It is no news that the vacation rental business has exploded worldwide thanks to the sharing economy. With the industry generating billions and billions of revenue per year, providers for related services have popped up like mushrooms. To be able to separate the wheat from the chaff we have composed a number of basic principles that apply to revenue management for vacation rental business or apartments.
With sites like Airbnb, Homeaway, Onefinestay, Tripping, Wimdu, 9flats, Vacationrentals, Flipkey and Booking.com making a swift move into the apartment rental business, the apartment rental business has become a mainstream lodging provider.
Given the explosive growth of the apartment rental industry, equally have the numbers skyrocketed of aggregators for management services and technologies. Many of these businesses aim to take away your trouble to rent your apartment, some more successful than others.
Channel management technologies, Property Management Systems and revenue management systems have emerged left and right. Not surprisingly, these technologies often resemble their respective counterparts in hotel industry.
Since Xotels got actively involved in managing close to 1000 individual apartments and vacation rentals in different destinations about 3 years ago, we have been able to work with and test numerous technologies and service providers.
Hence here are a couple of thoughts putting service providers and technologies against the light of revenue management practices and technologies in other lodging establishments such as hotels, hostels, resorts and holiday parks.
The biggest challenge for vacation rental revenue management compared to revenue management for traditional lodging establishments is the lack of capacity.
The core ingredient for almost any revenue manager simply does not have its equal in the vacation rental industry. No capacity means no capability to measure pick up, pace or occupancy percentages. You have an empty or fully booked scenario for each day of the year, and there’s no way around it.
Given that each unit is sold separately based on a unique location with a unique price and its own value proposition, there is no real difference for owners or service providers that manage (much) larger quantities of apartments.
Having access to multiple units on different locations simply does not change the principle of the uniqueness of information gained when selling one unit. It gives you more data, but that does not provide you with much valuable for managing 1 individual unit.
Benchmark and rate shopping tools
A benchmark of a direct competitive set does not provide much useful information. The individual character of unit sales and unit pricing plays a role once again.
In addition, revenue management in the apartment rental industry seems to still be in its child’s shoes and there are more pricing operational decisions made for and by individual properties, than can be analysed sensibly.
Making a quick jump to hotel industry; when talking to individual hotel owners, I would like to share the thought that I am convinced that their individual pricing strategy is smart, and their competitors are all silly and far less intelligent than they are.
However, I always add that, when combining all direct competitors, and taking all of their prices and pricing decisions, their behaviour is probably reasonably smart on average, and a decent indicator of demand for the individual owner.
This principle however, I have not been able to apply in the apartment rental industry. The variety of competitors is too large, pricing strategies are too wide-spread and the industry is too fragmented to allow for meaningful logical conclusions.
Channel Managers
Channel managers as standalone tools, that provide rates and inventory to sales channels, and sometimes are capable of sending reservations back, will largely suffer the same fate as their counterparts in hotel industry.
Most of them will disappear rapidly, even faster than channel managers disappeared from the hotel industry. Channel management technology in the end represents the ‘man in between’. They have a function of existence between PMS’s and distribution channels. The man in between, in the end will always be cut out if the 2 providers that it serves, can provide a better, more efficient and/ or cheaper solution.
The reason that they’ll disappear faster, is that there are no legacy systems in the apartment rental industry. All technology that I have seen is cloud based, completely open to interfaces, and thus rapidly involving, building direct interfaces between PMS’s and OTA’s.
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Property Management Systems (PMS)
PMS’s in this field have stood up incredibly fast, and are growing up quickly and mostly have to deal with an inexperienced and uneducated end user, and potentially with the savvy service aggregator of multitudes of apartments in between.
Whilst most of the PMS’s I have seen still struggle with direct user interfaces and user experience, they are much more open to build interfaces to any other technology provider (pricing systems, OTA’s, payment systems, concierge and security systems).
Near future changes will lead to PMS’s no longer needing channel managers to supply distributors with rates and inventory. PMS’s will simply work to be more efficient.
Given that the number of sales channels is far more limited than in i.e. hotel industry, this will come full circle rather sooner than later.
Automated pricing tools
This is an area where we really dug in. Being a revenue management company, this got really interesting to us.
We looked at and worked with several pricing tools for the vacation rental industry.
These were our most interesting conclusions:
Multiple tools we looked at claimed to have complex algorithms, or to have machine learning tools. When asking for more details, no one provided insight in how algorithms were working, what weight certain elements had in pricing decisions.
I can imagine that systems do not want to give away the in-depth details of algorithms, but no one was able to specify any high level information about what weight certain pieces of information played in the outcome of their pricing. Yet we did see tremendous fluctuations in pricing:
- Events
- Competitors
- Incoming flight passenger volumes
- City wide demand
- Historical patterns
But again. No one was able to show what weight each element had to come to a price recommendation, and no one was able (or possibly, willing) to explain how each element worked and impacted pricing.
We tested actively with live data though, and looked at recommended prices by tools. Hence we did get solid impressions. For example, in multiple tools;
- All events were imported automatically and carried a similar weight. Therefore, events were not representative of existing demand.
- That historical data was often matched incorrectly.
- Elements like weather or incoming passenger volume that have little to no influence on demand for apartments were often incorporated to decide on a price.
- Offered seemingly complex algorithms, but major calculation errors are rapidly discovered.
Not surprisingly, we saw a lot of errors in pricing, that either prevented apartments from selling or sold them too low. On top did we notice that several tools had a high price recommendation for dates far out, and closer to the arrival date prices came down fast. In addition, we saw that what seemed to be simple daily pricing errors had far more significant revenue impact due to length of stay restrictions.
Certain tools do allow to overrule pricing, however when managing large quantities of apartments, this can be a rather overwhelming task, given that the errors are not easily found. The tools we looked at simply had a focus on detailed decisions, but not on managing larger groups of apartments.
Managing apartments of different owners
This easily the second biggest challenge I have come across when doing the revenue management for different individual apartment owners through one central provider or aggregator.
Revenue management is a field where communication is crucial. So is testing of strategies in order to achieve the highest level of success. If one aggregator manages 100 apartments from 100 different owners, there will always be apartments that perform worse than others.
And logically, there will always be owners with sub expectations about performance and reporting.
You can’t possibly think you can comfortably manage expectations with hundreds of owners. Due to the complexity of revenue management and the fact that any price and transaction is always open to interpretation, the decision must be centrally made.
I have seen multiple apartment management companies drown in a steady flow of questions, comments, frustrations and co-management efforts from owners. I personally manage that exact same stream of questions for hotel managers and owners. The only reason I am able to handle it is that I can have 1 account manager handle this for 1, 2 or 3 hotels maximum. Not a single account manager would survive doing this for 100 properties, whether larger hotels or small apartments.
Hence a very strict working relationship must be established with the owner. The moment owner interference is an option, this creates an unmanageable stream of information. No matter how good the apartment results will be, owners will always have thoughts and questions.
This requires formal and upfront agreements that specify this part of the working relationship with owners, and follow through via standard reporting via extranets. I have even concluded that reports to individual owners about apartment performance should not even contain information about average room rates and occupancy percentages to avoid questions. The only thing they get to see is the revenue generated during a month. This may avoid questions about the complex world of yield management, and that’s the only purpose.
In my next article, there’s much more about how I believe revenue management can be applied in the apartment rental industry.
