Best Revenue Management Software

RoomPriceGenie provides automated pricing for hotels, aimed squarely at small and independent properties rather than the chains and groups the established revenue management vendors serve. That audience choice determines everything about how the product is built and sold.

The gap it addresses is real and large. Revenue management systems were designed for hotels employing a revenue manager, and a thirty room independent property has no such person, so it prices by copying last year's rates and adjusting when the owner notices the town is busy. The result is systematic underpricing on high demand nights and empty rooms on quiet ones.

Automation rather than recommendation is therefore the correct design for this buyer. A large hotel wants suggestions a professional evaluates and sometimes overrides, while an independent owner wants the rate set correctly without having to think about it, because the alternative is not careful manual pricing but no pricing decision at all.

The constraints discussion on the vendor's own site is refreshingly honest about the limits. Charging what pure optimisation suggests is not always sensible when a property has regulars, a local reputation and guests who will notice a rate that tripled for a festival weekend, and building those constraints into the system is more useful than pretending they do not exist.

IDeaS supplies revenue management to hospitality, publishing customer results alongside its product material and drawing on a long analytics heritage. It is among the most established names in hotel revenue management and competes largely on the quality of its forecasting.

Forecasting is genuinely the whole product in this category, whatever the interface looks like. A revenue system recommends a rate for a future date, that recommendation depends entirely on predicted demand, and everything else is presentation of a forecast that is either good or is not.

What makes hotel forecasting difficult is the number of things moving at once. Demand varies with the day of week, the season, local events, competitor rates, the booking window and how much has already been sold, and the interactions between those matter as much as the factors themselves, which is why this resisted spreadsheet modelling for so long.

The behavioural obstacle is at least as large as the technical one and is discussed less. A revenue manager who overrides the system whenever it suggests something surprising will get results no better than their own judgement, and the recommendations most worth following are precisely the counterintuitive ones. Adoption in this category is a management question rather than a software one. Published figures on the site were customer results rather than prices.

Duetto provides revenue management for hotels and casinos, built around open pricing: setting rates independently for each segment, channel and date rather than deriving everything from a single base rate with fixed differentials.

The traditional approach constrains a hotel in a way that costs money. If corporate rates are always a fixed percentage below rack rate, then raising one raises the other, and the hotel cannot respond to a corporate demand surge without also pricing out the leisure guests who would have filled the remaining rooms.

Pricing each segment independently removes that coupling. A hotel can raise its corporate rate while holding leisure steady, or discount a channel where it has unsold inventory without touching the rest, which is what makes the yield gain material rather than a rounding difference on the annual figures.

Casinos are called out separately because their economics invert the usual logic. A guest's value is what they spend on the floor rather than what they pay for the room, so the right room rate may be zero for the right guest, and that requires a model pricing against total guest value rather than accommodation revenue alone, which is a materially different calculation from standard hotel yield management. No pricing is published.

PROS builds AI-powered pricing and revenue optimisation, and its scope has narrowed in an important way: the PROS B2B business is now Conga, so what remains under the PROS name is airline retailing and offer management. Anyone shortlisting PROS for general B2B price optimisation should establish which company now holds the capability they read about, because material published before the split describes both under one name.

What PROS does today centres on turning offer management into a revenue engine for airlines. The pricing components are named individually. Real-Time Dynamic Pricing sets fares as demand conditions change rather than on scheduled updates. Dynamic Ancillary Pricing applies the same treatment to extras such as seats and bags, which is where a growing share of airline revenue sits. Revenue Management handles the underlying forecasting and inventory economics, and Continuous Pricing is offered as a distinct use case alongside offer optimisation and ancillary optimisation. Group Sales Optimizer covers group bookings, a pricing problem with different mechanics from individual fares.

Around pricing sit shopping and merchandising, product management and a product catalog, plus Stock Keeper. An offer marketing family, airTRFX, airModules, airWire and airSEM, handles the demand side, so an optimised offer is also marketed and distributed. The scale claim is specific and gives a sense of the computation involved: more than 400 million prices and 1.7 billion forecasts every day. AI Agents, integrations and a partner ecosystem extend the platform, with PROS University providing training and PROS Connect and developer resources supporting implementation. Pricing is not published.