Amazon Products Dataset with Stock Count Values

**Description**
This sample dataset includes 1,000 real Amazon listings, collected daily from multiple regional Amazon marketplaces (including the US, UK, Germany, and Canada). It contains structured data across three dimensions: products, offers, and customer reviews — supporting analysis of stock levels, pricing strategies, seller dynamics, and buyer sentiment.
The amazon_offers table includes offer-specific details such as price, condition, inventory count, Buy Box status, shipping information, and offer rank. The inventory field is particularly valuable for tracking stock availability per seller and offer over time.
The amazon_products table provides product-level attributes, including title, description, images, monthly sales estimates, technical specifications, and best sellers rank. The reviews table contains verified user feedback, complete with ratings, full text, timestamps, and verification status.
To meet specific analytical or integration needs, we’re happy to collaborate and publish a new listing aligned with your preferred schema and schedule.

**Sample Use Cases**

- 📊 Dynamic Pricing Models:
- Use offer-level data to power machine learning pricing engines.
- 🛒 Buy Box Tracking:
- Identify which sellers dominate the buy box across time and categories.
- 💬 Sentiment Modeling:
- Train LLMs or NLP classifiers on verified review text.
- 📈 Sales Trend Forecasting:
- Predict demand by analyzing the interplay between BSR, review velocity, and inventory fluctuations.
- 🧠 Brand & Product Performance Intelligence:
- Track product-market fit and competitive pricing effectiveness.