Metropolitan chain hotel: 87 products from 150 rooms and apartments
150 rooms and apartments, ten PMS categories, 87 ways to sell them. This anonymised chain hotel in a major city shows how an established room portfolio can serve different guest needs without adding physical inventory.
Around €5.20 in additional premium per online booking
The revenue snapshot covers 774 direct online bookings. This online channel represented 9% of the property's booking mix. Averaged across all those online bookings, including bookings without a premium, the recorded additional premium was around €5.20 per booking.
For every 100 online bookings, around 54 were individualised feature or experience products and 46 were plain categories. Of those 54 individualised bookings, around 36 sold above the relevant category price. Roughly two thirds of individualised product bookings therefore carried a room-feature premium, averaging €13 on those bookings.
Per 100 online bookings: around €473 in room-feature premiums plus €45 from increased additional-service upselling above that of comparable category bookings. Combined: around €518 in additional premiums.
Regular category upgrades and the usual sales of additional services come on top. The figures here measure the additional premiums.
More than a room-feature selector
Around 55% of the individualised product bookings were experience products; the remaining 45% were feature-based products. Guests used both ways of buying the same underlying inventory.
That matters for a chain hotel. Selling individually does not require every guest to configure a room feature by feature. A product can bring together the characteristics that fit a particular stay, while other guests can select the details that matter to them.
Couples looked for different sleeping arrangements and a quieter room
In the supplementary guest analysis, twin beds appeared in couples' bookings around 150% more frequently than in the average booking. Particularly quiet rooms and the double-bedroom layout appeared around 120% more frequently.
A couple is not one fixed set of preferences. The hotel can present sleeping arrangements and room location clearly, giving guests a choice that a broad category name cannot explain on its own.
The feature analysis also distinguishes attributes that guests actively selected from those included in a booked product. That gives the team evidence for deciding what to highlight, rather than treating every feature in a reservation as a deliberate request.
59% booked last-minute; others planned six weeks ahead
Around 59% of bookings in the guest analysis were last-minute. Solo travellers booked 18 days ahead on average; couples booked 42 days ahead. The same property served both short-notice demand and guests planning well in advance.
That suggests two useful sales entry points: an immediately bookable stay for guests making a quick decision, and a more specific room product for guests who want to secure their preferred setup early.
Around 20% of guests in this analysis were returning guests. A familiar property can still offer a more relevant stay: repeat visits need not mean repeating the same category choice.
Matching recorded a 13% higher nightly value
The Match flow recorded a 13% higher accommodation value per night than the Lowest Price flow, comparing the same reporting months. The combined Most Popular and Recommended flows recorded an 11% higher nightly value on that basis.
These are observed differences between online booking flows, separate from the feature and service premiums above. They give the hotel a second view of performance: what guests book when the journey starts with a suitable product instead of the lowest price.
87 products, the same 150 physical units
Dynamic Inventory separates the physical room from the product sold. A room or apartment can be presented through its sleeping arrangement, quiet location, kitchenette or suitability for a particular stay. Products share the availability of the physical units behind them; smart room assignment fulfils the booked features.
The hotel sets the balance between premium revenue and guest experience. It can price selected features, include others or reward greater assignment flexibility with a lower price. GauVendi makes those choices bookable and records the response.
What could your chain sell beyond its categories?
Ask your IBE or CRS provider for the additional premium per 100 online bookings from room features and increased service sales. Then ask which products different guest segments buy. The combination reveals both the revenue and the reasons behind the booking.
Source: GauVendi Business Intelligence. Revenue metrics use 774 direct online bookings at this anonymised property. Room-feature figures sum positive premiums against recorded category prices where available and average category rates otherwise; service figures measure the premium over comparable category-booking upselling. Per-booking metrics use the full online sample. Guest insights come from a separate 769-booking analysis; feature and sales-flow analyses use their own comparison bases. Figures are rounded.
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