---
title: "Hotels — Sales & Direct Director"
description: "Direct booking funnel, OTA-to-direct shift, BAR page diagnostics, country mix for direct revenue, last-minute vs early-booking distribution. Sealmetrics MCP prompts for hospitality."
canonical_url: "https://docs.sealmetrics.com/web-analytics-prompts/hotels"
lang: "en"
date_generated: "2026-08-27T14:18:06.639Z"
source_hash: "2c1fa95a279946248a4288bd1aa336da5d831b0bf4b0633bf3a95f3277bb8b47"
content_type: "documentation"
owner: "docs"
llm_priority: "useful"
source_file: "web-analytics-prompts/09-hotels.mdx"
publisher: "Sealmetrics"
---

# Hotels — Sales & Direct Director

Canonical page: https://docs.sealmetrics.com/web-analytics-prompts/hotels

Built for hotels and chains that want more direct bookings, less OTA dependency, and a clear view of country mix and pickup behavior.

**MCPs required:** Sealmetrics MCP
**Best for:** Sales & Direct Directors, Revenue Managers, Marketing Directors of hospitality groups

---

## SEAL-051 — Direct booking funnel by step and device

```text
Using Sealmetrics MCP for site {site_id} (a hotel), build the direct booking funnel for the last 30 days.

Funnel steps (adjust if my booking flow differs):
1. Landing entrance
2. Search availability (micro-conversion: search_availability)
3. View room (micro-conversion: view_room)
4. Start booking / select dates (micro-conversion: start_booking)
5. Reach payment step (micro-conversion: reach_payment)
6. Booking confirmed (macro: conversion)

Per step, return: sessions in step, % to next step, split by desktop / mobile / tablet.

Highlight the worst-performing step per device. End with one optimization hypothesis per device and a "test first" suggestion.
```

---

## SEAL-052 — BAR / rates page diagnostics

```text
For site {site_id}, query Sealmetrics MCP for the last 90 days.

Pull metrics for the BAR / rates / "best available rate" page (URL pattern: {bar_url_pattern}):
- Entrances, pageviews, bounce rate, time on page, conversion rate from this page, revenue attributed.
- Trend month by month over the last 90 days.
- Top 5 traffic sources and their CR on this page.

Compare to site averages. Flag any metric more than 30% worse than site average. End with a 3-bullet diagnosis.
```

---

## SEAL-053 — Top countries by direct conversions

```text
Using Sealmetrics MCP for site {site_id} (hotel), for the last 90 days:

Top 10 countries by direct booking conversions (utm_source = direct or null, organic, brand search):
- Country, conversions, revenue, AOV, average length of stay (if `nights` property is captured), top room type purchased.

Top 10 countries that browse but do not book (high entrances, near-zero conversions):
- Country, entrances, bounce rate, top device, top language.

End with: 3 countries to push direct campaigns to (high direct intent already), 3 countries to localize first (browsing but not booking).
```

---

## SEAL-054 — Last-minute vs early-booking distribution

```text
For site {site_id}, query Sealmetrics MCP and use the property `check_in` on macro conversions (or `days_to_check_in` if pre-computed) for the last 90 days.

Compute days-to-check-in = check_in - conversion_date. Bucket into:
- Same-day, 1-3 days, 4-7 days, 8-14 days, 15-30 days, 31-60 days, 60+ days.

For each bucket: number of bookings, total revenue, average ADR if `room_rate` is captured, top country of origin.

Compare distribution vs same period last year if data exists. Flag any bucket whose share dropped more than 5 percentage points.
End with a 3-bullet revenue-management recommendation.
```

---

## SEAL-055 — Geo mix of high-revenue direct guests

```text
Using Sealmetrics MCP for site {site_id}, for the last 6 months:

Identify the top 10 countries that generated the most direct revenue. For each: bookings, revenue, AOV, average length of stay, average days-to-check-in, dominant room type.

Build a geo-targeting brief: which 5 countries deserve a dedicated paid campaign in their language, with a specific room type as the hero, and the right booking window for the creative.

Output: 1 ranking table + 5 campaign briefs (1 per country) of 3 lines each.
```

---

## See also

- [Geography & Segmentation](./geography)
- [Product Properties (room types, length of stay)](./product-properties)
- [Forecasting (pickup curve)](./forecasting)