Agent-Skills.md

Agent Skills: Review Management

Optimize review scores and leverage user-generated content for AI visibility and brand trust. Use when building review presence across platforms, improving review response rates, or leveraging reviews for AI recommendation signals. Covers target metrics and platform prioritization.

UncategorizedID: majesticlabs-dev/majestic-marketplace/review-management

Repository

majesticlabs-dev/majestic-marketplace
majesticlabs-devLicense: NOASSERTION
327

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pnpm dlx add-skill https://github.com/majesticlabs-dev/majestic-marketplace/tree/HEAD/plugins/majestic-marketing/skills/seo/review-management

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plugins/majestic-marketing/skills/seo/review-management/SKILL.md

Skill Metadata

Name
review-management
Description
Optimize review scores and leverage user-generated content for AI visibility and brand trust. Use when building review presence across platforms, improving review response rates, or leveraging reviews for AI recommendation signals. Covers target metrics and platform prioritization.

Review Management

Frameworks for building review presence that influences AI recommendations.

Target Metrics

| Metric | Minimum | Target | Strong | |--------|---------|--------|--------| | Score | 3.5/5 | 4.0/5 | 4.5+/5 | | Volume | 10+ | 50+ | 100+ | | Recency | 6 months | 3 months | 1 month | | Response rate | 50% | 75% | 90%+ |

Platform Priority

B2B Software

  1. G2 (highest AI weight)
  2. Capterra
  3. TrustRadius
  4. Gartner Peer Insights

B2C / E-commerce

  1. Google Business Profile
  2. TrustPilot
  3. Yelp
  4. Amazon (if applicable)

Local Businesses

  1. Google Business Profile
  2. Yelp
  3. Industry-specific directories
  4. Facebook

Feature-Rich Reviews

AI heavily weights UGC that teaches WHAT products do.

Review Prompts That Work

| Prompt | Purpose | |--------|---------| | "Which specific feature helped you most?" | Feature mentions | | "What problem did [Product] solve?" | Use case context | | "How does it compare to alternatives?" | Competitive context | | "What results have you seen?" | Outcome data |

Strong vs Weak Reviews

| Weak (Low AI Value) | Strong (High AI Value) | |---------------------|------------------------| | "Great product!" | "The automated lead scoring saved us 10 hours/week" | | "Highly recommend" | "Switched from Salesforce because [specific reason]" | | "5 stars" | "The [Feature] feature helped us [specific outcome]" |

Review Request Strategy

Timing

| Trigger | Timing | Message | |---------|--------|---------| | Onboarding complete | Day 30 | "How's your experience so far?" | | Feature adoption | After key feature use | "How is [Feature] working for you?" | | Milestone achieved | After success | "Would you share your results?" | | Renewal | At renewal | "Help others find us" |

Request Template

Hi [Name],

Congrats on [specific achievement with product]!

Would you share your experience on [Platform]? Specifically:
- What problem did [Product] solve for you?
- Which feature has been most valuable?
- What results have you seen?

Here's the direct link: [URL]

Takes 3 minutes and helps teams like yours find us.

Thanks,
[Your name]

Response Strategy

Positive Reviews

  • Thank specifically for details mentioned
  • Reinforce key triplets naturally
  • Mention upcoming features if relevant

Negative Reviews

  • Respond within 24 hours
  • Acknowledge the issue
  • Offer resolution path
  • Follow up after resolution

Response Template (Negative)

Hi [Name],

Thank you for sharing this feedback. I'm sorry [specific issue]
impacted your experience.

[Specific action taken or offered]

If you'd like to discuss further, please reach out to [contact].
We're committed to [relevant triplet about quality/service].

[Name], [Title]

Score Recovery

If score is below 3.5:

  1. Analyze - Identify themes in negative reviews
  2. Fix - Address root causes
  3. Reach out - Contact unhappy reviewers with fixes
  4. Request updates - Ask for updated reviews
  5. Dilute - Actively request from happy customers

AI Citation Impact

| Review Element | AI Learning | |----------------|-------------| | Feature mentions | What product does | | Use cases | Who product is for | | Comparisons | Competitive positioning | | Outcomes | Value proposition | | Industry context | Target market |

Reviews teach AI about your product. Volume + quality = citation likelihood.