In the 18 years that I’ve been a residential real estate broker in Manhattan, I’ve worked with many buyers and sellers who underestimate what goes into properly valuing and pricing apartments.
You might think it’s easy to price a NYC apartment. After all, most apartment buildings have the same layout in a given line across several floors, making it easier to find close comparable sales, which are known as “comps.”
That assumption has grown bolder in the age of artificial intelligence. It seems like you would just pull the numbers, put them in a spreadsheet and have AI run an analysis for you.
I won’t deny that this is how many agents run a pricing analysis. But there’s more to valuation and pricing than pure number crunching.
Pricing a home requires both quantitative and qualitative information. It’s both a skill and an art.
In my real estate career, my average ratio of Sold Price to Listed Price is 100%. That means that on average, I priced homes exactly in line with market expectations. Some homes sold for slightly under ask, some sold for over ask.
When I’m running comps on a prospective listing or on a home my buyers want to buy, the spreadsheet is only the starting point.
But numbers alone won’t give you a complete picture. The numbers only help within the context of a larger story, which is the qualitative part.
Once I have a handle on the numbers, I seek to understand that larger contextual story. This is especially important when I see an apartment that seems to have sold for under its value or above its value.
The spreadsheet alone won’t tell you what drove the price down or up.
The principles I apply to valuing and pricing homes also apply to understanding the numbers in any business. Whether you’re selling a product, filling classes in your gym or yoga studio, or looking at website metrics, it’s crucial to understand the. context of the numbers you’re looking at.
Here are some of the qualitative factors that are relevant to understanding real estate comps.
(1) Competition
Real estate is a free market, which means it’s especially subject to forces of supply and demand. If I’m looking at a comparable 2-bedroom apartment that sold six months ago, I want to get a sense of the competition that the subject apartment faced.
- How many other 2-bedrooms were on the market when that apartment went into contract?
- Did the 2-bedroom buyers have a lot of choices at that time, or was the apartment that sold the only option?
- Were the other 2-bedrooms of similar quality, or was the one that sold an outlier — either much better quality or much worse quality?
(2) Market Area
Defining the competition requires defining the neighborhood scope and understanding buyer tendencies.
If several other 2 bedrooms were on the market in the same local geographic area, that’s a very different picture than if there were many on the market in a completely different neighborhood.
This requires nuanced detailed knowledge of human behavior and preferences that AI won’t have. For example, most buyers looking on Fifth Avenue likely aren’t also looking in the West Village, but sometimes those buyers would consider Central Park West.
(3) Demand
The flip side of supply is demand. Even if there were few 2 bedrooms on the market at the time the subject apartment went to contract, it may not have sold at a premium if the dominant demand at that time was for one bedrooms.
Demand in the real estate market can be harder to ascertain when looking backward. Although AI can help by looking at search patterns, search patterns aren’t always indicative of demand. This is something you know from being on the ground, talking to people, and immersed in the market.
If buyers are looking for 2 bedrooms but there aren’t many available, they might sit on the sidelines until there’s more supply.
The spreadsheet shows the sales, but it doesn’t tell you what people were actually looking for — or what wasn’t available to meet their needs.
(4) Marketing
When the market is surging with demand, an agent doesn’t have to do much to sell a home. The true test is whether an agent can get top dollar for a seller in a slower demand market.
As I often remind my clients, “It’s not the market. It’s the marketing.”
The photos, videos, and listing description set up buyers’ expectation for the home. If the home meets those expectations, buyers are more likely to make quick offers.
On the other hand, if buyers walk in and don’t recognize the home based on what they’ve seen and read online, they’ll be turned off and less likely to make an offer.
(5) Tangible Intangibles
Another piece of relevant data that the numbers don’t tell you is the quality of the apartment and access for showings.
- What condition was it in?
- Was it staged well?
- Was it easy to access for showings?
Some homes linger on the market and sell for less because the sellers don’t make them available for showings easily, or showings are restricted to certain times that don’t work for many buyers.
Applications Beyond Business
The principles here apply whenever you’re looking at data, whether in your business or in your personal life.
In my weightlifting, I track my numbers religiously. But I’ve learned that just because the numbers aren’t increasing doesn’t mean I’m not making progress. Doing more reps at the same weight, or squatting deeper with the same weight, is still progress.
Whether you’re selling a home, a product, a service, or just tracking metrics in a hobby, it’s important to look beyond the spreadsheet at the full story.
Love it? Hate it? What do you think? Don't hold back...