This workflow automates web scraping of Amazon search result pages by retrieving raw HTML, cleaning it to retain only the relevant product elements, and then using an LLM to extract structured product data (name, description, rating, reviews, and price), before saving the results back to Google Sheets. It integrates Google Sheets to supply and collect URLs, BrightData to fetch page HTML, a custom n8n Function node to sanitize the HTML, LangChain (OpenRouter GPT-4) to parse product details, and Google Sheets again to store the output. URL to scape . Result Who Needs Amazon Search Result Scraping? This scraping workflow is ideal for teams and businesses that need to monitor Amazon product listings at scale: E-commerce Analysts** – Track competitor pricing, ratings, and inventory trends. Market Researchers** – Collect data on product popularity and reviews for market analysis. Data Teams** – Automate ingestion of product metadata into BI pipelines or data lakes. Affiliate Marketers** – Keep affiliate catalogs up to date with latest product details and prices.
Tags
Google SheetsWHTTP Request
OpenRouter Chat Model
Structured Output ParserRelated workflows
See all AI Automation→
Monitor Japanese business partners for registry changes with gBizINFO and Gemini
Quick Overview This workflow runs weekly to check Japanese business partners listed in Google Sheets against the gBizINFO corporate registry API, uses Google Gemini to assess the risk impact of detected changes, updates the stored partner snapshot, and escalates findings to Slack and Gmail based on materiality. How it works Runs every week on a schedule. Reads the partner list (including corporate numbers and last-known name/address) from Google Sheets. Queries the gBizINFO corporate registry API for each partner and posts a Slack message if the lookup fails. Compares the latest registry data to the stored snapshot to detect name, address, or closure/dissolution changes and continues only when changes are found. Sends the detected changes to Google Gemini to classify materiality (high/medium/low) with a short summary and recommended action, and posts a Slack message if the assessment fails. Updates the Google Sheets partner snapshot with the latest registry details so the change is recorded. Routes by materiality to notify Slack (medium/other), and for high materiality also posts a Slack alert and creates a Gmail draft requesting a credit review. Setup Create a Google Sheets spread
Match Japanese jGrants subsidies to your company with Gemini, Slack and Gmail
Quick Overview This workflow runs weekly to search the public jGrants API for open Japanese subsidies, scores each subsidy’s fit for your company using Google Gemini, logs results to Google Sheets, and notifies a Slack channel (and drafts a Gmail kickoff email) for strong matches. How it works Runs weekly on a schedule and loads your company profile details (industry, headcount, prefecture, investment plan, and search keyword). Calls the public jGrants subsidies API to retrieve currently accepting programs sorted by newest first, and posts to Slack if the search fails. Processes each returned subsidy individually and asks Google Gemini to produce a fit score, verdict (strong/possible/no), reasons, next steps, and a short summary. Normalizes the Gemini response into consistent fields, and posts to Slack if scoring fails for a subsidy. Upserts each scored subsidy into a Google Sheets tracker (keyed by subsidy ID) to avoid duplicates across weekly runs. Routes results by verdict: sends a detailed Slack alert and creates a Gmail draft for strong matches, posts a lightweight Slack message for possible matches, and flags unclear verdicts in Slack. Setup Add credentials for Google Gemini
Monitor overtime risk against Japanese labour caps with Gemini, Sheets, Slack & Gmail
Quick Overview This workflow runs weekly to read attendance overtime from Google Sheets, totals it per employee and month, uses Google Gemini to classify risk against Japanese labour-law limits, writes results back to Sheets, and escalates high-risk cases via Slack and a Gmail draft. How it works Runs every week on a schedule. Loads configured Japanese overtime limits and fetches raw attendance rows from a Google Sheets “Attendance” worksheet. Aggregates overtime hours per employee per month. Sends each employee-month total to Google Gemini, which returns a structured risk level (over/approaching/ok) plus a short summary and recommended manager actions. Stores or updates the assessment in a Google Sheets “Overtime Status” worksheet keyed by employee and month. Posts to Slack when overtime is over the cap (and drafts a manager notice in Gmail), posts an early-warning Slack message when approaching the cap, and flags unclear or failed assessments to Slack for manual review. Setup Add credentials for Google Sheets OAuth, Google Gemini (PaLM) API, Slack OAuth2, and Gmail OAuth2. Create a Google Sheets spreadsheet with an “Attendance” sheet containing Employee (or Name), Month (or Date)