When it comes to apartment market data, it’s important to make a distinction between “macro” and “micro.”
Macro data refers to statistics like a metro area’s average rent or its occupancy rate. Micro data refers to the average rent or vacancy rate of a competitive set of communities. Think of it in terms of a photo – macro is the whole photo. You can see the entire picture but not the details. Micro data is like zooming in on that photo. You can now see things like a ribbon in someone’s hair or a flower just starting to bloom.
When evaluating the performance of your apartment properties, it’s helpful to consider both macro and micro statistics. In other words, micro data – the more detailed, closer view data – will provide by far the most valuable, relevant insight.
The Fallacy of Averages
To be sure, reading third-party monthly or quarterly reports detailing a metro area’s apartment macro data can give operators important context for their communities’ performance. It’s always good to understand the broader market in which your properties operate and to take in the numbers, insight and analysis regarding trends in your metro area.
But here’s the thing: when it’s time to truly put the performance of your community into perspective, micro data eats macro data for breakfast. Put simply, if your property is located in say the booming Midtown area of Atlanta, you can’t really evaluate your property’s pricing based on the average rent in metro Atlanta. Even the average rent for the individual submarket in which your community is located may not be entirely relevant. To be truly in the know about how your community is performing, you need to know the rent dynamics in your comp set.
Clearly, the average rent for a metro area is calculated using information from communities that are not competitors for your prospects. Therefore, the same can hold true for submarket averages.
For instance, say a particular average submarket rent is calculated by gathering information from communities within a certain three-mile radius. In urban areas, a three-mile radius may contain between 200 and 300 communities. If you’re in that submarket, your prospects aren’t considering those 200 to 300 communities before making a decision. So does it really help you to know what’s happening at them in terms of rent and occupancy?
The only completely relevant comparative information comes from the other communities your prospects typically consider, i.e., your comp set.
It starts with selecting the right comp properties that are most likely comparative in product to your property and offer similar advantages in location. The reason why this is so important is that any prospect who is considering making your property their home is, most likely, also considering these 5-8 properties.
So, having visibility in terms of rents, occupancy, traffic and leases to these comp properties allows you to adjust your strategy and ensure your property stays competitive. Being able to see and select specific comps is especially very important as you dig in deeper into the competitive landscape and compare renovated unit types to specific comps, excluding unit types that are not comparable to your property, and the like.
The ideal way to get data about your comp set is through market surveys. So, as I’ve detailed before, the traditional manual approach to market surveys has its own set of issues.
Automating the collection of asking rents and other performance data from comps can streamline the process significantly while also improving the accuracy of the information gathered. As such, associates can now concentrate on the many other tasks they have to tend to that are critical to signing new residents and keeping current ones happy. In the end, it’s how your community compares to its comp set that’s the most important indicator of performance. Having a firm grasp of the rents and occupancy rates of the competitors is what allows an operator to know when it should push or scale back rents at its own communities.