Extracting Review Keywords from Hubbuycn’s Purchased Products in Spreadsheets for Product Optimization
With the growing demand for international shopping, Hubbuycn has become a trusted platform for agency purchasing services. To enhance product competitiveness, it is essential to analyze customer reviews systematically and extract actionable insights. This article demonstrates how text mining technology in spreadsheets can be used to identify key evaluation keywords, assess user concerns, and guide product improvements.
1. Data Collection and Text Mining in Spreadsheets
Customer feedback from Hubbuycn’s agency purchases can be collected and structured in spreadsheets for analysis. Using built-in functions ( Key focus areas derived from sentiment-tagged keywords may include: Automated analysis via add-ons like Google Sheets’ Natural Language API
Conclusion:
SPLIT, TRIM, LOWER), keyword frequency can be extracted and filtered to identify prevalent terms. Advanced methods like TF-IDF (Term Frequency-Inverse Document Frequency)
Example (Google Sheets formula for keyword counting):
=ArrayFormula(COUNTIF(LOWER(A2:A100),"*shipping*"))2. Identifying User Concerns and Product Advantages
Positive Feedback (Strengths):
Negative Feedback (Improvement Opportunities):
3. Market Comparison and Optimization Strategies
Evaluation Keyword
Industry Benchmark
Recommended Action
"Shipping time"
≤7 days (Premium competitors)
Partner express couriers; track delivery ETAs.
"Product manual missing"
100% inclusion (Standard)
Quality checks for accessories.
"Customs hassle"
DDP (Delivered Duty Paid) options
Offer tax-inclusive pricing tiers.
4. Implementing AI & Consistency Checks
5. Future Optimization Roadmap