---
title: "Pre-arrival guest messages: AI Use Case"
description: "Send each guest a short pre-arrival message built from their booking and your approved property information, such as check-in details, directions and add-on options, so the front desk handles fewer routine questions on arrival day."
url: https://lidvizion.ai/use-cases/pre-arrival-guest-messages/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---

[Use cases](https://lidvizion.ai/use-cases/) · Customer support

# Pre-arrival guest messages

Send each guest a short pre-arrival message built from their booking and your approved property information, such as check-in details, directions and add-on options, so the front desk handles fewer routine questions on arrival day.

[Talk through this workflow](https://lidvizion.ai/contact/?need=ai-workflow&from=%2Fuse-cases%2Fpre-arrival-guest-messages%2F#write) · [Automate the repeatable](https://lidvizion.ai/services/automation/)

Where it starts

## The trigger.

A booking reaches the agreed number of days before arrival.

How it runs today

- Guests ask the same arrival questions by phone, email and chat.
- Pre-arrival emails are generic or are not sent at all.
- Special requests in booking notes are missed until check-in.

The workflow

## Four bounded steps.

Each step has an owner and a stop rule.

1. 01 / Read
   Read upcoming bookings and the approved property information for each stay type.
2. 02 / Draft
   Draft a short message with check-in details, directions and relevant options in the property’s template.
3. 03 / Flag
   Flag special requests, accessibility needs and unusual bookings for staff before anything is sent.
4. 04 / Send
   Send approved messages on schedule and route guest replies to the reservations team.

Where people stay in control

## Approval points.

- Staff handle special requests, accessibility needs and any booking changes.
- Messages use only approved property information and the guest’s own booking details.

How we would measure it

## Against a baseline.

Measured before and after, on the same work.

### Routine arrival questions per stay.

### Share of bookings that receive a pre-arrival message on time.

### Special requests flagged before arrival day.

Related

## Go deeper.

- [Automate the repeatable](https://lidvizion.ai/services/automation/): Give recurring work an owner, a trigger, and a stop rule.
- [Client vs. server: where code runs](https://lidvizion.ai/resources/basics/backend-client-vs-server/): What belongs in the browser or app, and what must stay on a server you control.
- [Send better pre-arrival messages](https://lidvizion.ai/guides/send-better-pre-arrival-messages/): A four-step playbook to write approved message templates, draft each guest’s message from their booking, flag special requests for staff and cut routine arrival questions.
- [How to send pre-arrival guest messages with AI](https://lidvizion.ai/answers/how-to-send-pre-arrival-guest-messages-with-ai/): How can a hotel or rental operator use AI to send every guest a useful message before arrival without missing special requests?

More use cases

## Other places to start.

[All use cases](https://lidvizion.ai/use-cases/)

- [Support triage and reply drafts](https://lidvizion.ai/use-cases/support-triage/): Customer support Classify incoming tickets, find the relevant answer, and draft a reply for an agent to check.
- [At-risk customer alerts](https://lidvizion.ai/use-cases/at-risk-customer-alerts/): Customer support Spot customers who may be about to leave from support tickets, usage and account notes, and give the account owner a short summary to act on.
- [Return and refund requests](https://lidvizion.ai/use-cases/return-and-refund-requests/): Customer support Check each return or refund request against your policy and order records, prepare the response and the system updates, and send anything outside policy to a person.

An illustrative workflow pattern, not a result from a specific customer.

Bring the messy version

## One workflow. A better way to run it.

Show us the tools, the handoffs, and the part that keeps slowing your team down.

[Let’s map your workflow](https://lidvizion.ai/contact/) · [Read our approach](https://lidvizion.ai/approach/)