Rent Comp Survey Strategy for Multifamily Development
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Picking the correct comp sets is one of the most crucial due diligence items a developer must take when determining if new multifamily construction is feasible. I will show you how to tackle a few critical questions by leveraging HelloData to produce and refine the rent survey. This real-time data should inspire confidence and give you a leg up on your competition.
Contents
We are exploring the feasibility of developing a 275-unit "Class A" apartment building. We've analyzed the "back of the napkin" with "rough numbers." There may be potential to build a profitable project.
The intention is to assess the comp set and determine reasonable rents and charges for parking, storage, pets, etc. This tutorial will highlight Tactica's Development Model for the proforma assumptions.
This analysis takes place in a submarket that has seen a lot of new apartment units come online as of late, so we must be mindful of the impact of this excess supply on our revenue potential.
I will use HelloData's real-time property information to assist with the analysis but keep the apartment complex names confidential.
While technically, all this data is public information, the focus of this article is to show you how to maximize HelloData's features, which is possible to demonstrate without calling out actual properties.
We put the estimated unit count and square footage into the "Unit Mix" tab of Tactica's Development Model. We need to come up with baseline rent projections.
Let's dive into the rent comps. Tactica is partnered with HelloData.ai, pioneers in using artificial intelligence to gather rent-comp data and insights. If you want to try out their platform, they offer a 7-day free trial.
Related: Check out HelloData.ai full review
Technically, there's no subject property. The subject property is our development that is yet to be built. Instead, I will choose a project that most closely resembles our future building and designate that building as the subject property below.
The first thing I want to do is ensure the comps are:
In the same neighborhood
Same construction style (I don't want to see high-rise apartments if we are building podium construction)
Comps are all built within the last five years
The comps HelloData suggests are solid. All comps are in the same neighborhood and have the same construction method. However, two comps were built in 2017 and 2012. I will cut those loose before creating the rent comp report.
You can "edit" your comp set and then "delete" any comps by clicking the red garbage can.
I'd also check if any remaining comps have vastly different unit or community amenities than our planned project.
I suggest cutting out a comp with too many features we aren't planning to include. I’d do the same with a property with fewer amenities than we plan to build.
All of these comps look relatively similar. The pool could be a nice differentiator!
You can custom-choose the most essential amenities by clicking the "+" sign and selecting dozens of options.
The next thing I want to understand is property performance. Every comp has a "$" in the “Specials” column, signifying that management offers prospective residents concessions. You can click on the “$” sign to see the specific discount provided to future residents and how the discount has changed historically.
This knowledge is essential when we enter the lease-up assumptions into the development proforma. There's quite a lot of softness in this submarket.
Next, I want to look at the average rents of closed listings over the last few months for the prevalent unit types in the development. Let's say we want to look at:
Studio/One BA
One BR/One BA
Two BR/Two BA
As an example, the studio rents in the comp set are the following:
I'll plug that data into the underwriting model, as our studio rent is a placeholder for the proforma rent.
I'm backing into the PSF rent by typing in a chunk rent amount that will add out to $2.06.
I'd input the same effective rent data for the one and two-bedroom units.
I'd also be looking at the comp bar charts and comparing the effective rents of each unit type.
I’d be asking questions like:
What differentiates the highest-priced One BR vs. the lowest-priced One BR?
Do any properties have unique amenities that give their units a rent boost?
What building does my project relate to the most in terms of quality and renter experience?
What building does my project relate to the most in terms of location?
I'd adjust the rents in the proforma as I make these determinations.
I'd then analyze the rent trend of the various unit types. Below, you can see the effective rent trends of One BR/One BA over the past six months. Each color is a different property.
There's a downward trend. And quite frankly, all unit types have a similar pattern.
Some questions I'd ponder are:
Is this typical seasonality?
What does the current supply pipeline look like (this is outside of the scope of HelloData software)?
Does the subject property have attributes in common with comps with strong trendlines?
Does the subject property have characteristics in common with comps with weak trendlines?
The market is clearly in decline. While the property we build will be slightly higher quality than some of the comps and in a better location, I'm uncomfortable forecasting rents near the top of the comp set.
I'm currently taking the average comp set rent as the proforma projection. I want to decrease the proforma's rent by 10% for conservative underwriting. I know more supply is coming online in the upcoming year and will be delivered around the same time our project receives its certificate of occupancy.
In summary, I am taking the effective rents of the comp set and solving for 10% less.
Studio: $2.06 x (1 - 10%) = $1.85
One BR: $1.93 x (1 - 10%) = $1.74
Two BR: $1.60 x (1 - 10%) = $1.44
Blended Property Rent = $1.69 PSF
Note: We can sharpen the pencil later, but want to see if the deal works with conservative numbers.
Because I am conservative with the proforma rents, I expect the property to stabilize relatively quickly (in about nine months). This assumption assumes we’d be able to pre-lease 30% of the units and lease 16 units/month until achieving 95% occupancy.
We'll be leasing the newest units on the market significantly below the average comp’s rent. I will also estimate one month of concessions during the lease-up as an additional layer of security.
However, I wouldn't expect any concessions on renewals, and the average effective rent will stabilize near $1.69 PSF for second-generation leases.
When the construction period is wrapping up, and you are close to leasing units, you can look at the actual listing unit details of the comps set to see how units are leasing in the submarket in real time.
You can click on each listing to see how the rent has changed during marketing.
You could also look at HelloData's "Recommended Rent" to determine rent potential.
Every unit has a recommended rent that is less than "Last Eff Rent." This discrepancy was a big reason I backed off the proforma rent assumption and added a one-month lease-up concession as an extra safety buffer.
HelloData can also help us with "other income" and "expense" projections.
I can see immediately what the competition charges for items like:
Misc Fees
Storage
Pets
Parking/Garage
I'd solve for a similar amount in the proforma underwriting.
I'd also use HelloData's financial analysis to verify that our operating expense projections are reasonable.
I'd compare the "per unit" column to the projections in Tactica's proforma.
If there were a significant discrepancy, I would verify that with the property manager to ensure we estimated accurately. Property taxes are quite different, but they can be vetted with public county data.
As I worked through this project, it became apparent that this submarket's rent is far too low to justify a new development. This could change with time, but I purposely cherry-picked a market experiencing rent decline, has seen excessive supply over the past decade (especially lately), and has fallen out of favor with residents.
While I was aware of this anecdotally, HelloData helped me quantify it by showing me the following:
Every comp was offering two months of free rent
Effective rent trends are down over the past six months
Most listings (especially larger units) have been sitting online for months, some even 100+ days
“Recommended Rents” are 10% - 20% less than listing rent levels for the building most similar to our project
Development is challenging now, with higher interest rates and ballooning construction costs. Further factoring in rental decline makes construction nearly impossible in certain markets around the US and Canada.
Summarizing Development Rent Survey
Using HelloData’s software, we can get real-time effective rent information in the submarket, assess the most appropriate rental comps, and determine reasonable rents for a planned development. We had the most accurate data in seconds, and we can follow these comps daily to see how the market changes over time.
HelloData takes care of all the time-consuming tasks and gives you the comp data in one central location, making it seamless to transition to your proforma underwriting.