by Rom Hendler
The recently published phocuswright analysis provides InnoVel’s up-to-date look into the state-of-affairs in revenue management. The new technologies are outsmarting existing RM algorithms and hotels, call for a new era in rate transparency and cooperation between developers and the industry.
The industry is at a very unique crossroad. Just when hoteliers thought they’ve mastered the art of working with online travel agents, there seems to be a sense of déjà-vu.
Much like in the 1990s, we’re now seeing third-party sites using innovative tactics to bypass hotel revenue management strategies, such as access to rates designed for wholesale segments.
In fact, not only are we recognizing these familiar scenarios, but the current changes may even be more drastic than what it seems on the surface.
Their creative products can easily be incorporated into hotel’s current platforms, as quick technological fixes and updates, allowing hotels to adjust their systems to the new competitive reality.
By creating strategic alliances with these startups, hotels may not only save millions of dollars, but also move to the forefront of cutting-edge technologies.
Services such as RoomNinja, Pruvo, Betterhotel, Hotelmize and Arbitrip look into the details of existing confirmed reservations in order to rebook them in the event of rate drops in the same hotel, or at a better hotel that is cheaper or has a similar (or higher) price.
Thereby, the effect of rate drops proliferates to the existing reservations, which are either replaced with lower-rated ones or lost to a competitor.
In such cases, the displacement can be huge. The negative impact can be devastating, as the displacement can easily be greater than the incremental revenue generated by the new reservations.
Re-booking sites have several variations to their business model, most started as B2C products but many have started to pivot towards B2B solutions.
Nevertheless they all follow the same practice described above.
This practice fosters two new customer behaviors, first is re-booking for a lower rate, and second is booking rooms in many hotels for the same date range, waiting to see which one will eventually lower their rates, when the latter occurs they rebook to get the best offer and cancel all the others.
This obviously causes a much higher cancellation rate for each hotel.
Split-reservation booking sites such as Splittytravel shops different combinations of the total length of stay.
These solutions can split the duration of stay to two or more reservations at a lower total price and book them as a back to back reservations.
This happens due to the use of different rates by length of stay that the algorithms of the current revenue management systems provides in order to maximise revenue.
Thereby, third party sites are able to find availability at rates lower than those offered by the property, even when there is an active effort in establishing rate parity across channels.
In addition to displacing revenues, these sites generate multiple back-to-back reservations for the same guest stay, which may complicate operation for the front desk and possibly housekeeping.
IP-based rate serving
OTAs seem to serve different rates to customers based on their IP address. The supplier (the hotel) does not have visibility to these sites and is not able to verify rate parity.
Technology today enables both the suppliers and the guest to shop different sites with different IPs and book the cheapest rate possible.
Why does this matter? With such practices OTAs are bypassing the hotels’ rate strategies and creating opportunities to undercut rates.
The examples above present specific situations where RM systems must respond quickly to new pricing models in order to retain control over the rates and avoid customers rebooking their reservation at a lower rates.
Steps to take
More generally speaking, besides needing more sophisticated and smarter shopping tools, hotels will need to re-examine and improve particular revenue management practices as follows:
Though the industry is doing better on rate parity, it seems that much more effort has to be put in place in order to cover all potential channels and use better fencing mechanisms.
Constant changing of prices up and down:
Revenue Management Solution algorithms should strive to make less rate adjustments, have a more accurate forecast and change rates mostly upwards rather than fluctuate the price up and down to match demand.
In practice, we will likely see slower and more conservative price increases, and perhaps a little more instances with unsold inventory.
In the cases where hotels do in fact have to lower rates, the calculation must compare the total displacement with the incoming incremental revenue for the new reservations, and include the share caused by the re-booked reservations.
Serving rates by length of stay:
Hotels will need to move back to the old pricing model of having actual daily rates blended into a specific length of stay rate, that is equal to the total of theone night stay rates divide by the length of the stay, to prevent displacement to split reservation booking sites.
More aggressive overbooking levels:
Overbooking levels will need to be adjusted and shopping tools will have to be much smarter in order to make better rate decision, understand the OTA impact (Fornova is a tool that provide this type of insights) and control the distribution channels.
The advent of another wave of technology-based changes in the hotel distribution scenario is already a reality, and it is here to stay.
The importance of the upcoming wave of technologies is so pronounced that one may say we have now entered a second stage in the post-Internet hotel distribution landscape.
Hotel companies must be more cutting edge than its online competitors, rather than the other way around.
Therefore, hotels must have effective revenue management, with constant update of technologies and business intelligence to address new and upcoming disruptions.
It’s high time for a new generation of RM systems, in which transparency strategies are at new levels, and hotel proactively improve RM algorithms, possibly through alliances with innovative technology companies.
We call the mindset underlying this new generation of systems “Revenue Management 3.0”.