Shoupai 4 VOC Sentiment Pain-Point Scoring

Problem

Customer feedback is often scattered emotional language, making it hard to tell which issues deserve product insight. Shoupai 4 VOC Sentiment Pain-Point Scoring turns raw VOC into comparable behavioral blockers and uses quantitative scores to support prioritization instead of relying on emotional intensity alone.

How It Works

The skill processes single or batched VOC through a structured workflow:
- Five-level sentiment classification: maps statements from L1 minor complaint to L5 angry propagation, distinguishing experience, retention, churn, and brand impact.
- Pain-point extraction: requires behavior-oriented verb-object phrases such as cannot find refund entry or cannot edit shipping address, avoiding vague labels like bad experience.
- Seven-dimensional scoring: evaluates sentiment type, sentiment intensity, pain-point intensity, scenario frequency, commercial impact, pain-point value score, and insight eligibility.
- Value calculation: computes sentiment intensity × pain-point intensity × scenario frequency into a 1-125 score, then uses thresholds and commercial impact to flag demand-insight candidates.

Boundaries

It is useful for user reviews, support logs, interview notes, and open-ended survey responses. The output is table-oriented and suitable for pain-point matrices and prioritization, but it does not replace evidence review, legal judgment, or complex business modeling. For large batches, maintain consistent scoring and split inputs above 50 records.