Sentiment Analysis of AliExpress Product Reviews in Spreadsheets and Its Role in Product Improvement
2025-04-26
In the era of e-commerce, customer feedback serves as a goldmine of insights for product optimization. This article explores how to leverage sentiment analysis tools within spreadsheets to analyze AliExpress product reviews, extract actionable data, and guide product development.
Step 1: Importing Review Data into Spreadsheets
Begin by exporting AliExpress product reviews (CSV/Excel format) and importing them into spreadsheet tools like Google Sheets or Microsoft Excel. Structure columns to include:
- Review Text
- Product ID/Variation
- Rating
Step 2: Text Mining & Sentiment Analysis
Tools Used:
- Google Sheets add-ons (e.g., Lexicon-based sentiment analyzers)
- Custom scripts (Python/Apps Script for advanced NLP)
Key Processes:
- Keyword Extraction: Identify高频 terms (e.g., "durable," "shipping delay") using TF-IDF or Word Clouds.
- Sentiment Scoring: Categorize reviews as Positive, Neutral, or Negative
- Theme Tagging: Manual labeling for recurring topics (e.g., "packaging", "battery life").
Step 3: Deriving Actionable Insights
| Sentiment | Top Keywords | Product Improvement Direction |
|---|---|---|
| Positive (4-5★) | "value for money", "fast delivery" | Enhance marketing of强项 features |
| Negative (1-3★) | "size difference", "poor instructions" | Redesign sizing charts, improve manuals |
Turning Data into Product Strategy
Sentiment analysis transforms subjective reviews into objective improvement metrics. By:
- Prioritizing
- Iterating
Businesses can systematically enhance product-market fit and复购率.