Let us further our comp set analysis by examining the distribution of the two key metrics, base price and occupancy, for the identified comparable units. As we can see on the first chart, our Base Price graph shows where, amongst a comp set, this unit’s Base Price falls. In the second chart, we can see that the distribution around occupancy is actually considerably broader, though still similar, to our sample unit.
And, while some units show a larger deviation in one of these metrics (e.g. base price), these units, in turn, are more similar in the other metric (e.g. occupancy). The third chart below offers one more vantage point to see how our Comp Set model works.
In short, when we examine the distance metric, you can see that while our comparable set model clearly favors units that are close by, it also considers some units farther away, if they show very similar performance metrics.
In total, Wheelhouse’s Comp Set model analyzes and identifies both a broad and narrow set of comparable units. Over the years, our data has illustrated that it is best to price against a larger set of ‘potential comparable units’, as opposed to a smaller set of ‘certain comparable units’.
Additionally, due to this approach, we can show customers a broader set of ‘potential comparable units’, which can be useful in providing a broader range of insights when either (a) comparing performance metrics or (b) deciding on a pricing strategy.