HelloData Rent Comp & Expense Benchmark Review
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For the past couple of weeks, I've had access to HelloData.ai. Its platform uses artificial intelligence to pull and analyze rent and expense comps of your desired submarket. Within 10 minutes of using it, I realized this tool could become the standard for rent comp analysis for all multifamily investors across the US.
I rarely see new tech in the multifamily space that will flip the game upside down. HelloData.AI has already done that with its rent comp analysis tool, and even more exciting is the upside that's yet to come.
A+ Value Proposition
HelloData costs $250 per month.
This price point is tremendous value if you use this program for any combination of the following:
Acquisitions rent comp analysis
Monitoring your competition as a property owner
Market survey tool as a property manager
You can create infinite reports all over the country if you desire. There are no geographic barriers. Any time you have a submarket or property you want to investigate, there are no limitations. You even get unlimited comps!
HelloData.ai vs. Standard Rent Comp Analysis
I used to offer a consulting service called "Property Positioning." Owners would hire Tactica to help figure out how to maximize their property. The most significant component of this exercise was figuring out how the property was positioned within the submarket comp set.
I would delicately pick and scrutinize the rent comps and determine strategies to take the subject property to the next level. I charged between $3,000 - $6,500 depending on the number of comps and if I could physically tour the properties.
I spent hours gathering data, including:
Touring
Taking pictures
Ranking pictures
Scouring listing data online
Calling leasing agents for the latest rental data (which was usually wrong)
Cleaning and organizing this data to make tangible insights.
One of these assignments would take at least a week (40 hours minimum). Most of the project scope was in the form of gathering and organizing data. It's incredibly tedious to do it well.
The fun and essential part of the assignment was developing a plan of attack for property ownership once I organized that data and could interpret it.
HelloData
All of the "gathering" and "organizing" is done with a click of the button with HelloData.
It will find comps for you based on factors like:
And then detail the subject property and comps by:
Average Rents by Unit Type
Rent Comparison
Historical Rent Trends
Unit Availability
Amenities and Finishes Ratings (on a 10-point scale assisted by AI.)
Fees/Ancillary Income Charges
Expense Comps (More on this later)
This data can be exported flawlessly into Microsoft Excel, ready for your proforma underwriting model.
You can also pick unique comps if you prefer something other than HelloData's selections.
In summary, you could pay for HelloData for two years, and it'd still be cheaper than some of the analyses I put together for owners for a couple of weeks’ worth of work.
Related: See a case study using HelloData to determine the rental premiums of a 332-unit acquisition.
It does all the heavy lifting for you, although it will still be up to you to assess the data and make your interpretations. That's the fun part!
Intuitiveness
You don't need to be a financial analyst to master this tool. It's effortless and straightforward. I didn't feel like I needed assistance with anything. I knew what I was looking at and what the data told me. If you're using any of the Tactica tools, HelloData will be a breeze!
There was maybe an hour or so of "exploring," but it was entertaining to uncover all the functionality and unlock all the analysis features. There were no roadblocks or frustrations with the user experience.
Even better, you get a free seven-day trial when you sign up, so you'll have plenty of time to get acclimated and be sure HelloData is the right tool for you!
Robust Data Levels
I'm a data guy. If you follow Tactica, you know that. One thing I loved about this tool was the varying sophistication of data. For example, you can look at the average rent by unit type.
Notice the ability to filter by “unit type,” “active/closed listing,” and “period.”
This data is what I would use to determine high-level rental premiums when doing a value-add proforma analysis.
But then you can see the history of individual units, their pricing changes throughout the listing, if concessions management is offering, etc.
These insights would impact a "best and final" when finalizing your underwriting or keeping tabs on your competition if you own properties.
This kind of data only used to be possible for the subject property if you had a rent roll and were willing to take the time to do an analysis. With HelloData, you can simultaneously get a granular view of multiple properties from publicly listed data.
Operating Advantage
So many operators out there can't justify the cost of an algorithmic-based property management system. The most sophisticated systems are reserved for private equity and institutional players with endless budgets.
Private owners and property managers can use HelloData to perfect their comp set and monitor it in real-time. You can follow how rents are moving in your submarket, the status of concessions, how long listings are outstanding, and how the pricing changes during unit listings. You can take that information and react immediately.
You can even “enable email notification” to updates about buildings and unit information.
Inclusive of Smaller Properties
Since HelloData gathers data by scraping the web with AI, properties that invest more in marketing will naturally have more data on the web. When playing with this tool, I focused more on "Class C" and smaller properties that are likely to have more "ma-and-pa" owners, invest less in marketing, and ultimately have less data about their properties on the web.
Spoiler: It was still pretty good! Was there less information than some of the larger, newer properties I investigated? There was less, but the available data was accurate and helpful.
I called an owner I know who owns a 10-unit brownstone and has never paid for marketing. I set his property as the “subject” and called on HelloData to suggest ten comps.
I asked him live if his rents were accurate as HelloData depicted them. They were. Then we talked about comps. We realized the rent he charged was higher than the likely actual market.
While a handful of comps were charging the same amount for studio apartments, the square footage of my friend's units was much smaller than the comp set by about 30-40%. That may be why there's some vacancy!
I discovered this intel in less than five minutes.
Operating Expense Benchmarks Included
The subscription also includes operating benchmarks.
This section is a cherry on top of an already fantastic program. One of the most common questions I get at Tactica is, "Do you have any good expense benchmarks."
My advice has been the following:
Start tracking revenue/expenses on deals you underwrite
Talk to local property managers
Talk to local brokers
While those bullets are still necessary and highly recommended, the "Financials Analysis" section is another invaluable resource. Did you notice the fine print in the image above?
“Computed based on year end 2022 financials from the 10 most similar multifamily properties with year built between 1906 and 1930 and number of units between 101 and 217 in the Chicago-Naperville-Elgin, IL-IN-WI MSA.”
GSE-insured loans are required to report quarterly financials. This data is publicly available, but it has to be pieced together from different places, standardized, and normalized for analysis. HelloData did this work to develop a comprehensive database with real financials from over 25,000 properties across the U.S., which then trained predictive algorithms that underwrote income and expenses in any market.
Should you take this data and plug it into your proforma model? Absolutely not!
However, you should review your vetted underwriting assumption to these averages. If there is a significant delta in any line item, try to figure out why that is.
I think of this section as additional peace of mind. It's a safety check, and you should use it responsibly. This data is updated quarterly.
Development Due Diligence
HelloData significantly decreases the due diligence burden for developers. Creating a custom rent comp survey, assessing the submarket, and determining estimates for effective rents, ancillary income charges, and operating expense projections is easy to tackle.
I wrote a separate tutorial for using HelloData for multifamily development—creating a rent comp survey and populating the development proforma.
Future of HelloData
While working through HelloData, I also saw areas of improvement and innovation.
Finding Better Comps (Updated)
The tool was exceptionally good at finding comps on par with the subject property. You might need this scope if you own a property and don't don't make any improvements. You'll have to pay attention to your direct comps.
When I looked back at past rent comp exercises I completed manually vs. what HelloData pulled, there was much overlap in comps, but it always seemed to be the "worse" or” “inferior" comps that overlapped. Candidly, these are the accurate comps; they were most "equal" to the subject property, but it's also it's to have comps a "tier above" to try t” emulate.
I brought this up with Hello Data ownership, and they told me they are already working on a solution!
Update: Within a week of writing this review, HelloData.ai created an update to find “Value-Add Comps” (in beta).
Looking back at an old property positioning assignment I did in 2019, the “value-add comps” selection suggested 75% of the comps I had manually handpicked (6/8). Even more impressive, one of the comps it excluded was a property I thought was “over-renovated” in the submarket. While the finish levels were the nicest in the comp set, the potential rent premium wouldn’t justify the cost to renovate.
Renovations vs. Original
On the same wavelength as "finding better comp," ideally, there would be more emphasis on renovations vs. original units. Again, this is already in the works, and there’s a dedicated column to each comps renovation status in the Excel export that will populate soon.
More Graphics
I think with time, it would be nice to see more charts and graphs to help better interpret the data. With rent comps, I’ve always been a huge scatterplot fan. It’s nice to see all the rents plotted based on effective rent and square footage with a trend line that helps viewers interpret the subject property’s position in the comp set on a rent PSF context. Below is an example from Tactica’s Rent Comp Model:
With how fast HelloData has been innovating its product since I began working on this review, I would expect deeper visual analysis to be on the near horizon.
AI Picture Rating System
I asked ownership how the AI rates units, common areas, and amenities on a ten-point scale.
The algorithm has examined millions of photos spanning the most luxurious penthouse high-rise in NYC to a dilapidated "Class D" property in the rural USA. Every kitchen, bathroom, bedroom, living area, common area, etc, falls somewhere between that spectrum.
In certain circumstances, the spectrum is too broad. Most investors only care about one tiny sliver of all the multifamily asset classes, such as:
"C+/B- properties built in the 1960s - 1970s”
"A-/+ properties in the CBD"
Having such a broad scope of quality bunches attributes to closely together within a given niche.
As an example, a "Class C" kitchen that is original could rate at "4/10," vs. a renovated could rate at "5/10" even if it has:
Granite countertops
Stainless steel appliances
Modern LTV flooring
Upgraded hardware
New plumbing fixtures
To get the first kitchen to the level of the second kitchen may cost $12,000 and lead to a $150 rent premium. A difference of "1" in rating seems too low for such a significant difference in quality and rent potential.
If the AI were instead grouping properties by era first before ranking the picture, kitchen #1 could be a "3/10" and kitchen #2 a "9/10" because we'd throw the penthouse in NYC out of the equation to create more of an apples-to-apples comparison, which is much more tangible for a “Class C” investor.
The good news is that the algorithm can be refined, and this is a huge emphasis of the HelloData team. Ownership constantly tests its parameters and is open to feedback in this department.
Summarizing HelloData.ai
HelloData will change how real estate professionals conduct their rent comp analysis. AI makes collecting and organizing public online rental data seamless and at a price point that is certainly cheaper than your time is worth.
The immediate benefits of HelloData include the following:
A+ Value Proposition
Intuitiveness
Robust Data Levels
Operating Advantage
Inclusive of Smaller Properties
Operating Benchmarks (Expense Comps)
After talking with ownership, I realized this is just the beginning, and HelloData will continue to evolve and innovate. I expect to see functionality soon to account for:
Finding and Comparing Subject to 'Better' Comps - Now includes “Value-Add” Comps
Renovations vs. Original Unit Breakdowns - Coming Soon
More Visuals
Narrower/Niche AI Picture Rating System
I highly recommend that you give this software a spin. It’s a game-changer.
I'd love to hear your feedback in the comments below!
