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Guest service / Vendor example

Triage guest messages before the front desk replies

Turn incoming requests into draft answers, service tasks, and a short escalation queue.

Approved AI assistantBeginnerOriginal editorial guide

What you’ll produce

A review queue with intent, urgency, source policy, draft response, and assigned department.

Inputs & connections

  • A small set of redacted guest requests
  • Current property FAQ and department escalation rules

Begin with approved exports or pasted source material. Live access requires separately configured integrations and permissions; this guide does not install them.

Your starting prompt

Replace the bracketed fields. This is our suggested prompt, not a quote from the source.

Review these guest requests for [property] using only [approved FAQ]. For each, return intent, urgency, relevant policy reference, suggested department, and a draft response. Mark missing facts as unknown. Escalate safety issues, complaints, refunds, and policy exceptions to staff. Do not send messages or create service commitments. Keep the guest's actual request beside your interpretation.

How to run it

  1. 01

    Choose twenty historical requests and label the correct action with the front-desk lead.

  2. 02

    Provide the current FAQ with version dates and an explicit escalation list.

  3. 03

    Run the sample and compare answers and routing with the staff labels.

  4. 04

    Allow drafts into a staff queue only after correcting recurring errors.

KEEP A PERSON IN THE LOOP

Review before you act

Front-desk staff check policy accuracy, tone, urgency, and room-specific facts before replying.

Limitations & success checks

  • A plausible answer can still quote an outdated policy.
  • Languages, PMS access, and live ticket creation depend on the implementation.

Measure: Missed escalations, factual corrections per draft, and staff review time.

Sources & attribution

The sources below support the reported example or a tool capability. They do not validate our prompt or prove the outcome in your environment.

Vendor exampleAI guest messaging ↗

Vendor describes guest answers, translation, service tickets, and staff handoff. Our prompt and review process are editorial additions.

Creator / publisher: Canary Technologies

Practitioner reportBooking.com partner agent for guest inquiries — X post ↗

The visible X post reports an agent helping Booking.com accommodation partners respond to guest inquiries. The public embed truncates further details; it does not establish routing features, accuracy, or savings. The prompt and escalation checks here are our editorial additions.

Creator / publisher: Victoria Slocum

Editorial review: 2026-10-12. How we label evidence.

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