Sentiment Analysis of AliExpress Product Reviews in Spreadsheets and Exploring Product Improvement Directions
Introduction
In the era of e-commerce, customer reviews play a crucial role in determining the success of a product. Platforms like AliExpressspreadsheetstext analysis tools
Step 1: Importing AliExpress Review Data into Spreadsheets
AliExpress allows sellers to export customer reviews in formats compatible with spreadsheet tools like Microsoft ExcelGoogle Sheets. The raw data typically includes:
- Product ratings (1-5 stars)
- Review text
- Date of review
- User demographics (if available)
Once imported, the data can be preprocessed by removing duplicates, irrelevant text (e.g., "Verified purchase"), and handling missing values.
Step 2: Performing Sentiment Analysis
Using Built-in and Third-Party Text Analysis Tools
Popular spreadsheet tools support sentiment analysis through either built-in functions or third-party add-ons:
- Google Sheets (via Apps Script/Add-ons):LexalyticsGPT-powered sentiment analysis, classify reviews into
Positive
,Neutral
, orNegative
. - Excel:xlwings) for more advanced classifications.
Example in Google Sheets:
=IF(STAR_RATING 3, "Positive", IF(STAR_RATING 2, "Neutral", "Negative"))
For finer granularity, implement an algorithm like TextBlobVADER
Step 3: Extracting Keywords and Themes
Lexical Frequency Analysis:Datawrapper
- "High quality," "fast delivery" (Common in positive reviews).
- "Defective," "not as described" (Frequent negatives).
Pro Tip:
Step 4: From Insights to Product Improvement
Translating findings into tangible improvements involves:
- Satisfaction-Driven Enhancements:
- Addressing Pain Points:"battery life"
Sentiment | Keyword | Action Plan |
---|---|---|
Negative (15%) | "difficult assembly" | Redesign packaging with clear setup instructions. |
Positive (40%) | "comfortable material" | Highlight this attribute in product descriptions. |
Conclusion
By systematically analyzing AliExpress reviews
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