Overview

Amazon's Voice of the Customer (VOC) dashboard includes a powerful diagnostic feature called Root Cause Insights, which uses machine learning to analyze customer feedback and surface the specific reasons behind negative product experiences. For sellers managing product quality and listing accuracy, understanding these root cause definitions is essential for quickly identifying and resolving the issues that drive returns, negative reviews, and potential listing suppression.

Key Points / What Sellers Need to Know

• Machine learning-driven analysis — Amazon uses automated summarization models to group customer complaints into specific root cause categories, giving sellers a structured view of what's going wrong with their products.
• Not always available — Root cause insights only appear when Amazon's model can confidently map customer feedback to a defined category. Some listings may not display granular root causes if the data is insufficient or ambiguous.
• Directly tied to customer feedback — These insights are derived from actual buyer comments and complaints, not from Amazon's internal assessments, making them a reliable signal of real customer experience.
• Covers dozens of categories — Root causes span everything from product authenticity and quality concerns to packaging damage, missing parts, and misleading advertising.
• Actionable for quality improvement — Each root cause category points to a specific area sellers can investigate and improve, whether that means adjusting supplier standards, updating listings, or improving packaging.

Root Cause Categories Explained

Amazon organizes root cause insights into a comprehensive set of categories that cover virtually every type of product complaint a seller might encounter. Appearance issues flag situations where a customer is dissatisfied with how a product looks — not because of damage, but because the product's visual presentation didn't meet expectations. Authenticity concerns arise when customers question whether a product is genuine, with a separate category specifically for books and media. include broad assessments like "bad quality" (covering thin, poorly made, or wobbly products) as well as more specific issues like material quality, durability complaints where products don't last, and general craftsmanship concerns.