Diagnose
Map the booking journey end to end, audit search and paid visibility, and establish what the current data can and cannot prove.
Case Study
Sabre Hospitality: Before and After Direct Booking
A hotel technology partnership that moved a portfolio from fragmented, OTA-dependent distribution to a single, measurable direct-booking journey connected to live rate and inventory data.
Client
Sabre Hospitality
Industry
Hotel technology and distribution
Scope
Hotel SEO, website and booking experience, advertising, analytics
Focus
Direct booking growth and channel-mix control
THE RESULTS
Before and After
The same portfolio, the same properties and the same guests—what changed was the path from search to confirmed reservation.
Before
- Direct bookings depended on a fragmented path across the brand site, OTA listings and the reservations call centre, with no single view of what a direct booking actually cost.
- Paid search competed against OTA bids on the portfolio’s own brand and property names, so a large share of media budget re-bought demand the hotels already owned.
- Property, room and package pages carried thin, duplicated copy that answered neither guest questions nor search intent.
- Tracking stopped at the booking-engine handoff, so revenue and marketing teams could not connect campaigns to confirmed reservations.
- AI assistants and answer engines described the properties using outdated third-party details instead of the hotels’ own facts.
After
- One direct-booking journey from search to confirmation, aligned with live rate and inventory data from the central reservation system.
- Brand and property terms defended, with incremental demand captured across Google Hotel Ads, metasearch and paid search at a lower cost per direct booking.
- Room-, rate- and package-level content built from real guest search demand and property-specific detail.
- End-to-end measurement from ad click to confirmed reservation, with cost per direct booking and revenue reported alongside channel mix.
- Clean entity and structured hotel data so search engines and AI answers cite the property’s own rates, amenities and location.
| Measure | Before | After |
|---|---|---|
| Direct booking share of room nights | Secondary to OTA channels | Primary direct channel |
| Cost per direct booking | Unmeasured at the booking-engine handoff | Tracked to confirmed reservations |
| Branded search coverage | Shared with OTA listings | Owned by the property |
| Booking-engine conversion rate | Friction and drop-off between search and checkout | A single, tested booking path |
| Channel-mix visibility | Reports ended at the click | Revenue and room nights by source |
How the Work Unfolded
Five phases, sequenced so measurement existed before budget was scaled.
Fix the foundation
Repair technical and tracking gaps so rates, availability and confirmed reservations can be attributed to the campaigns and pages that produced them.
Rebuild the direct path
Rework property, room and package content, booking-engine handoff and mobile experience around real guest questions.
Capture and defend demand
Restructure search and paid media around brand defence, destination demand and metasearch, with OTA cannibalisation monitored.
Measure and refine
Report cost per direct booking, channel mix and revenue influence, then adjust budgets and content against confirmed results.
Figures shown reflect the measures tracked through this engagement. Verified performance detail is available on request during a marketing analysis.
Direct bookings. Measurable revenue.