review-analyzer

To extract customer pain points and selling points from Amazon reviews, you can analyze raw review data using ASIN-based fetching via Shulex VOC OpenAPI or by uploading a CSV for cross-platform data. This automatically identifies core sentiment to inform product development.

Yes, you can analyze cross-platform ecommerce reviews by providing review data in a CSV file format. The system processes the uploaded CSV to extract sentiment, pain points, and selling points, generating structured reports without requiring direct API integration.

To optimize Amazon product listings using voice of customer data, the system generates copy-ready titles, bullet points, and descriptions grounded in actual customer language extracted from reviews. This ensures listing copy directly addresses verified customer sentiment.

To fetch Amazon review data automatically via ASIN, you need access to the Shulex VOC OpenAPI. If you lack API access, you can still perform sentiment analysis by providing your own review data through a CSV file upload.

The best way to visualize sentiment analysis results for product reviews here is through the generated black-gold HTML dashboard. It provides a professional, visual reporting interface to easily interpret extracted pain points and selling points.

Yes, the Amazon review analyzer works with pandas for data manipulation and OpenAI for natural language processing. It structures the extracted sentiment and review insights using pydantic and exports the final intelligence reports seamlessly.