DoctorClaw Feedback Digest

Customer feedback digest — collect, categorize, and summarize reviews, survey responses, and support tickets. Weekly cron or on-demand.

Customer Feedback Digest

Listen to your customers without drowning in data. This skill collects feedback from reviews, surveys, support tickets, and social mentions — then categorizes it by sentiment, topic, and urgency so you know exactly what to fix, what to celebrate, and what to respond to.

Run it weekly for a full digest, or trigger on-demand after a product launch or campaign.

What You Get

• All feedback categorized by sentiment (positive, neutral, negative, critical)
• Topics extracted and ranked by frequency (feature requests, bugs, praise, complaints)
• Urgent issues flagged for immediate response
• Suggested responses for negative reviews
• Trend analysis showing sentiment shifts over time
• Highlight reel of your best customer quotes

Setup

Required

• Feedback source — At least one: review platform data (CSV export), survey responses, support tickets, or social mentions your agent can access

Optional (but recommended)

• Multiple sources — combine Google Reviews, app store reviews, support emails, survey tools
• Response access — ability to reply to reviews or tickets after your approval
• Delivery channel — Telegram/Discord for digest and urgent alerts
• Feedback archive — folder to store historical digests for trend tracking

Configuration

Tell your agent:

1. Feedback sources — where to pull feedback from (file paths, URLs, integrations)
2. Review schedule — when to compile the digest (default: every Monday)
3. Response style — your tone for responding to reviews (grateful, professional, empathetic)
4. Urgency triggers — what counts as urgent (1-star reviews, keywords like "refund", "broken", "unsubscribe")
5. Delivery — where to send the digest
6. Product/service context — what you sell, so the agent understands the feedback properly

How It Works

Step 1: Collect Feedback

• Pull feedback from all configured sources
• For each piece: source, date, author (if available), content, rating (if applicable)
• Normalize ratings across sources (stars → sentiment score)

Step 2: Analyze Sentiment

Categorize each piece of feedback:

🟢 POSITIVE — Happy customers

• 4-5 star reviews, compliments, thank-you messages
• Keywords: love, great, amazing, helpful, recommend, best

🟡 NEUTRAL — Mixed or informational

• 3-star reviews, feature requests without complaint, questions
• Neither strongly positive nor negative

🔴 NEGATIVE — Unhappy customers

• 1-2 star reviews, complaints, frustration
• Keywords: disappointed, frustrated, doesn't work, waste, overpriced

⚫ CRITICAL — Needs immediate attention

• Threats to churn, refund requests, public complaints, legal mentions
• Keywords: refund, cancel, lawyer, scam, report, BBB

Step 3: Extract Topics

Group feedback by recurring themes:

• Feature requests — things customers want added
• Bugs/issues — things that are broken or confusing
• Praise points — what customers love most (keep doing this)
• Pain points — recurring frustrations
• Competitive mentions — when customers compare you to competitors

Rank by frequency — most-mentioned topics first.

Step 4: Draft Responses

For NEGATIVE and CRITICAL feedback, draft responses:

• Acknowledge the issue specifically
• Apologize where appropriate
• Offer a solution or next step
• Match the configured response style
• Mark as DRAFT — never post without approval

Step 5: Compile Digest

text

⭐ Feedback Digest — [Date Range]

📊 SENTIMENT OVERVIEW
Total feedback: [X] pieces
🟢 Positive: [X] ([X]%) | 🟡 Neutral: [X] ([X]%)
🔴 Negative: [X] ([X]%) | ⚫ Critical: [X]
Average rating: [X.X] / 5.0

⚫ CRITICAL — RESPOND NOW ([X])
1. [Source] — [Author]: "[excerpt]"
   📝 Suggested response: "[draft]"

🔴 NEGATIVE HIGHLIGHTS ([X])
2. [Source] — "[excerpt]"
   Topic: [bug/complaint/pricing]
   📝 Suggested response ready

🔥 TOP TOPICS THIS WEEK
1. [Topic] — mentioned [X] times ([sentiment breakdown])
2. [Topic] — mentioned [X] times
3. [Topic] — mentioned [X] times

💚 BEST QUOTES (use in marketing!)
• "[Great quote from happy customer]" — [Author]
• "[Another great quote]" — [Author]

📈 TRENDS
• Sentiment [up/down] [X]% vs last period
• New topic emerging: [topic]
• Recurring issue: [issue] — [X] mentions this month

💡 RECOMMENDATIONS
• [Fix X — 8 negative mentions this week]
• [Feature Y requested by 5 customers — consider adding]
• [Reply to critical reviews within 24 hours]

Step 6: Deliver & Archive

• Send digest via configured channel
• Critical items get immediate alerts (don't wait for weekly digest)
• Save to memory/feedback/YYYY-MM-DD.md
• Track response status (drafted → approved → posted)

Examples

User: "Show me this week's customer feedback"

Agent compiles and responds with the full digest.

User: "What are customers complaining about most?"

Agent:

Top complaints this week:

1. Onboarding confusion — 6 mentions. Customers struggling with initial setup.
2. Slow response times — 4 mentions. Support taking 48+ hours.
3. Pricing clarity — 3 mentions. Confusion about what's included in each tier.

Recommendation: Create an onboarding guide or video — this alone would address 40% of negative feedback.

User: "Send response to the critical review"

Agent: Posts the approved response to the review platform.

Customization Ideas

• NPS tracking — run periodic NPS surveys and track scores over time
• Review request automation — after positive interactions, auto-send review requests to happy customers
• Feedback-to-feature pipeline — auto-create feature request tickets from customer suggestions
• Competitor review monitoring — track what customers say about competitors too
• Testimonial collector — auto-curate the best quotes for marketing use

Want More?

This skill handles feedback collection and analysis. But if you want:

• Custom integrations — connect to Trustpilot, G2, Intercom, Zendesk, or your specific review platforms
• Advanced automations — auto-respond to reviews, trigger NPS surveys, feed insights into product roadmap
• Full system setup — identity, memory, security, and 5 custom automations built specifically for your workflow

DoctorClaw sets up complete OpenClaw systems for businesses:

• Guided Setup ($495) — 2-hour live walkthrough. Everything configured, integrated, and running by the end of the call.
• Done-For-You ($1,995) — 7-day custom build. 5 automations, 3 integrations, full security, 30-day support. You do nothing except answer a short intake form.

→ doctorclaw.ceo