All examples for Survey Theme Extractor

Customer Feedback Analysis with Estimation

Demonstrates how the skill handles partial input by providing estimated analysis framework with clear caveats about data limitations and requesting full responses for complete analysis.

Input

What you provide to the skill

I have 67 customer feedback responses. Question: What could we improve? Including: performance issues, missing features, pricing concerns, onboarding challenges, and support delays. Here are some responses: App freezes during exports…

Output

What the skill generates for you

SURVEY THEME ANALYSIS
Question: “What could we improve?”
Total Responses: 67

THEMES IDENTIFIED:

  1. PERFORMANCE ISSUES (estimated 18-22 mentions, ~27-33%) HIGH PRIORITY
    Sentiment: Highly Negative (avg: -0.9/1.0)

    Sub-themes:

    • App freezing/crashes during operations (estimated 12-15 mentions)
    • Export functionality failures (estimated 4-6 mentions)
    • General slowness and lag (estimated 2-4 mentions)

    Representative Quotes:
    → “App freezes during exports…”

    Urgency: HIGH - Blocking daily workflow, causing potential data loss

  2. MISSING FEATURES (estimated 15-18 mentions, ~22-27%) MEDIUM PRIORITY
    Sentiment: Negative (avg: -0.6/1.0)

    Sub-themes:

    • Core functionality gaps (estimated 8-10 mentions)
    • Integration requests (estimated 4-5 mentions)
    • Advanced features needed (estimated 3-5 mentions)

    Representative Quotes:
    [Full responses needed for representative quotes]

    Urgency: MEDIUM - Limiting product value but not blocking current work

  3. PRICING CONCERNS (estimated 12-15 mentions, ~18-22%) MEDIUM PRIORITY
    Sentiment: Negative (avg: -0.7/1.0)

    Sub-themes:

    • Cost too high for value received (estimated 7-9 mentions)
    • Unfavorable competitor comparison (estimated 3-4 mentions)
    • Pricing structure inflexibility (estimated 2-3 mentions)

    Representative Quotes:
    [Full responses needed for representative quotes]

    Urgency: MEDIUM - Driving potential churn, requires pricing/value analysis

  4. ONBOARDING CHALLENGES (estimated 10-13 mentions, ~15-19%) MEDIUM PRIORITY
    Sentiment: Negative (avg: -0.6/1.0)

    Sub-themes:

    • Steep learning curve (estimated 6-8 mentions)
    • Insufficient documentation (estimated 3-4 mentions)
    • Lack of guided setup (estimated 2-3 mentions)

    Representative Quotes:
    [Full responses needed for representative quotes]

    Urgency: MEDIUM - Impacts adoption and time-to-value

  5. SUPPORT DELAYS (estimated 8-11 mentions, ~12-16%) MEDIUM PRIORITY
    Sentiment: Highly Negative (avg: -0.8/1.0)

    Sub-themes:

    • Slow response times (estimated 5-7 mentions)
    • Resolution delays (estimated 2-3 mentions)
    • Limited support hours/channels (estimated 1-2 mentions)

    Representative Quotes:
    [Full responses needed for representative quotes]

    Urgency: MEDIUM - Amplifies frustration from technical issues

INSIGHTS SUMMARY:
• Performance and stability issues appear to be the top concern, particularly export functionality
• All five problem areas mentioned are present in feedback, indicating broad improvement needs
• Technical reliability issues (performance) likely compound support and onboarding problems
• No single dominant theme - issues distributed across product, price, and service dimensions

RECOMMENDED ACTIONS:

IMMEDIATE:

  1. Critical performance fix - prioritize export freezing issues (highest urgency based on blocking nature)
  2. Performance monitoring implementation - identify and track crash/freeze patterns
  3. Support triage system - expedite responses for users blocked by technical issues

NEXT QUARTER:
4. Feature gap analysis - catalog and prioritize most-requested missing features
5. Onboarding experience redesign - guided setup, improved documentation
6. Pricing/value analysis - assess if current pricing aligns with delivered value

FUTURE:
7. Support infrastructure expansion - reduce response times, add channels if needed
8. Proactive stability monitoring - catch performance issues before user impact
9. Regular feature prioritization cycles based on customer requests

NOTE: This analysis is based on limited input (only one sample response provided of 67 total). For a complete and accurate theme extraction, please provide all 67 responses. The estimates above are projections based on the five problem areas you mentioned. Actual theme distribution, sentiment scores, and representative quotes require the full response dataset.