What the Service-recovery and compensation decision system prompt does

Act as a hotel guest-recovery governance lead, operations-risk analyst and customer-care decision designer; do not make legal determinations.

The prompt will, at minimum:

  • Validate datasets, definitions, time windows, market scope and source-of-truth ownership before assessing service-recovery and compensation decision system
  • Examine incident taxonomy, severity, safety and discrimination flags, guest impact, stay phase, service promise, evidence, repeat incidents, loyalty status, room and rate context, responsibility, recovery options, monetary and non-monetary compensation, approval limits, consistency, fraud risk, privacy, documentation, escalation, response timing and learning loop; preserve original identifiers and show the derivation of every finding
  • Segment only when evidence supports the split. Expose missingness, sample bias, seasonality, releases, campaigns, migrations and other confounders instead of hiding them in averages
  • Recompute material metrics from supplied values; disclose formulas, denominators, exclusions and scenario assumptions. Never invent benchmarks, market sizes or competitor performance
  • Turn evidence into a severity-and-authority matrix, recovery decision tree, compensation guardrails, escalation workflow, communication standards and audit register; assign owner, priority, dependency, expected signal, verification method and human-approval point to each action

Who it is for

Gökhan Güzel's hospitality prompt for ChatGPT users: marketers, founders, agencies and consultants who need an auditable, evidence-based deliverable instead of generic advice.

What you get

  • Scope, evidence and control register
  • Jurisdiction- and risk-tiered applicability matrix
  • Control-gap and submission-readiness analysis
  • Mandatory human-review and remediation checklist
  • Source, limitation, confidence and QA report

Variables

PlaceholderPurpose
{{approval_limits}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{compensation_catalog}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{complaint_cases}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{escalation_contacts}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{fraud_controls}}Approved rule, policy or constraint; state owner, version, scope, jurisdiction and effective date
{{guest_segments}}Target audience, segment, persona, customer/player or industry group
{{hotel_name}}Verified identifier or text value; state exact spelling, source, status and validity scope
{{incident_taxonomy}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{loyalty_rules}}Approved rule, policy or constraint; state owner, version, scope, jurisdiction and effective date
{{privacy_rules}}Approved rule, policy or constraint; state owner, version, scope, jurisdiction and effective date
{{response_service_levels}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{service_standards}}Approved rule, policy or constraint; state owner, version, scope, jurisdiction and effective date
{{success_metrics}}Numeric value or table; state formula, numerator, denominator, unit, currency, tax treatment, period and source
{{target_markets}}Target markets

How to use

Copy the prompt with the button above, replace every {{placeholder}} with your verified data, and paste it as the first message in a new ChatGPT conversation. The prompt runs a short question gate first; answer it, then the deliverable is produced.

Run Service-recovery and compensation decision system in ChatGPT

Open a new ChatGPT chat, paste the filled-in Service-recovery and compensation decision system prompt and answer the short question gate. ChatGPT then returns the executive decision, the evidence ledger and the task-specific tables in one reply.

Source

Original file in the multilingual prompt library on GitHub: