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Compare product prices from Amazon, Walmart and Google Shopping via Telegram using OpenAI

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Compare product prices from Amazon, Walmart and Google Shopping via Telegram using OpenAI preview
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1. Workflow Overview

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 purchas...

Best for

  • Market Research automation workflows
  • AI Chatbot automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.stickynote, n8n-nodes-base.code, n8n-nodes-base.telegramtrigger, n8n-nodes-base.httprequest, n8n-nodes-base.merge, n8n-nodes-base.aggregate, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Sankar Battula.

Original n8n.io source

1.1 Workflow description

Title
Compare product prices from Amazon, Walmart and Google Shopping via Telegram using OpenAI
Workflow name
Compare product prices from Amazon, Walmart and Google Shopping via Telegram using OpenAI

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.

What this template does

This 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.

Rather 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.

How it works

  1. A user sends a product name to the Telegram bot.
  2. The workflow queries Walmart, Amazon, and Google Shopping in parallel.
  3. Each marketplace response is cleaned and mapped into a consistent offer structure.
  4. All offers are merged and consolidated into a single dataset.
  5. An AI agent evaluates price, seller, reviews, and match quality to identify the best sensible offer.
  6. A Telegram message is sent back with the recommended price, seller, price range, offer count, confidence level, reasoning, and a direct purchase link.

Requirements

Before using this template, connect the following credentials:

Telegram API OpenAI SerpApi

You'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.

Example input

DJI Osmo Pocket 3 Creator Combo [file:73]

Example output

šŸ”Ž DJI Osmo Pocket 3 (Creator Combo / Osmo Pocket 3 family) āœ… Best Price: $557.91 šŸŖ Seller: B&Z Legend šŸ“Š Range: $6.85 - $1349.99 🧩 Comparable Offers: 69 šŸŽÆ Confidence: Medium šŸ“ 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. šŸ”— 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

If no strong match is found, the workflow prompts the user to try a more specific product name.

Good to know

Results 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.

More specific product names usually produce better recommendations than broad searches.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Sticky Note

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 2 - Sticky Note1

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 3 - Sticky Note2

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 4 - Sticky Note3

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 5 - Sticky Note4

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 6 - Parse Walmart Response

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 7 - Parse Amazon Response

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 8 - Format AI Recommendation

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 9 - Telegram Product Request

Type / Role
n8n-nodes-base.telegramTrigger - telegramTrigger
Config choices
Version 1.2

Block 10 - Search Walmart via SerpApi

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.4

Block 11 - Search Amazon via SerpApi

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.4

Block 12 - Search Google Shopping via SerpApi

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.4

Block 13 - Merge Marketplace Offers

Type / Role
n8n-nodes-base.merge - merge
Config choices
Version 3.2

Block 14 - Aggregate Offer Data

Type / Role
n8n-nodes-base.aggregate - aggregate
Config choices
Version 1

Block 15 - AI: Choose Best Offer

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 3.1

Block 16 - Price Analysis Model

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.3

Block 17 - Send Telegram Recommendation

Type / Role
n8n-nodes-base.telegram - telegram
Config choices
Version 1.2

Block 18 - Parse Google Shopping Response

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

3. Summary Table

Workflow Compare product prices from Amazon, Walmart and Google Shopping via Telegram using OpenAI
Complexity advanced
Nodes 18
Categories Market Research, AI Chatbot
Author Sankar Battula
Published 25 Mar 2026

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/14330/14330.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Compare product prices from Amazon, Walmart and Google Shopping via Telegram using OpenAI do?

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 purchas...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Market Research, AI Chatbot use case.