Radix Weekly Data Report – June 24th
Both Traffic and Leases Are Showing Signs of Improvement

With the Fourth of July on the horizon, we continue to see positive developments when it comes to leading indicators in the apartment industry, according to new data from Radix.

On a national basis, both traffic and leases were slightly down on a week-over-week basis during the seven days ending on June 24. However, traffic is now only 15.6% behind when compared to the same time last year, and leases are up 3.9% from one year ago.

Also encouraging: both occupancy and leased percentage have increased for three weeks in a row. YoY, both metrics were still down 1.59% and 1.10%, respectively. But if the leading indicators such as traffic and leases continue to move in a generally positive direction, the YoY gaps in occupancy and leased percentage should close.

As for the national net effective rent (NER), that metric declined again WoW, and in fact the decline accelerated when compared to the preceding week (-0.4% for the seven days ending on June 24 vs. -0.2% for the seven days ending on June 17). However, YoY, the gap has shrunk slightly. The strongest headwinds to NER growth remain a resurgence of coronavirus cases (which are increasing in most MSAs) and continued economic fallout and uncertainty due to an increase in new cases.

With that background, here are more notable takeaways from the week ending on June 24:

  • As mentioned above, nationally both traffic and leases were slightly down WoW (0.7% and 1.1%, respectively). However, as also noted, the YoY trends are strong. Operators have clearly figured out ways to drive traffic and lease to make up for the ground they lost during the peak of the pandemic.
  • The national occupancy rate was 92.94%, and the leased percentage rate was 94.94%. That’s a WoW increase of 10 basis points and 19 basis points, respectively.
  • Fourteen of the 21 MSAs tracked by Radix saw their occupancy rates increased from the preceding week. The largest WoW increases were found in San Antonio (0.63%), Orlando (0.62%) and Denver (0.42%). The largest WoW decreases recorded in Miami (-0.84%), San Jose, Calif., (-0.45%) and Portland, Ore. (-0.31%).
  • At $1,727, the national NER stood 0.4% lower than the week before and 4.3% lower than the same time last year. On a WoW basis, NER declined in 13 of the MSAs tracked by Radix. Metros with the largest WoW decline were San Francisco (-1.4%), Riverside, Calif., (-1.1%) and Houston (-0.9%).

National Apartment Association
How to Get the Right Data

In today’s apartment landscape, let it never be said that apartment operators lack access to data.

Whether it’s a community’s own data, revenue management data, marketing data or market surveys of competing communities, or metro area/submarket reports produced by third parties, there has been a serious uptick in the availability of metrics and business intelligence during the past few years. And apartment managers are finding themselves awash in an overwhelming amount of statistics and numbers.

Read the full article on NAA.

Don’t Worry Too Much about Average Metro Rents – It’s the Rents of Your Comps that You Really Want

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.

Digging Deep

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.

Rental Data Delays Are Not OK

Life moves pretty fast.” So said the wise philosopher Ferris Bueller in the 1986 classic movie.

I can’t help but think of that line sometimes when thinking about apartment rental rates. They move pretty fast, too. In fact, they’re changing on an almost daily basis.

To make the most effective decisions regarding pricing and concessions, apartment communities need access to real-time rental rate data, or something extremely close to it.

The problem is, though, many operators are relying on data that – especially in the lightning-fast world we live in now – seems downright out of date.

Delayed Data

Operators rely on a number of data points when trying to determine how rates for their communities compare to the competition. These data points include everything from market rent, concessions (upfront and/or amortized) for each unit type, occupancy and leased percentage, traffic and leases, amenities, etc.

Similarly, and to help ease the process of gathering all these data points, operators sometimes turn to market surveys compiled by third-party research organizations. These surveys are usually conducted at the market level and then a regression analysis is performed to determine submarket data. While this methodology seems to offer the most robust and logical look at how an entire market or metro is performing there are two key areas of concern: 1) the survey data is, in the best-case scenario, 30 days old and 2) the surveys don’t provide true insight into the surrounding submarket, let alone at the property/comp level.

It is also a common practice for research firms to collect market data through a variety of tactics including ILS scraping and cold calling properties within a market. These practices can result in erroneous data sets due to inaccurate ILS listings and timing needed to conduct property calls.

Onsite Team Efforts

In an effort to combat the potential pitfalls of third-party market surveys, communities also leverage onsite associates to research rental rates and vacancy data for competing properties. This manual process is also problematic. First, it can take awhile for associates to actually get in contact with someone who will give them the information. Furthermore, there is an assumption that the person on the phone is providing the most accurate information – which unfortunately is not always the case.

Also, overextended associates are understandably prone to human error when gathering this data and inputting it manually into market survey spreadsheets. Finally, by the time rental rate information has been gathered and the resulting spreadsheets have been compiled and passed, the data within the spreadsheets is often out of date.

Put simply, the methodologies used to collect and manage comp data in the multifamily industry today are seriously flawed. So the result is poor pricing and management decisions that cost millions if not billions of dollars in revenue.

The Benefits of Real Time

Furthermore, it’s time for operators to commit themselves to put automated processes in place that allow them to gather and analyze real-time rental data about the submarkets in which their communities are located.  

When they have access to this type of data, they develop a true understanding of how their properties are actually competing within their submarkets. As a result, they can make effective, relevant decisions about pricing that reflect where their competitive set truly is at that point in time. In short, they can be sure that their pricing is never too high – or too low.