RS Metrics Identifies Class B-Mall Performances

Posted on April 9, 2018
Michael Gantcher from RS Metrics contributes to Trepp site on:
Identifying Class-B Mall Performance From a Bird’s-Eye View

Michael Gantcher from RS Metrics

Parking lots aren’t simply a place to leave your vehicle while you pop in to the store; they can be the site of concerts, festivals, even championship parades (ask a New Jersey Devils fan about that if you have the chance). Parking lots can also serve a greater purpose in measuring CRE performance, especially in regards to retail. A mall’s parking lot can serve as an indicator for the building’s foot traffic, especially if the lot is less than full. With the retail sector under the microscope, we use this blog to examine data on customer traffic for a few US malls.

Sometimes, it’s helpful to view something from a different perspective to analyze it. When measuring customer traffic as a performance indicator, a bird’s-eye view might be best. RS Metrics partners with high-resolution satellite imagery firms, such as DigitalGlobe and Airbus, to derive data and trends on customer traffic at CMBS properties. This data can be used to highlight early indicators of slipping property performance.

The ABCs of Mall Class-ifications

For the purpose of this blog, we examined parking lot trends at malls by Class-ifications. The mall Class-ifications for this analysis takes several factors into account, both qualitative (tenant mix, geography, demographics, etc.) and quantitative (Sales per Square Foot, or SPSF). The SPSF for class-A malls are $500 or more, while class-B SPSF figures are in the range of $350 to $500. Class-C malls usually feature SPSF below $350. CMBS investors are comfortable owning debt on class-A malls and have shied away from debt exposure to class-C malls, leaving the fate of class-B malls as an open-ended question.

RS Metrics surveyed over 90 class-B malls across the country and indexed the monthly traffic figures from January 2016 to October 2017. We then compiled a large nationwide sample of both class-A and class-C malls and compared those average traffic figures to that of the class-B index.

The Monthly Average Fill Rate Index compares the average fill rate (cars/spaces) each month for a property or a set of properties. The starting point of the index sets the average monthly fill rate for each data series to 100 and shows the change of relative performance of each over time. For example, if the average fill rate for class-A malls is 50% and the average fill rate for class-B malls is 25%, then they would both be reflected as 100. If both class-A and class-B mall average fill rates are 50% in the following month, then the index would move class-B malls to 200 and would keep class-A malls at 100.

The chart below indicates that customer traffic trends at class-B malls (green line) performed closer to class-A malls in 2016 but closer to class-C malls in 2017.

Source: RS Metrics

RS Metrics cross-referenced properties within the Class-B Mall Index with Trepp’s CMBS data to highlight a few large CMBS loans which are backed by properties with average fill rates that are underperforming the broader index. The monthly average fill rate for both the broader Class-B Mall Index and the five loans we highlighted peaked in December 2016, which coincides with the holiday shopping season. Throughout 2017, the monthly average fill rate for the broader index and the highlighted loans fluctuated with gap between the two widening until October.

RS Metrics calculates the trendline slope of each property’s traffic trend in the Class-B Mall Index over the period of analysis. By ranking the properties by the magnitude of their trendline slopes, we can identify the outperforming properties (those with the steepest positive trendline) and the underperforming properties (those with the steepest negative trendline slope). The five properties included in the index above are those for which we see the steepest negative trendline slope.

Source: RS Metrics

Of course, there is more to the fundamentals of a property and their ability to cover their debt service than parking lot traffic. As a data firm, RS Metrics does not know the economics of or activities occurring on or around any given property, such as renovations, transportation improvements or hindrances, new competition entering the market, etc. This satellite property traffic analysis should be incorporated as part of a mosaic of data used to assess a property’s health.

Contact RS Metrics to get more information about the data in this blog, including the five largest underperforming class-B properties. You can reach us directly at 212–671–1056 or Please also visit our website at and follow us on Twitter @RS Metrics.

Disclaimer: The information provided by Trepp is based on information generally available to the public from sources believed to be reliable.

Read the full article on Trepp here.

Originally published at on April 9, 2018.