{"workflow":{"id":14330,"name":"Compare product prices from Amazon, Walmart and Google Shopping via Telegram using OpenAI","views":20,"recentViews":5,"totalViews":20,"createdAt":"2026-03-25T21:06:59.853Z","description":"Send a product name to Telegram, compare offers across Amazon, Walmart, and Google Shopping, and get the best sensible buying recommendation with confidence level, price range, and a direct purchase link.\n\n## What this template does\n\nThis template transforms Telegram into a smart product price comparison tool. Once a user sends a product name, the workflow simultaneously searches Amazon, Walmart, and Google Shopping, standardizes all results into a unified format, and delivers the most practical buying recommendation.\n\nRather than blindly picking the lowest price, an AI step filters out poor matches, suspiciously cheap listings, and mismatched product variants to ensure the recommendation is trustworthy.\n\n\n## How it works\n\n1. A user sends a product name to the Telegram bot.\n2. The workflow queries Walmart, Amazon, and Google Shopping in parallel.\n3. Each marketplace response is cleaned and mapped into a consistent offer structure.\n4. All offers are merged and consolidated into a single dataset.\n5. An AI agent evaluates price, seller, reviews, and match quality to identify the best sensible offer.\n6. A Telegram message is sent back with the recommended price, seller, price range, offer count, confidence level, reasoning, and a direct purchase link.\n\n\n## Requirements\nBefore using this template, connect the following credentials:\n\nTelegram API\nOpenAI\nSerpApi\n\nYou'll also need to add your own SerpApi key, review the marketplace query settings, and adjust or remove any fixed search location values as needed.\n\n## Example input\n\nDJI Osmo Pocket 3 Creator Combo [file:73]\n\n## Example output\n\n🔎 DJI Osmo Pocket 3 (Creator Combo / Osmo Pocket 3 family)\n✅ Best Price: $557.91\n🏪 Seller: B&Z Legend\n📊 Range: $6.85 - $1349.99\n🧩 Comparable Offers: 69\n🎯 Confidence: Medium\n📝 Why this was chosen: Chosen the lowest sensible price among New/unspecified offers: B&Z Legend at $557.91. Much cheaper listings (< ~$200) appear anomalous or risky (very low prices, unclear sellers). There are lower open-box offers (e.g., $498.75) but they carry added risk; established retailers (Best Buy, Official DJI store, OE USA) list in the ~$569–$999 range if you prefer retailer security.\n🔗 Link: https://www.walmart.com/ip/DJI-Osmo-Pocket-3-Creator-Combo-4K-120fps-Camera-1-CMOS-3-Axis-Stabilization-Face-Object-Tracking-Mic-Clear-Sound-Vlogging-Photography/10583721243?classType=VARIANT\n\n\nIf no strong match is found, the workflow prompts the user to try a more specific product name.\n\n## Good to know\n\nResults may vary depending on marketplace availability, search query quality, and regional settings. Using specific product names typically yields more accurate recommendations than broad or generic searches.\n\nMore specific product names usually produce better recommendations than broad searches. \n\n\n","workflow":{"id":"cjFtpkavkWHqy0Bm","meta":{"instanceId":"917bc29bfa2c82f24f16831fb4e0bfe2709765de8e62d99b486a2dcfe168d792"},"name":"Best Price","tags":[],"nodes":[{"id":"9f9e28a8-eac9-4c40-a656-95f108df1d73","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-800,272],"parameters":{"width":948,"height":620,"content":"## 🛒 Find the Best Product Price Across Amazon, Walmart & Google Shopping\n\nSend a product name to Telegram, compare offers across Amazon, Walmart, and Google Shopping, and get the best sensible buying recommendation with confidence level, price range, and a direct purchase link.\n\n**What this template does**\nThis template turns Telegram into a smart product price comparison tool. When a user sends a product name, the workflow simultaneously queries Amazon, Walmart, and Google Shopping, standardizes all results into a unified format, and delivers the most practical buying recommendation — filtering out suspicious listings and weak matches using an AI step.\n\n**How it works**\n1. A user sends a product name to the Telegram bot\n2. The workflow queries Walmart, Amazon, and Google Shopping in parallel\n3. Each marketplace response is cleaned and mapped into a consistent offer structure\n4. All offers are merged and consolidated into a single dataset\n5. An AI agent evaluates price, seller, reviews, and match quality to identify the best sensible offer\n6. A Telegram message is sent back with the recommended price, seller, price range, offer count, confidence level, reasoning, and a direct purchase link\n\n**Requirements:** Telegram API · OpenAI · SerpApi — add your SerpApi key and review any fixed location/region values in the HTTP Request nodes before use.\n\n**Good to know:** More specific product names yield more accurate results. If no strong match is found, the workflow prompts the user to refine their query."},"typeVersion":1},{"id":"e8b6c840-01f0-437c-8613-c850297dc3d3","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[240,128],"parameters":{"color":4,"width":220,"height":200,"content":"## 📨 Input\n\nUser sends a product name via Telegram to trigger the workflow."},"typeVersion":1},{"id":"9b6abf88-03a3-48a0-b5e8-e0d01727003d","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[528,800],"parameters":{"color":6,"width":524,"height":232,"content":"## 🔍 Marketplace Search\n\nSearches Google Shopping, Amazon, and Walmart in parallel via SerpApi.\n\nEach response is cleaned and normalized into a shared offer structure for consistent comparison.\n\n⚙️ Add your **SerpApi** key to each HTTP Request node and adjust any fixed location or region values as needed."},"typeVersion":1},{"id":"5ba3de21-bce6-4ca6-bcd9-7b586392b799","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[1200,112],"parameters":{"color":3,"width":660,"height":200,"content":"## 🤖 AI Offer Comparison\n\nMerges all marketplace results, then uses an AI agent (GPT-4) to evaluate price, seller reputation, reviews, and title match quality.\n\nAvoids suspiciously cheap listings, weak matches, and clearly different variants — recommending the best sensible buying option."},"typeVersion":1},{"id":"c6658c67-1e3d-47fe-b196-90deb7eed0e2","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[1984,128],"parameters":{"color":5,"width":480,"height":200,"content":"## 📤 Output\n\nFormats the AI recommendation and sends a Telegram message with: best price, seller, price range, offer count, confidence level, reasoning, and purchase link."},"typeVersion":1},{"id":"b8c51f8b-9865-41a2-bb78-e15c813c9b1b","name":"Parse Walmart Response","type":"n8n-nodes-base.code","position":[864,576],"parameters":{"jsCode":"const results = $input.first().json.organic_results;\nconst blocked = [\"at&t\", \"at&t\", \"verizon\", \"t-mobile\"];\n\nreturn results\n  .filter(item => item.seller_name != null && item.seller_name !== \"\")\n  .filter(item => {\n    const title = (item.title ?? \"\").toLowerCase();\n    return !blocked.some(word => title.includes(word))})\n  .map(item => ({\n    json: {\n       seller_name: item.seller_name ?? null,\n      product_id: item.product_id ?? item.us_item_id ?? null,\n      offer_id: item.primary_offer?.offer_id ?? null,\n      title: item.title ?? null,\n      offer_price: item.primary_offer?.offer_price ?? null,\n      reviews: item.reviews ?? null,    \n      badge: null,\n      product_url: item.product_page_url ?? null\n    }\n  }));"},"typeVersion":2},{"id":"f87281b3-6d73-4a83-9c4d-18bbc9aa0bdd","name":"Parse Amazon Response","type":"n8n-nodes-base.code","position":[864,352],"parameters":{"jsCode":"const results = $input.first().json.organic_results;\nconst blocked = [\"Clear\",\"Case\"];\n\nreturn results\n  .filter(item => item.price != null && item.price !== \"\")\n  .filter(item => {\n    const title = (item.title ?? \"\").toLowerCase();\n      return !blocked.some(word => title.includes(word))})\n\n  .map(item => ({\n    json: {\n      marketplace: \"Amazon\",\n      product_id: item.asin ?? null,\n      offer_id: item.asin ?? null,\n      title: item.title ?? null,\n      offer_price: item.extracted_price ?? null,\n      reviews: item.reviews ?? null,\n      seller_name: \"Amazon\",\n      badge: \"Overall Pick\",\n      product_url: item.link_clean ?? item.link ?? null\n    }\n  }));\n"},"typeVersion":2},{"id":"cbe2baa7-bcde-42a5-bdf9-e626a0386bfe","name":"Format AI Recommendation","type":"n8n-nodes-base.code","position":[2000,352],"parameters":{"jsCode":"\nconst raw = $input.first().json.output ?? \"{}\";\nlet data;\n\ntry {\n  data = JSON.parse(raw);\n} catch {\n  return [{\n    json: {\n      message: [\n        \"I couldn't parse the recommendation result.\",\n        \"Please try again with a more specific product name.\"\n      ].join(\"\\n\")\n    }\n  }];\n}\n\nconst formatPrice = (value) =>\n  value === null || value === undefined || value === \"\" || isNaN(Number(value))\n    ? \"N/A\"\n    : `$${Number(value).toFixed(2)}`;\n\nconst confidence = data.confidence || \"Unknown\";\nconst reasoning = data.reasoning || \"No explanation available.\";\nconst comparableCount = data.comparable_offer_count ?? \"N/A\";\nconst productName = data.product_name || \"Unknown product\";\nconst recommendedPrice = formatPrice(data.recommended_price);\nconst minPrice = formatPrice(data.min_price);\nconst maxPrice = formatPrice(data.max_price);\nconst seller = data.recommended_seller || \"Unknown seller\";\nconst link = data.recommended_url || \"N/A\";\n\nif (\n  !data.recommended_price &&\n  !data.recommended_url &&\n  (!data.comparable_offer_count || Number(data.comparable_offer_count) === 0)\n) {\n  return [{\n    json: {\n      message: [\n        `🔎 ${productName}`,\n        \"I could not find a confident product match.\",\n        \"Try a more specific name with brand, model, storage, color, or bundle.\"\n      ].join(\"\\n\")\n    }\n  }];\n}\n\nconst message = [\n  `🔎 ${productName}`,\n  `✅ Best Price: ${recommendedPrice}`,\n  `🏪 Seller: ${seller}`,\n  `📊 Range: ${minPrice} - ${maxPrice}`,\n  `🧩 Comparable Offers: ${comparableCount}`,\n  `🎯 Confidence: ${confidence}`,\n  `📝 Why this was chosen: ${reasoning}`,\n  `🔗 Link: ${link}`\n].join(\"\\n\");\n\nreturn [{ json: { message } }];\n"},"typeVersion":2},{"id":"ea6e989e-5708-492d-9725-feb65ecdc6ee","name":"Telegram Product Request","type":"n8n-nodes-base.telegramTrigger","position":[320,352],"webhookId":"aa4244ec-6712-4a8f-981d-cc9e4e9eb0a1","parameters":{"updates":["message"],"additionalFields":{}},"typeVersion":1.2},{"id":"d91a60b9-652d-46d7-a036-0988130c23c5","name":"Search Walmart via SerpApi","type":"n8n-nodes-base.httpRequest","position":[608,576],"parameters":{"url":"https://serpapi.com/search","options":{"response":{"response":{"responseFormat":"json"}}},"sendQuery":true,"queryParameters":{"parameters":[{"name":"engine","value":"walmart"},{"name":"query","value":"={{ $json.message.text }}"},{"name":"api_key"}]}},"typeVersion":4.4},{"id":"f32b7a10-39d1-4131-a61d-9f9e33e1bf08","name":"Search Amazon via SerpApi","type":"n8n-nodes-base.httpRequest","position":[608,352],"parameters":{"url":"https://serpapi.com/search","options":{"response":{"response":{"responseFormat":"json"}}},"sendQuery":true,"queryParameters":{"parameters":[{"name":"engine","value":"amazon"},{"name":"k","value":"={{ $json.message.text }}"},{"name":"amazon_domain","value":"amazon.com"},{"name":"api_key"}]}},"typeVersion":4.4},{"id":"6167982f-bf8d-4a0f-a297-d621d3098273","name":"Search Google Shopping via SerpApi","type":"n8n-nodes-base.httpRequest","position":[608,128],"parameters":{"url":"https://serpapi.com/search","options":{"response":{"response":{"responseFormat":"json"}}},"sendQuery":true,"queryParameters":{"parameters":[{"name":"engine","value":"google_shopping"},{"name":"q","value":"={{ $json.message.text }}"},{"name":"location","value":"United+States"},{"name":"api_key"}]}},"typeVersion":4.4},{"id":"6d7de77b-6c20-4f24-b09e-e8bb53efc25f","name":"Merge Marketplace Offers","type":"n8n-nodes-base.merge","position":[1168,336],"parameters":{"numberInputs":3},"typeVersion":3.2},{"id":"f5475b85-0812-473c-b4ed-23f7af14a83e","name":"Aggregate Offer Data","type":"n8n-nodes-base.aggregate","position":[1408,352],"parameters":{"options":{},"aggregate":"aggregateAllItemData"},"typeVersion":1},{"id":"865661c0-aeef-4b85-9961-c8643fb73880","name":"AI: Choose Best Offer","type":"@n8n/n8n-nodes-langchain.agent","position":[1648,352],"parameters":{"text":"=Act as a product price analyst.\n\nYour task is to review all marketplace offers for the same product and suggest the best lowest price to buy.\n\nUse only the input data provided.\nDo not use external knowledge.\nDo not guess missing values.\n\nInput:\n{{ JSON.stringify($json.data) }}\n\nRules:\n1. Compare all offers by title, price, seller, reviews, and product URL.\n2. Treat offers as comparable only if they refer to the same product family and close variant.\n3. Exclude offers that are clearly different variants, such as different model, storage, Pro/Pro Max, carrier status, or bundle.\n4. Exclude offers with unclear or invalid prices.\n5. Mark condition from the title when possible, such as New, Refurbished, Restored, Used, Pre-Owned, Renewed, or Unknown.\n6. Recommend the lowest sensible price to buy.\n7. Do not automatically choose the absolute cheapest offer if it looks risky due to very low reviews, suspicious title, weak seller signal, or poor match quality.\n8. If the cheapest offer is still a valid and sensible choice, recommend it.\n9. Keep the reasoning short and practical.\n10. Return valid JSON only.\n11. No markdown, no code fences, no extra text.\n\nReturn this exact JSON schema:\n{\n  \"product_name\": \"\",\n  \"total_offers_reviewed\": 0,\n  \"comparable_offer_count\": 0,\n  \"min_price\": null,\n  \"max_price\": null,\n  \"avg_price\": null,\n  \"median_price\": null,\n  \"recommended_price\": null,\n  \"recommended_seller\": \"\",\n  \"recommended_url\": \"\",\n  \"condition_summary\": \"\",\n  \"confidence\": \"\",\n  \"reasoning\": \"\"\n}\n","options":{},"promptType":"define"},"typeVersion":3.1},{"id":"3f7483d2-bb9d-4e23-97d1-01744962655d","name":"Price Analysis Model","type":"@n8n/n8n-nodes-langchain.lmChatOpenAi","position":[1504,576],"parameters":{"model":{"__rl":true,"mode":"list","value":"gpt-5-mini"},"options":{},"builtInTools":{}},"typeVersion":1.3},{"id":"63ad1712-fe57-4c2d-b951-890b06f8d01b","name":"Send Telegram Recommendation","type":"n8n-nodes-base.telegram","position":[2160,352],"webhookId":"c18ae219-cb34-453a-a5be-8f1af98d8345","parameters":{"text":"={{ 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}));"},"typeVersion":2}],"active":false,"pinData":{},"settings":{"binaryMode":"separate","executionOrder":"v1"},"versionId":"2fb2d17b-e6ba-4fa8-a731-f43ab5f4f010","connections":{"Aggregate Offer Data":{"main":[[{"node":"AI: Choose Best Offer","type":"main","index":0}]]},"Price Analysis Model":{"ai_languageModel":[[{"node":"AI: Choose Best Offer","type":"ai_languageModel","index":0}]]},"AI: Choose Best Offer":{"main":[[{"node":"Format AI Recommendation","type":"main","index":0}]]},"Parse Amazon Response":{"main":[[{"node":"Merge Marketplace Offers","type":"main","index":1}]]},"Parse Walmart Response":{"main":[[{"node":"Merge Marketplace Offers","type":"main","index":0}]]},"Format AI Recommendation":{"main":[[{"node":"Send Telegram Recommendation","type":"main","index":0}]]},"Merge Marketplace Offers":{"main":[[{"node":"Aggregate Offer Data","type":"main","index":0}]]},"Telegram Product Request":{"main":[[{"node":"Search Walmart via SerpApi","type":"main","index":0},{"node":"Search 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