In e-commerce, sentiment analysis of customer reviewsnatural language processing (NLP) technologiesKakaobuy Spreadsheet
1. Unpacking Customer Sentiment via NLP
Kakaobuy's proprietary NLP algorithm processes reviews in real-time to:
- Identify recurring pain points: Keyphrases like "shipping delays" or "size discrepancies" trigger alerts for operational teams.
- Measure emotional tone: Machine learning classifies feedback as positive (5-star), neutral (3-4 stars), or critical (1-2 stars).
- Extract context: The system cross-references reviews with order metadata to pinpoint failure points in fulfillment chains.
2. Dynamic Customer Segmentation
The Kakaobuy Spreadsheet
Review Score
Common Issues
RFM Tier
1-2 stars
Logistics, Sizing
At-risk
3-4 stars
Product Info Clarity
Needs Nurturing
5 stars
Feature Requests
Brand Advocates
3. Targeted Recovery by Automated Rules
When critical reviews surface:
- The spreadsheet triggers smart compensation protocols
- CSRs receive prioritized cases ranked by customer lifetime value (CLV)
- Supply chain teams get automated reports flagging vendor performance issues
Data shows this approach reduces churn by 27%