Ian Wong

Co-Founder, Opendoor · 1 appearance on the record.

computed by AI from the episodes · how this works → · full disclaimer →

Ian Wong is a co-founder of Opendoor. He is known for utilizing data science to value and purchase homes nationwide.

12statements → 4claims → 3claims resolved → 33%fully supported → 4/5average certainty → 1.58/5average debate potential →

1 supported 2 partly supported 0 contradicted 1 not checkable as stated how the 4 claims stand · each chip opens the sources

4 assertions · 1 opinion · 3 insights · 4 disclosures · every statement was checked. The predictions and assertions are the 4 claims: statements the public record can support or contradict. 3 are resolved, and 1 names no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.

The record, in short

What the tape says about how Ian argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

Their most notable supported claim

Assertion Supported
U.S. homes outside major urban centers consistently sell 3% below list price
“When you list a home in the, anywhere else in the country, you actually close for three percent less than you list for, right?”
Ian Wong Feb 3, 2017 ▶ 22:44 Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)

How they sound: speaking style how? →

288 words/min while actually speaking · 12.4 um and uh per 1k words

No argument clarity score for Ian Wong: no usable question→answer exchanges on raw tape (a fair score needs 8+). We do not score a sample that small. Roundtable and news formats yield far fewer direct exchanges than interviews.

Measured by listening to the audio itself: 4,261 words across 1 episode of raw-level tape, transcribed verbatim with every um and uh kept, each one attributed only where the alignment onto our timed stream is unambiguous. These are measurements of speaking style. We do not rank them: across this corpus, fluency and argument quality are nearly uncorrelated (ρ≈0.2), and smooth talking does not signal clear thinking. How it's measured →

Everything Ian Wong said on the MAD Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →

Insight
Data science Venn diagrams underplay the importance of software engineering and business
“I think that's the minimum bar to be a sufficient data scientist. A, B it totally underplays the importance of software engineering, and C, that's actually just a small part of what it means to be a data scientist. I think it totally neglects things like busin…”
Ian Wong Feb 3, 2017 ▶ 14:44 Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)
Disclosure
Opendoor offers home buyers a 30-day satisfaction return guarantee
“With us, we even have something called a thirty-day satisfaction guarantee. So you can actually return the home to us if you don't like it.”
Ian Wong Feb 3, 2017 ▶ 17:41 Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)
Opinion
Crowdsourcing is a completely underappreciated technique in data science
“But I'm really hoping that just in 17, as a site know, is going to be the comeback year for crowdsourcing, because we need it. And it's totally underappreciated as a technique.”
Ian Wong Feb 3, 2017 ▶ 7:17 Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)
Insight
Real estate valuation is a wide data problem, not a high-n problem
“And this is not the traditional big data problem. In the traditional big data problem, You have basically a lot of data, right, so a lot of n. Really in this problem we have very wide data.”
Ian Wong Feb 3, 2017 ▶ 8:48 Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)
Assertion Not checkable as stated
Real estate financial hedging instruments lack sufficient liquidity for practical transactions
“There are not that many available out there, and they're not liquid enough where they're attractive from a, you know, to actually transact on.”
Ian Wong Feb 3, 2017 ▶ 18:18 Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)
Assertion Supported
U.S. homes outside major urban centers consistently sell 3% below list price
“When you list a home in the, anywhere else in the country, you actually close for three percent less than you list for, right?”
Ian Wong Feb 3, 2017 ▶ 22:44 Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)
Disclosure
Opendoor eliminates friction by purchasing homes directly from sellers for cash
“We'll actually make an offer for your house and buy it from you so that you don't have to endure three months of stress and headache.”
Ian Wong Feb 3, 2017 ▶ 1:50 Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)
Assertion Partly supported
The average US home takes three months to sell, with 14% failing
“The average home takes over three months to sell, and there's a one in seven chance to deal with fall through”
Ian Wong Feb 3, 2017 ▶ 2:01 Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)
Assertion Partly supported
US residential real estate generates $100 billion in annual transaction fees
“Every year, 1.4 trillion dollars of assets change hands, generating a hundred billion dollars in fees.”
Ian Wong Feb 3, 2017 ▶ 2:27 Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)
Disclosure
Opendoor uses deep learning and crowdsourcing to extract data from home photos
“And so practically speaking, what we do is a combination of deep learning, so we have a couple boxes, and Amazon has running CARES and is kind of turning all these photos into structured data, and also a lot of crowdsourcing.”
Ian Wong Feb 3, 2017 ▶ 6:59 Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)
Insight
Human emotion causes residential real estate transactions to cluster around round numbers
“People like to close in round numbers. So you see these striations, and it's because people like to close for 200 K or 201 K, when in fact, you know, that's just totally just human emotions at play.”
Ian Wong Feb 3, 2017 ▶ 11:50 Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)
Disclosure
Opendoor flexes its seller transaction fee based on the home's risk profile
“Now, the offer that a seller gets has two numbers in them. One is the fair market value. So this is what we think your home would sell for on the market. And the other one is a fee. And that fee actually flexes depending on the risk of the home.”
Ian Wong Feb 3, 2017 ▶ 18:33 Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven)

Appearances (1)

EpisodeDateSpeaking time
Modernizing Real Estate with Data Science // Ian Wong, Opendoor (FirstMark's Data Driven) Feb 3, 2017 18m
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