-Risk Revenue Friction?","type":"n8n-nodes-base.if","position":[-80,1328],"parameters":{"options":{},"conditions":{"options":{"version":3,"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"62f3951b-dc89-453f-b1dc-03414a3ff7e6","operator":{"type":"number","operation":"gt"},"leftValue":"={{ $json.correlatedScore }}","rightValue":60}]}},"typeVersion":2.3},{"id":"1210bb63-14e7-410f-a61d-fd33885e006f","name":"Tag as High 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}}","Review Header":"={{ $json.reviewHeader }}","Review Rating":"={{ $json.reviewRating }}","Revenue Impact":"={{ $json.estimatedImpact }}","Confidence Score":"={{ $json.confidenceScore }}"},"schema":[{"id":"Brand","type":"string","display":true,"required":false,"displayName":"Brand","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Friction Type","type":"string","display":true,"required":false,"displayName":"Friction Type","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Revenue Impact","type":"string","display":true,"required":false,"displayName":"Revenue Impact","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Priority","type":"string","display":true,"required":false,"displayName":"Priority","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Impact Score","type":"string","display":true,"required":false,"displayName":"Impact Score","defaultMatch":false,"canBeUsedToMatch":true},{"id":"Confidence 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Bright Data Customer Friction & Conversion‑Loss Intelligence Engine"}},"typeVersion":4.7},{"id":"86db919b-3a9e-4286-aecb-ea99da273c35","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-5136,624],"parameters":{"color":4,"width":512,"height":576,"content":"## Customer Friction & Conversion-Loss Intelligence Engine\n\nThis workflow extracts Amazon reviews and identifies hidden revenue friction.\n\nIt:\n\n- Scrapes and monitors review data\n- Detects delivery, returns, product & support issues\n- Uses AI to estimate revenue impact\n- Scores and prioritizes friction severity\n- Logs high-risk conversion leaks automatically\n\nOutput Delivers:\n- Optimization Opportunity\n- Delivery & Returns Risk\n\nWhat you need:\n- Bright Data account (for web scraping)\n- OpenRouter API key (for AI analysis)\n- Google Sheets (for output dashboards)\n\nThe result: structured friction intelligence that turns customer complaints into measurable revenue opportunities.\n"},"typeVersion":1},{"id":"48c90aeb-d535-4f0b-bf4f-5efe70184acf","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[-3680,1056],"parameters":{"color":7,"width":1072,"height":768,"content":"## Review Scraping Flow\n\nInitiates and manages the collection of customer review data from Amazon using Bright Data to enable friction and conversion analysis.\n\n- Starts automated review scraping process  \n- Monitors snapshot generation progress  \n- Waits until review dataset is fully ready  \n- Downloads structured review content  \n- Handles and logs scraping failures  \n\nProvides reliable and structured review input for downstream friction signal detection and impact analysis."},"typeVersion":1},{"id":"8cd5f1a9-aab0-4883-bc22-09776bea562a","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[-2304,1008],"parameters":{"color":7,"width":752,"height":768,"content":"## Friction Signal Detection\n\nAnalyzes downloaded customer reviews to identify potential friction points impacting user experience and conversion.\n\n- Processes structured review data  \n- Detects delivery and fulfillment issues  \n- Identifies returns and refund-related concerns  \n- Flags product durability or quality complaints  \n- Filters reviews with no critical friction signals  \n\nPrepares validated friction signals for downstream AI impact analysis."},"typeVersion":1},{"id":"58ca37d7-fc3e-45c6-9434-6201b3d145d2","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[-1232,992],"parameters":{"color":7,"width":816,"height":816,"content":"## AI Friction Impact Analysis\n\nProcesses validated friction signals using AI to estimate their impact on customer experience and conversions.\n\n- Prepares review data for AI analysis  \n- Classifies type of customer friction  \n- Estimates revenue impact level  \n- Assigns numerical impact score  \n- Validates structured AI output  \n\nEnables prioritization of conversion-impacting customer experience issues."},"typeVersion":1},{"id":"7757d68f-e273-460e-b5d9-ec11b9bc3011","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[-144,816],"parameters":{"color":7,"width":784,"height":1008,"content":"## Friction Prioritization & Opportunity Logging\n\nFilters high-risk friction signals and routes them into structured reporting dashboards.\n\n- Flags high-risk revenue-impacting friction  \n- Tags moderate or low-priority issues  \n- Prepares checkout optimization opportunities  \n- Logs delivery and returns-related risks  \n- Stores prioritized friction insights for reporting  \n\nSupports targeted conversion optimization and operational improvements."},"typeVersion":1},{"id":"36a23fbf-d956-47c9-a5fc-d37991621fc3","name":"Friction Impact Analyzer","type":"@n8n/n8n-nodes-langchain.lmChatOpenRouter","position":[-960,1600],"parameters":{"options":{}},"typeVersion":1},{"id":"4cd0fb94-0ead-47aa-abb9-99489833212d","name":"No Friction Detected","type":"n8n-nodes-base.set","position":[-1744,1584],"parameters":{"options":{},"assignments":{"assignments":[{"id":"31f389dc-a1f2-45f9-81b7-b37811d5c313","name":"frictionSignals","type":"string","value":"There is no issue for the customer in review"}]}},"typeVersion":3.4},{"id":"04baa210-e459-4d50-944b-83ba8a766fac","name":"Sticky Note5","type":"n8n-nodes-base.stickyNote","position":[-5136,1232],"parameters":{"color":4,"width":512,"height":480,"content":"## Setup Instructions\n\nBefore running this workflow, configure the following credentials in n8n:\n\n**1. Bright Data API** — Required for web scraping\n- Sign up at brightdata.com\n- Create an API token\n- Add as \"BrightData account\" credential in n8n\n\n**2. OpenRouter API** — Required for AI classification\n- Sign up at openrouter.ai\n- Generate an API key\n- Add as \"OpenRouter account\" credential in n8n\n\n**3. Google Sheets OAuth** — Required for output logging\n- Connect your Google account in n8n\n- See the **Google Sheets Setup** sticky note for required tabs and columns\n- Update each Google Sheets node to point to your new spreadsheet\n\nAfter connecting credentials, edit the configuration node to set your target companies, URLs, or parameters."},"typeVersion":1},{"id":"9018eebe-cf35-414e-a353-7aee195ed37c","name":"Sticky Note6","type":"n8n-nodes-base.stickyNote","position":[-4512,1056],"parameters":{"color":7,"width":464,"height":560,"content":"## Input & Configuration\n\nInitial configuration block where the target product URL is defined for friction analysis.\n\n- Sets the Amazon product page URL  \n- Initiates workflow execution manually  \n- Provides configurable entry point for review analysis  \n\nAllows flexible targeting of product-level customer friction signals."},"typeVersion":1},{"id":"c96bf200-f6d3-490b-83e6-583389f5b6fb","name":"Sticky Note7","type":"n8n-nodes-base.stickyNote","position":[-5136,1744],"parameters":{"color":4,"width":512,"height":440,"content":"## Google Sheets Setup\n\nCreate a Google Spreadsheet with 3 tabs and add these column headers in row 1:\n\n**Tab: Checkout Optimisation List**\nBrand | Friction Type | Revenue Impact | Priority| Impact Score | Confidence Score | ASIN | Review Header | Review Rating | Timestamp\n\n**Tab: Delivery & Returns Risk Report**\nbrand | productName | asin | reviewHeader | reviewText | reviewRating | frictionSignals | frictionCategory | estimatedImpact | impactScore | confidenceScore | reasoning | correlatedScore | deliveryRisk | returnsRisk\n\n**Tab: log bright data error**\nerrorSource | errorMessage | errorCode | timestamp | hasError\n\nAfter creating the spreadsheet, update each Google Sheets node to point to your document and select the matching tab."},"typeVersion":1}],"active":false,"pinData":{},"settings":{"binaryMode":"separate","availableInMCP":false,"executionOrder":"v1"},"versionId":"6da612ec-bcc3-47e2-b04c-d8cbe9f4c7eb","connections":{"Set Product URL":{"main":[[{"node":"Start Review Scraping (Bright Data)","type":"main","index":0}]]},"Is Snapshot Ready?":{"main":[[{"node":"Download Review Data","type":"main","index":0}],[{"node":"Wait Before Status Check","type":"main","index":0}]]},"Download Review Data":{"main":[[{"node":"Detect Friction Signals","type":"main","index":0}]]},"Tag as High Priority":{"main":[[{"node":"Log Checkout Optimization Opportunity","type":"main","index":0}]]},"Check Scraping Status":{"main":[[{"node":"Is Snapshot Ready?","type":"main","index":0}]]},"Run Friction Analysis":{"main":[[{"node":"Set Product URL","type":"main","index":0}]]},"Any Friction Detected?":{"main":[[{"node":"Prepare Review for AI Analysis","type":"main","index":0}],[{"node":"No Friction Detected","type":"main","index":0}]]},"Detect Friction Signals":{"main":[[{"node":"Any Friction Detected?","type":"main","index":0}]]},"Format Bright Data Error":{"main":[[{"node":"Log Scraping Error","type":"main","index":0}]]},"Friction Impact Analyzer":{"ai_languageModel":[[{"node":"AI Friction Impact Analyzer","type":"ai_languageModel","index":0}]]},"Wait Before Status Check":{"main":[[{"node":"Check Scraping Status","type":"main","index":0}]]},"AI Friction Impact Analyzer":{"main":[[{"node":"Calculate Correlated Friction Score","type":"main","index":0}]]},"Validate AI Friction Output":{"ai_outputParser":[[{"node":"AI Friction Impact Analyzer","type":"ai_outputParser","index":0}]]},"Is High-Risk Revenue Friction?":{"main":[[{"node":"Tag as High Priority","type":"main","index":0},{"node":"Prepare Delivery & Returns Risk Flags","type":"main","index":0}],[{"node":"Tag as Moderate / Low Priority","type":"main","index":0}]]},"Prepare Review for AI Analysis":{"main":[[{"node":"AI Friction Impact Analyzer","type":"main","index":0}]]},"Calculate Correlated Friction Score":{"main":[[{"node":"Is High-Risk Revenue Friction?","type":"main","index":0}]]},"Start Review Scraping (Bright Data)":{"main":[[{"node":"Wait Before Status Check","type":"main","index":0}],[{"node":"Format Bright Data Error","type":"main","index":0}]]},"Prepare Delivery & Returns Risk Flags":{"main":[[{"node":"Log Delivery & Returns Risk","type":"main","index":0}]]}}},"lastUpdatedBy":1,"workflowInfo":{"nodeCount":31,"nodeTypes":{"n8n-nodes-base.if":{"count":3},"n8n-nodes-base.set":{"count":7},"n8n-nodes-base.code":{"count":2},"n8n-nodes-base.wait":{"count":1},"n8n-nodes-base.stickyNote":{"count":8},"n8n-nodes-base.googleSheets":{"count":3},"n8n-nodes-base.manualTrigger":{"count":1},"@n8n/n8n-nodes-langchain.agent":{"count":1},"@n8n/n8n-nodes-langchain.lmChatOpenRouter":{"count":1},"@brightdata/n8n-nodes-brightdata.brightData":{"count":3},"@n8n/n8n-nodes-langchain.outputParserStructured":{"count":1}}},"status":"published","readyToDemo":null,"user":{"name":"Yaron Been","username":"yaron-nofluff","bio":"Building AI Agents and Automations | Growth Marketer | Entrepreneur | Book Author & Podcast Host\n\nIf you need any help with Automations, feel free to reach out via linkedin:\nhttps://www.linkedin.com/in/yaronbeen/\n\nAnd check out my Youtube 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