Quick Overview
This workflow runs every Monday to scrape recent Amazon product reviews via ScraperAPI, uses OpenAI to classify sentiment and feature tags, and then saves each new review into a Notion database with structured properties and a formatted page body.
How it works
- Runs every Monday at 8am and loads a configured watchlist of Amazon ASINs plus Notion and locale settings.
- Fetches Amazon product data (including recent reviews) for each ASIN using ScraperAPI.
- Extracts reviews from each response and only forwards reviews that have not been seen in previous runs, capped per ASIN.
- Sends each new review to OpenAI to return a JSON sentiment label, 1–4 feature tags, and a one-sentence summary.
- Normalizes the AI output, clips long review text to fit Notion limits, and converts the review date into an ISO date.
- Creates a new page in the target Notion database for each review, filling properties like Sentiment, Stars, Feature tags, Product, Review date, and metadata.
Setup
- Add ScraperAPI credentials and ensure the ScraperAPI Amazon Product (SDE) endpoint is available for your account.
- Add Notion API credentials, share the target database with your Notion integration, and copy the database ID into the watchlist and setup configuration.
- Manually run the “Run once — set up Notion columns” path to create/ensure the required Notion database properties (Sentiment, Stars, Feature tags, Product, Review date, Verified, Reviewer, ASIN, AI summary).
- Add an OpenAI API credential and confirm the selected chat model is available in your OpenAI account.
- Update the ASIN list, locale settings (tld and countryCode), and the max new reviews per ASIN to match your products and desired volume.