I have some experience with this that I figured is worth sharing, though it's not directly related to the article. Recently, I developed a quick tool that checks the demand for a given type of property in a given geographical area and compares it with the demand for a single listing in question in order to find discrepancies. The discrepancies are typically asking prices that are either far lower or far higher than the demand for that kind of property in that area. I marketed this to a number of brokers as a way of calibrating how quickly they wanted to have a listing turn over, and offered a few price adjustment suggestions to their listings.
I failed for a few reasons, and I think it's worth outlining them here so that other people don't fall into the same traps if they decide to make tools for the real estate industry. YMMV, and take what I say with a grain of salt.
1. Real estate isn't as quantitative as I wanted it to be in my mind. Emotional "pulling out of their ass" price assignment was the rule, with no exceptions. Most of this works to the advantage of the people handling real estate, as it prevents them from being held accountable for judgment mistakes (as decisions are completely and purposefully subjective) within their own organizations.
2. Real estate folks aren't tech-savvy. Not even a little, and not even the ones that claim to be. Even getting the full functionality out of Zillow was beyond most of the folks I talked to. The best I saw any of them do was a table that calculated averages in Excel. This fact means that any product you deliver or show them has to be non-beta, completely polished, functioning flawlessly. They are used to selling people on existing features, and analyze products as such.
3. Honesty in business practices isn't considered desirable. Point blank, one of my early clients told me that they'd have their representatives at the open house try to screen out people who didn't appear wealthy enough to purchase the property at the high-end cost estimate they had agreed on internally. I was trying to sell him a way of justifying different price points quantitatively rather than qualitatively, but I'd completely missed that such justifications aren't wanted because having a formal structure prevents casual exclusion of the "wrong" type of people.
IME, real estate agents attending open houses are generally the more junior agents and the purpose is less about selling that specific house than it is about finding new potential buyer clients.
I took a prototype of a new app to one of Sydney's top real estate people.
He told me to sit down for a frank chat: "Good real estate agents focus their energy on selling houses. Great ones focus all of their energy on signing up new listings." Anything that is just there to benefit the client is really of no interest unless it achieves the latter.
Thank you for the detailed post - very helpful for me. If I may ask, what were some of the factors that you used to determine the demand for a property in a given area?
Median turnover time, price shift from month to month, demographic/socioeconomic data on prospective buyers. It's all quite simple, and behaves exactly as you would expect within urban areas-- as skeptical as the brokers were, their narrative to justify prices almost always ended up very close to the quantitative estimate. Suburbs and commercial real estate are much harder to nail down correctly.
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[ 4.9 ms ] story [ 12.8 ms ] threadI failed for a few reasons, and I think it's worth outlining them here so that other people don't fall into the same traps if they decide to make tools for the real estate industry. YMMV, and take what I say with a grain of salt.
1. Real estate isn't as quantitative as I wanted it to be in my mind. Emotional "pulling out of their ass" price assignment was the rule, with no exceptions. Most of this works to the advantage of the people handling real estate, as it prevents them from being held accountable for judgment mistakes (as decisions are completely and purposefully subjective) within their own organizations.
2. Real estate folks aren't tech-savvy. Not even a little, and not even the ones that claim to be. Even getting the full functionality out of Zillow was beyond most of the folks I talked to. The best I saw any of them do was a table that calculated averages in Excel. This fact means that any product you deliver or show them has to be non-beta, completely polished, functioning flawlessly. They are used to selling people on existing features, and analyze products as such.
3. Honesty in business practices isn't considered desirable. Point blank, one of my early clients told me that they'd have their representatives at the open house try to screen out people who didn't appear wealthy enough to purchase the property at the high-end cost estimate they had agreed on internally. I was trying to sell him a way of justifying different price points quantitatively rather than qualitatively, but I'd completely missed that such justifications aren't wanted because having a formal structure prevents casual exclusion of the "wrong" type of people.
I took a prototype of a new app to one of Sydney's top real estate people.
He told me to sit down for a frank chat: "Good real estate agents focus their energy on selling houses. Great ones focus all of their energy on signing up new listings." Anything that is just there to benefit the client is really of no interest unless it achieves the latter.