Amazon Product Performance Scoring using AI, Bright Data, and Google Sheets - n8n Workflow

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E-commerce Sellers and Managers looking for automated competitive analysis.
Product Researchers needing scalable Amazon trend monitoring.
Data Analysts who want to combine web scraping, AI decision-making, and database operations in a single n8n workflow.
Users seeking advanced n8n templates integrating Langchain AI Agents and custom tools.

Manual competitive research is slow and prone to errors. This specialized n8n workflow transforms how product performance analysis is conducted. By leveraging a multi-step automation process, this solution fetches product URLs from your source of truth (Google Sheets), employs the powerful web scraping capabilities of Bright Data to gather real-time metrics (units sold, sales rank, pricing, and reviews), and then utilizes an OpenAI AI Agent to intelligently score the product's market performance out of 10. Every step is handled by a dedicated n8n node, ensuring reliability and efficiency. This complete n8n automation provides a live intelligence dashboard directly within your Google Sheet, allowing quick, data-driven decisions.

This powerful n8n workflow begins with the Manual n8n trigger, activated by clicking 'Execute workflow.'

1. Trigger & Data Fetch: The n8n trigger initiates the process. The first n8n node, 'Fetch Amazon URLs from Google Sheets,' reads the list of Amazon product URLs and their corresponding row numbers from your designated Google Sheet.


2. AI Orchestration (The Brain): The flow then moves to the 'Amazon Product Analyzer (AI Agent)' n8n node. This Langchain Agent receives each URL and determines the best course of action.


3. Data Scrape: The AI Agent utilizes the 'Tool: MCP Client (Bright Data)' n8n node, which uses Bright Data's infrastructure to safely scrape complex Amazon data, including estimated units sold, stock availability, and sales rank.


4. AI Scoring: After receiving the scraped data, the Agent’s embedded 'OpenAI Chat Model' (using GPT-4o-mini) analyzes the gathered metrics. It performs a product analyst function, generating a 'performance rating out of 10.'


5. Structured Output: An 'Auto-fixing Output Parser' n8n node, backed by a secondary LLM, ensures the AI’s output is perfectly formatted into a structured JSON object, ready for database insertion. This is a critical feature of this n8n template, ensuring clean data.


6. Data Writeback: Finally, the 'Update Sheet with Product Insights' Google Sheets n8n node takes the newly processed and scored data and updates the original spreadsheet row by row, matching on the row_number field. This completes the fully automated n8n workflow cycle.

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1. Import the n8n workflow: Copy the provided JSON code and import it into your n8n instance via the 'Workflows' section.


2. Google Sheets Setup: You need two credentials. One for reading the URLs and one for updating the data. Ensure your Google Sheets account is connected via OAuth2. Update the 'Document ID' and 'Sheet Name' parameters in both Google Sheets n8n nodes to match your source sheet, which must contain a column for 'URL'.


3. OpenAI Credentials: Set up credentials for the OpenAI API key used by the OpenAI Chat Model n8n node and its secondary parsing node. This is essential for the AI Agent functionality.


4. Bright Data Credentials: Configure the MCP Client (Bright Data) credentials. This n8n node requires specific credentials to utilize the web scraping tool.


5. Activation: Ensure all credentials are set up correctly, and then click the manual n8n trigger to test the complete n8n workflow execution.

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When clicking ‘Execute workflow’ (Manual Trigger n8n node):
Function: This is the starting n8n trigger point for the automation, initiating the execution manually.
Key Configuration: None.
Fetch Amazon URLs from Google Sheets (Google Sheets n8n node):
Function: Reads the list of Amazon product URLs and their associated row numbers from a specified Google Sheet, providing the data necessary for the rest of the n8n workflow.
Key Configuration: Reads from document ID 12ouaPrMp5HEKKctEhVmjmIBVSFu75P4NFFe20XKH9mM (Product purchase trends).
Amazon Product Analyzer (AI Agent n8n node):
Function: Orchestrates the scraping and analysis process. It uses an internal instruction set to determine what information to extract and score, based on the input URL.
Key Configuration: Prompt defined to 'extract the unit sold, current price, stock availability, review count & rating, sales rank and based on it's purchasing performance give it rating out of 10.'
Tool: MCP Client (Bright Data n8n node):
Function: The web scraping tool utilized by the AI Agent. It executes the webdataamazonproduct operation to retrieve complex, real-time Amazon product data.
Key Configuration: Operation set to executeTool using the webdataamazonproduct tool name.
OpenAI Chat Model (LLM n8n node):
Function: Serves as the primary Large Language Model (GPT-4o-mini) for the Agent's reasoning and scoring tasks within this n8n template.
Update Sheet with Product Insights (Google Sheets n8n node):
Function: Writes the final, AI-processed product data back to the original Google Sheet using the update operation. This n8n node ensures data persistence.
* Key Configuration: Matches rows using the row_number field and defines output columns for Ranking, Sales rank, Units sold, Current price, etc., sourcing data from the Agent's output.