Compare Amazon prices with Google Shopping using Bright Data, OpenAI and Slack

Quick Overview

This workflow runs every morning to scrape your watched Amazon product prices with Bright Data, compares them to the last saved snapshot in Google Sheets, checks Google Shopping for cheaper offers when changes occur, and uses OpenAI GPT-5.6 to post a concise price-movement brief to Slack.

How it works

1. Runs daily on a schedule and loads a watchlist of Amazon product URLs and alert thresholds from the workflow configuration.
2. Sends the product URLs to Bright Data’s Amazon dataset scraper to collect the latest price, stock, seller, rating, and rank data.
3. Reads the existing history tab in Google Sheets, compares each product to its most recent prior snapshot, and flags price moves beyond the configured percentage thresholds, stock flips, or buy box seller changes.
4. Appends today’s full product snapshot to the Google Sheets history tab to create the baseline for the next run.
5. For products with flagged changes, queries Bright Data’s SERP API for Google Shopping results and extracts the cheapest plausible new-condition competing offers.
6. Uses OpenAI GPT-5.6 to write a sub-200-word Slack-ready brief grounded in the collected numbers and posts it to a Slack channel.

Setup

1. Create a Bright Data account, set up access to the Amazon dataset scrape endpoint and a SERP API zone, and add an HTTP Header Auth credential with Authorization: Bearer YOUR_KEY for both Bright Data HTTP requests.
2. Create a Google Sheet with a history tab, add Google Sheets credentials in n8n, and paste the sheet URL into history_sheet in the workflow configuration.
3. Add an OpenAI credential that can access the gpt-5.6-terra model and a Slack credential with permission to post messages.
4. Update the Slack target channel (default #price-watch) and paste your Amazon product URLs (one per line) plus thresholds like alert_drop_pct, alert_rise_pct, and max_products in the workflow configuration.