Reputation Intelligence

Tier 3 – Manual Data Input

• User-pasted review text with platform source and date
• Exported reputation tool reports
• Internal feedback submissions
• Survey data uploads

Required Data Elements

• Review text (full comment or summary)
• Numeric rating (1–5 scale or platform equivalent)
• Platform source (TripAdvisor, Google, Booking.com, Expedia, direct/internal)
• Review date
• Guest name (optional, often masked by platforms)
• Department impacted (inferred from text or specified)

Property Context

Before analysis begins, establish property context:

• Brand Promise: property positioning (luxury, upscale, select-service, economy)
• Property Type: full-service hotel, resort, extended stay, boutique, etc.
• Service Level: determines tone and depth of response (luxury responses are warmer and personal; select-service are efficient and action-focused)
• Comp Set: competitor properties for benchmarking
• Staff Messaging: brand voice, typical response tone for management replies
• Recent Initiatives: ongoing renovations, staffing changes, service launches (context for trend analysis)

Role-Specific Intelligence

General Manager

• Weekly reputation trend briefing (rating trajectory, emerging issues by department)
• Urgent alerts (safety, cleanliness, legal liability, discrimination)
• Competitive benchmarking vs. comp set properties

Director of Sales & Marketing

• Competitive reputation positioning (how property ranks vs. market)
• Sentiment themes driving bookings (pool, location, amenities)
• Positive review highlights for marketing asset generation

Operations & Department Heads

• Department-specific feedback trends (e.g., front desk speed, housekeeping cleanliness, F&B quality)
• Root cause analysis for negative patterns (e.g., AC noise in building 2 = HVAC maintenance issue)
• Actionable improvement recommendations

Core Analysis Framework

1. Review Categorization

Classify each review across three dimensions:

Department Attribution

• Front Desk / Check-in
• Housekeeping / Cleanliness
• Food & Beverage
• Maintenance / Facilities
• Pool / Spa / Recreation
• Parking / Valet
• Concierge / Guest Services
• Leadership / Overall
• Other

Sentiment Classification

• Positive: 4–5 stars, praises specific experience(s)
• Negative: 1–2 stars, complains about specific issue(s)
• Mixed: 3 stars or contains both praise and criticism

Thematic Tags

• Cleanliness, Noise, Staffing, Amenities, Location, Value, Safety, Responsiveness, Decor, Technology, Breakfast, Valet Service, Noise (specify source: AC, neighbors, traffic), etc.

2. Trend Detection

Trailing 90-Day Analysis

• Track average rating by platform (TripAdvisor, Google, Booking.com, Expedia)
• Identify rating trajectory (improving, declining, stable)
• Flag emerging patterns: 3+ mentions of same issue = potential systemic problem
• Compare recency-weighted sentiment (recent reviews weighted higher)
• Detect seasonal patterns vs. structural issues

3. Urgent Flags

Escalate immediately to GM and ownership:

• Safety Concerns: injury, theft, assault, break-in
• Cleanliness Crisis: bed bugs, mold, pests, hygiene violations
• Discrimination or Harassment: guest feels unsafe or unwelcome
• Health Code Violations: food poisoning, health inspector findings
• Legal Liability Exposure: slip-and-fall, property damage claims
• Breach of Confidentiality: staff named or operational secrets exposed

4. Competitive Benchmarking

• Compare property's average rating to comp set on same platform
• Identify competitor strengths (e.g., "competitor A has better parking reviews")
• Assess market position (leader, challenger, follower in reputation category)
• Highlight competitive vulnerabilities to address

5. Sentiment Scoring

Weight by platform authority and recency:

• High Authority: Google (local search), TripAdvisor (independent travelers)
• Medium Authority: Booking.com, Expedia (OTA platforms)
• Recency Multiplier: reviews <7 days old = 1.5x weight; <30 days = 1.2x; >90 days = 0.5x

Management Response Framework

Core Principles

• Tone: Empathetic, professional, never defensive, never templated
• Specificity: Reference the exact experience mentioned in the review (names of dishes, room number if disclosed, specific service issue)
• Accountability: Take responsibility where appropriate; avoid blame-shifting
• Action: Describe specific corrective action taken or planned (not generic apologies)
• Calibration: Match property tier (luxury = personal warmth; select-service = efficient, direct)
• Confidentiality: Never reveal staff names (unless positive), compensation details, or sensitive operational info

Response Structure

1. Acknowledgment: "Thank you for taking the time to share your feedback about [specific experience]."
2. Validation: "We understand [specific concern], and we take that seriously."
3. Ownership: "We fell short of [brand promise], and that's on us." (for negative reviews)
4. Corrective Action: "We have already [specific action taken] and [future action planned]."
5. Recovery: "We'd love the opportunity to restore your confidence. Please contact [GM/manager name] at [direct contact]." (negative reviews only)
6. Gratitude: "Thank you for choosing [property name]." (positive reviews: reinforce brand promise)

Response Calibration

Luxury Property Response

• Warmer, more personal tone
• Reference specific amenity or service experience
• Invite direct relationship with GM
• Offer specific recovery experience

Select-Service Property Response

• Efficient, direct, friendly
• Brief acknowledgment and action
• Simple contact method
• Focus on resolution

Negative Review Response (Key Rules)

• Always include a specific recovery action (never generic "we're sorry")
• Name a recovery opportunity (complimentary upgrade, amenity credit, meal on us)
• Provide direct contact to decision-maker (GM, DOSM, operations manager)
• Avoid deflection or excuses
• Acknowledge impact on guest experience

Positive Review Response (Key Rules)

• Thank specifically for what they mentioned (don't be generic)
• Reinforce the brand promise they experienced
• Invite return visit or engagement
• Keep response brief (don't overshadow their positive sentiment)

Response Priority

1. Critical: Urgent flags (safety, legal, cleanliness crisis) — respond within 24 hours
2. High: Recent negative reviews (last 7 days) — respond within 48 hours
3. Medium: Older negative reviews (8–30 days) — respond within 5 business days
4. Low: Positive reviews (maintain brand voice) — respond within 2 weeks

Output Formats

Daily Review Digest

• New reviews in past 24 hours by platform
• Sentiment classification (positive/negative/mixed) with flag icons
• Department attribution and thematic tags
• Draft management response for each review requiring response
• Escalation flags for urgent issues

Weekly Reputation Briefing

• Rating trend analysis by platform (chart of 90-day trajectory)
• Department performance scorecard (average sentiment score by department)
• Emerging issues (patterns detected, root causes suggested)
• Competitive benchmarking summary
• Response rate and quality metrics (% of reviews responded to, avg response time)
• Action items (staffing, training, infrastructure improvements)

Monthly Report

• Comprehensive review analytics (volume, sentiment distribution, rating trends)
• Department deep-dives (top strengths, improvement areas)
• Competitive market analysis
• Emerging themes and systemic issues
• Management response effectiveness (guest replies to responses)
• Strategic recommendations for owner reporting

Response Queue

• Prioritized list of reviews requiring management response
• Draft responses (ready-to-edit)
• Escalation flags (urgent, legal, safety concerns)
• Response owner assignment (GM, DOSM, department manager)
• Target response deadline

Brand Integrity

HospitalityOS™ Guest Review & Reputation Intelligence Skill is a proprietary service of HospitalityOS, Inc. All analysis, response frameworks, and competitive benchmarking data remain confidential to the property operator.

v1.0.0 | Skill created for HospitalityOS™ Hotel Intelligence Suite