Sentiment Analysis of AliExpress Product Reviews in Spreadsheets and Product Improvement Strategies

2025-04-22
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Introduction

In today's competitive e-commerce landscape, customer feedback holds immense value in shaping product development. This paper explores how businesses can leverage AliExpress review data

Methodology

1. Data Collection

Export product reviews from AliExpress to CSVExcel

  • Date, product SKU
  • Star ratings (1-5)
  • Review text in original language + English translation

2. Sentiment Analysis

Utilize spreadsheet add-ons like:

  • Google Sheets' Natural Language API
  • Azure Text Analytics

Automatically classify sentiment scores and extract positive/negative keywords

Key Findings Interpretation

Case Example: Bluetooth Headphones (1,287 reviews)

Trait Pos. Mentions Criticism Keywords
Sound Quality 78% (4-5★) "bass weak", "tinny"
Battery Life 62% (3-5★) "dies fast", "overstated"
Sample breakdown showing priority improvement areas

Implementation Framework

  1. Feature Prioritization Matrix

    Plot frequent complaints against technical feasibility to create an action plan

  2. A/B Testing Integration

    Use sentiment trends to validate design changes in subsequent product batches

Conclusion

By systematically analyzing review sentiments in accessible tools like Google Sheets, manufacturers can transform qualitative feedback into:

  • 20-30% reduction in common product complaints
  • Specific R&D focus areas
  • Data-backed marketing claims (e.g. "Improved battery based on 900+ user reviews")
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