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How Aspect-based sentiment analysis Helped Reduce Customer Return Reasons Across European E-Commerce Stores

Oct 13, 2026,

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Project Overview

European e-commerce brands were experiencing recurring product returns but lacked detailed visibility into the customer issues driving those decisions. Aspect-based sentiment provided a structured approach to identify product-level concerns from customer feedback, analysis helping businesses distinguish issues related to quality, sizing, packaging, delivery, features, and overall product expectations.

Actowiz Metrics combined review intelligence with E-commerce & D2C analytics to transform unstructured customer opinions into actionable insights. The solution helped identify recurring return drivers, compare sentiment across product aspects, and prioritize improvements. This enabled e-commerce teams to make informed decisions around product quality, descriptions, assortment, and customer experience.

Project Overview

Key Highlights

Key Highlights
  • Return Drivers: Identified recurring customer concerns associated with product quality, sizing, usability, packaging, and expectations.
  • Review Insights: Applied E-Commerce Return Reason Analysis to classify feedback and identify dominant product-related return patterns.
  • Product Diagnosis: Performed Aspect-level analysis of customer feedback for product returns to isolate specific dissatisfaction drivers.
  • Data Extraction: Used scrape customer reviews to analyze product return reasons for structured customer feedback intelligence.
  • Actionable Intelligence: Combined aspect-based analysis of product reviews and return reasons with Customer Feedback Data Collection and Customer Feedback Analysis.
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