Customer Feedback Analysis

Transform raw customer feedback from NPS surveys, CSAT responses, support interactions, and app store reviews into structured insights. This skill extracts recurring themes from open-text responses, calculates quantitative score distributions, identifies emerging trends over time, and produces reports that connect customer sentiment to specific product areas and business outcomes.

Workflow

1. Collect feedback data — Aggregate feedback from all available sources: NPS survey responses (score + open text), CSAT ratings from support interactions, in-app feedback widgets, app store reviews, social media mentions, G2/Capterra reviews, and sales call notes. Tag each response with metadata: date, customer segment, plan tier, account tenure, and source channel. Ensure consistent schema across all sources.

2. Clean and normalize — Deduplicate responses from the same customer across channels. Standardize rating scales (convert 1-5 CSAT to 1-10 for cross-comparison). Strip PII from open-text responses. Handle multilingual responses by detecting language and translating to English while preserving the original. Remove bot/spam responses using pattern detection (identical text, suspicious timing, single-word noise).

3. Extract themes from open-text responses — Apply topic modeling to cluster open-text feedback into coherent themes. Common theme categories include: product reliability, ease of use, specific feature feedback, pricing/value perception, support quality, onboarding experience, and competitive comparison. Assign each response to one or more themes with a confidence score. Pull representative verbatim quotes for each theme.

4. Calculate quantitative scores — Compute aggregate metrics: NPS (% Promoters minus % Detractors), CSAT average, and theme frequency distribution. Break scores down by segment (plan tier, industry, account size, tenure) to identify which cohorts are most and least satisfied. Calculate statistical significance for segment differences to avoid acting on noise.

5. Identify trends — Compare current period metrics against previous periods (month-over-month, quarter-over-quarter). Flag themes with significant volume changes (up or down 20%+ from baseline). Detect emerging themes that appear for the first time or cross a frequency threshold. Correlate sentiment shifts with product releases, pricing changes, or market events.

6. Generate insight report — Produce a structured report with: executive summary (3-5 key takeaways), quantitative scorecard, theme breakdown with representative quotes, trend analysis, segment comparison, and recommended actions. Each recommendation should be tied to a specific theme and prioritized by frequency and business impact.

Usage