Hotels — Sales & Direct Director
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
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
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
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
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
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.