With the arrival of high season, hoteliers and some Revenue neophytes breathe a sigh of relief: rooms – so it is thought – sell themselves, there is no need to go about formulating strange alchemy.
Instead, this reasoning is completely misguided: just beyond the high and peak season lies the pitfall.
Precisely at this stage and precisely to avoid recurring damages – sometimes caused by less-than-dynamic revenue managers – one must be very vigilant and quick to grasp any market evolution.
It is necessary to be timely and dynamic in outlining pricing movements.
And to achieve this there is only one thing one can do: study.
In the sense of sitting down to work and analyze historical and forecast data.
Of course, doing this at the very last minute doesn’t pay off.
It is necessary to start well in advance (up to a year earlier, even) gathering data that will provide any and all relevant sales information: this is the road map to avoid “gaping holes” in your turnover or, better yet, to optimize revenue.
A correct starting rate will generally yield these results in high season: it will tend to discourage well in advance bookings, on account of the high price.
Reservations will be collected here and there, without a constant flow; in peak season, bookings will be increasingly closer to stay date, when the starting rate becomes attractive.
Speaking of attractive rates, it is necessary to open a parenthesis to specify that – if applied at a certain distance from stay date – it allows for excellent commercial results: it can potentially attract many people.
However, it is equally important to remember that these rates must be applied to a few rooms only.
Back to our original topic, let’s now see what happens within two months or one month of the arrival date.
Well: this is the period where one must prick up one’s ears, as reservations become more numerous and more constant.
This is the time to keep one’s eyes wide open so as not to miss any signal coming from the market, of course, constantly referring to the historical data on last year’s pick-up by rate.
Let’s shed some light on this topic by using an example.
Let’s suppose a leisure hotel has achieved 95% room occupancy in the previous year, with an average sales price (Average Daily Rate) of 88€ per room, a total turnover of 8360€ and a Revpar of 83.60€.
Analyzing the historical data, the 95 rooms sold must be divided by type of booking – OLTA, site, telephone, walk-in (customers who arrive without a booking) – and by rate applied.
We get this table, which also includes the number of rooms sold for each individual channel:
From this table, one fact immediately catches the eye: OLTAs perform well with any rate but, their performance is stronger with the lowest rates, compared to other channels.
The site, on the other hand, tends to “vanish” in the first part of the sales plan and in the final part, when last-minute rates are applied.
Phone bookings display a fairly regular trend, while the walk-in trend is self-apparent, since it refers to the last rate, coinciding with the day of arrival.
Another aspect which should not be overlooked: the rates were raised too soon.
Faced with a risk of unsold, the revenue manager implemented a last-minute that brought the rate back to the starting level: with 15 rooms sold (13 + 2) he compensated, course-correcting at least in part.
So: how could a better outcome have been secured, that is, full occupancy achieved?
Perhaps, it would have been advisable to linger longer on the intermediate rates, particularly on the resistance rate. Which one? 99€, of course.