Amazon Price Drop Analysis with Bright Data and Google Gemini - n8n Workflow

• E-commerce analysts and researchers needing structured market intelligence.


• Users running n8n self-hosted instances who utilize community nodes like the Bright Data MCP Client.


• Data scientists interested in combining web scraping with advanced LLM processing in a single n8n workflow.


• Developers looking for complex n8n templates for AI-driven data extraction.

Acquiring timely and analyzed e-commerce price drop information is crucial for competitive analysis and consumer insight. This advanced n8n workflow solves the problem of unstructured web data by combining a powerful scraping tool (Bright Data) with state-of-the-art AI analysis (Google Gemini).

Starting with an n8n trigger, the workflow first extracts a list of daily price drops. It then intelligently uses an LLM for structured data parsing—turning messy scrape results into clean JSON objects ready for looping. For each product identified, the n8n workflow performs a deeper scrape, followed by two separate AI operations: summarization of the product description and detailed sentiment analysis, leveraging dedicated Google Gemini Chat Model n8n nodes. The final, enriched dataset is then centralized in Google Sheets and broadcast via a webhook notification, providing actionable intelligence through this comprehensive n8n solution.

This complex n8n workflow initiates with a Manual Trigger, designed to be executed on demand or scheduled.

1. Initialization: The n8n trigger starts the process. Initial configuration fields are set, including the source URL for price drops and a notification webhook URL.


2. Initial Scraping & Structured Extraction: The Bright Data MCP Client n8n node scrapes the initial price drop listing page (CamelCamelCamel). The raw markdown output is fed into the Structure Data Extract Using LLM n8n node, which leverages the Google Gemini Chat Model and a Structured Output Parser to extract key fields (title, price, link) into clean JSON.


3. Iteration: The resulting list is split out using the Loop Over Items n8n node, processing each product drop individually.


4. Detailed Scraping: Inside the loop, the workflow executes a Wait n8n node (10 seconds) for rate limiting, and then uses a second Bright Data MCP Client n8n node to scrape the detailed product page link associated with that item.


5. AI Analysis: The scraped product details are simultaneously routed to two Langchain n8n nodes: Summarize Content (using the Recursive Character Text Splitter for large inputs and the Google Gemini Chat Model) and Sentiment Analysis (also using the Google Gemini Chat Model, configured with a strict JSON schema for objective sentiment scoring).


6. Data Aggregation: The results of the summarization and sentiment analysis are merged, and then the final results for all products are aggregated using the Aggregate n8n node.


7. Output: The fully processed and analyzed data is logged to a Google Sheets document via the Update Google Sheets n8n node and simultaneously sent as a notification payload through the Webhook Notification for Price Drop Info n8n node.

To deploy this powerful n8n workflow, follow these steps:

1. Prerequisites: This workflow relies on the community n8n-nodes-mcp (Bright Data MCP Client). It is recommended for n8n self-hosted instances.


2. Import: Copy the provided JSON code and import it into your n8n instance using the 'New' menu and 'Import from JSON'.


3. Credentials Setup:

1. Input Configuration: Open the Set input fields n8n node and update the webhooknotificationurl to your desired endpoint (e.g., a Slack webhook or a testing URL like webhook.site).


2. Execution: Click the 'Test workflow' button (the manual n8n trigger) or activate the n8n workflow and set up a schedule.

When clicking ‘Test workflow’ (n8n trigger): A Manual Trigger n8n node used to initiate the data extraction sequence on demand.
Bright Data MCP Client List Tools / MCP Client for Price Drop Data Extract (n8n node): Connects to Bright Data's infrastructure. It is used initially to scrape the price drop overview page, leveraging the scrapeasmarkdown tool.
Set input fields (n8n node): A utility n8n node used to define variables, including the target scrape URL (pricedropurl) and the destination endpoint (webhooknotificationurl).
Structure Data Extract Using LLM (n8n node): This Langchain n8n node utilizes the connected Google Gemini Chat Model and the Structured Output Parser to extract product metadata (like ID, title, savings, link) from the raw scraped markdown, ensuring the data is structured correctly before the loop starts.
Loop Over Items (n8n node): Splits the structured product data so that subsequent operations (detailed scrape, AI analysis) are run individually for each item.
MCP Client for Price Drop Data Extract Within a Loop (n8n node): Scrapes the specific product detail page using the link obtained in the previous step.
Summarize Content (n8n node): An advanced Langchain n8n node configured with a Recursive Character Text Splitter to handle long product descriptions before performing summarization using the Google Gemini model.
Sentiment Analysis (n8n node): This n8n node instructs the Google Gemini model to perform sentiment analysis on the detailed product content, enforcing a JSON schema for objective metrics (sentiment, sentimentScore, topics).
Merge (n8n node): Combines the summarization output and the sentiment analysis output into a single data item for the current product.
Aggregate (n8n node): Collects all processed items after the loop finishes.
Update Google Sheets (n8n node): Appends the final, analyzed dataset to a specified Google Sheet, completing the core data logging action of this n8n workflow.
Webhook Notification for Price Drop Info (n8n node): Sends the final structured data as a JSON payload to the defined webhook, enabling integration with downstream applications.