So that’s one thing that we’ve been working on an update in the backend. Another one is our compacting algorithm. So this is something that our technology team has delivered in the past quarter that’s quite exciting, which allows us, actually, it’s part of the answer I should have mentioned on occupancy rate is this sort of Tetris game with the calendar to ensure that we can maximize the quantity of bookings that can happen in a given property, especially given that we tend to have a pretty broad distribution of length of stay. So to take a simple example, if a guest wants to stay with us for four weeks, of course the average length of stay is four nights. But suppose that someone wants to stay for four weeks and they need a place starting on Friday a couple days from now, well, if we’re not careful about how we allocate the significant number of bookings that we already have on the books, we might have nothing available.
But by properly putting the right reservations in the right units, we can actually open up more availability. So there’s a pretty complex math problem here that’s applied where our team has been able to update the algorithms and generate incremental compacting, incremental occupancy, which is particularly valuable for the high season, and demand constraint, supply constrained markets and properties. So those are just a couple of examples. Maybe the last one I should mention is an update to our fixed pattern length of stay formula. So I alluded to this in a prior earnings call, but for those that weren’t on the fixed pattern length of stay implies basically making the price per night a function of the length of stay and doing though in a continuous fashion.
So a three night or a four night stay will actually have a different price per night that depends on the cost to serve that specific guest. So this is something that’s quite innovative in the hospitality industry to kind of have our cost to serve by length of stay feed into our pricing model. And so our teams have updated and improved those formalized in a way that’s allowed us, we believe to increase the contribution profit at the asset level by just optimizing this kind of discount curve.
Unidentified Analyst: Great. Thanks for all the color. Then just like a quick follow up, 3Q guidance looks like it implies revenue acceleration that being driven more by the unit count or RevPAR?
Francis Davidson: Yes, sorry, I think we lost the last part of that question. So you mentioned Q3 guidance, revenue acceleration, and then we lost the rest of that question.
Unidentified Analyst: 3Q guidance implies to revenue acceleration, is that being driven more by unit count or RevPAR?
Francis Davidson: Okay, so the question as we understand it, is it – was it more unit counts or RevPAR that is driving the revenue increase in the guide for Q3? So Dom, I’ll let you answer that.
Dom Bourgault: Thanks, Francis. It is basically all RevPAR, we – from a volume standpoint, our forecast has been very stable. So yes, most of it is from a slight reduction in RevPAR for the same drivers we mentioned earlier.
