Hey Arubis, you're absolutely right. I copied the model from Scott (even the domain name). I'm unabashedly a huge fan and early subscriber of his newsletter since mid-2014.
Congrats on shipping! I was looking for something like this.
I did see that you have 1 past deal listed on home page. It would be great if you can add just a single page titled "Past Deals" or "Highlighted Deals" and show a few houses that your AI bot identified. That's more likely to encourage potential subs.
Also, how do you calc the CAP rate etc? Do you crawl existing sites that already have this data, or do you generate it on the fly? If the latter, how?
And how does your site / email list stack up against the following (which I think are somewhat related to what you are doing).
1) RoofStock.com - https://www.roofstock.com - Based in Oakland, they do end to end investing online, from intent to closing on mortgage. Most are already rented too, and they even provide Property Management services. They have a great engineering team. I even landed a Sr. Software Engineer position with them last fall, but ended up turning it down. Highly recommend if you are looking for a tech job... I think they are still hiring.
2) Mashvisor - https://www.mashvisor.com - Based in Silicon Valley (I think). They identify and list properties with AirBnB and Vaca rental potential. I like them too, but their sales team is very pushy and you can't do anything without signing up for a monthly subscription. I had a demo with their sales guy last year, and the whole thing was geared towards getting me to signup and pay.
Hey Larry, quick recommendation for your photo at the end - you should probably get a better professional photo that conveys reliability and confidence in your body language, or at the very least, flip the image so it draws readers' eyes toward the text.
Real-estate investors are not looking for houses in the US and Canada. They're looking for investments in Los Angeles, or Kansas, or Salt Lake City, or Arlington Virginia, et al. If you're sending deals to someone in Arizona, for New Hampshire or South Carolina properties, they're overwhelmingly going to fall flat.
Whenever you have the listing breadth to do it, you need to segment the emails down closer to the end user location, or at least make that an option when they sign-up. If I'm looking for a real-estate investments as a normal tier investor (ie I'm not super rich) that might own between one and a few properties, and I live in Boston, I am not investing in properties in Phoenix outside of unusual circumstances (eg the great recession, or going in with someone I just happen to know from there that will handle things locally in Phoenix).
I'd probably go further and suggest you knock down the pin for a specific market first, before sending out broad spectrum listings spanning the US in an email list. Starting out beyond that narrow focus, imo, dramatically increases the odds of failure, that you never properly connect to your email receivers (they don't get enough properties for their local interest, and dump your email list).
I think the business model is based on email subscribers. OP has mentioned elsewhere[1] here that he modeled the site and offering very closely based on Scott's Cheap Flights .com which was in the Cheap Flights domain.
What exactly constitutes a "cheap house" though? Just because a house is ultra cheap in absolute sticker price does not make it a good deal, or even "cheap". It's a combination of neighborhood home values, property taxes, school system, local economy, demand, geography, appreciation rate, and climate which make a home a good investment, with the actual home itself mattering least among those. There's definitely a lot of undervalued real estate in the US, but just looking for cheap houses is a bad idea.
So it scrapes lots of listing websites and emails when there’s a good deal? What qualifies as a good deal? How does the were does the deep learning fit it?
Interesting idea, maybe you could put more info on the linked page.
It sounds like a bullshit statement, to be honest. This is probably just a hand-picked curation of listings that fit the criteria this guy uses to determine if it's a good investment or not.
In fact that often defines a great deal. If a house has a problem and you know how to deal with it but most buyers won't want to bother, that can make a really great deal.
This could be useful. I find it interesting that the two examples of cheap houses on the front page are in areas that have had severely damaging weather but I guess you could find cheap houses there. Will I get notifications for places in Detroit as well?
I think this site will work in many cases except the best. The best cases come from finding an owner before they list their home, which is pretty rare. When there's a service that does that I might consider signing up.
What is the pros/cons between this and something like Realty Shares?
Wouldn't sending an email to a bunch of RE buyers create demand for a cheap property, which would (in theory) raise the bid, which would cascade to making the listing "not cheap"?
- Playing devils advocate on this one since I'm sure not everyone would bid for the same properties.
Pressing the button without entering an email results in a popup that says:
Error!
Please contact us at founders@larryscheaphouses.com and we'll figure out what's going on.
Considering the number of people that are going to glance over the text and assume that the button lets them see the deals you might want to have some basic help text.
Great idea! I’m looking to invest in real estate and have found the hardest part about it is surfacing interesting deals. If an AI can be parameterized to search for me, so much the better.
IANAL but it looks like -- and it's hard to tell for sure, as there is no sample email -- OP's site is "Linking" w/ some additional data, not "Listing".
This is such buzzword powered horseshit. Absolutely nothing about this problem domain requires Deep Learning. Simple regression models if implemented properly can do just fine. Not to mention that sites like Redfin/Zillow have access to far more data and already have pretty good models for the most part. Just because you can throw a Neural net at a given problem, doesn't make it the right thing to do...
I'd be a lot more forgiving if the site that was linked was an actual blog post that contained information on how deep learning helped tackle this problem. But all the site is, is a way to aggregate emails while throwing buzzwords in your face.
As much as I like the phrase "buzzword-powered horseshit," there are always opportunities to apply new technologies in a creative way. In this case, it seems obvious to me that NNs will do a good job in identifying latent features that would otherwise slip past a linear model.
Sure, NNs "could" do that...but they are far more likely to just memorize a bunch of stuff when someone who isn't well versed with ML just applies an out of the box solution to a problem, looks at a simplified cross-validation number (I hope) and assumes that NN is better than some simpler model.
If the OP had actually posted a blog talking through things he did and how the NN helped and why he believes it is actually learning something useful and not just learning the noise, then this would certainly be interesting. But I've seen far too many people take powerful, flexible models with a large number of parameters and throw them at simple problems, with insufficient data and thought.
I'd normally give someone the benefit of the doubt...but taking the sum total of the quality of the linked web page, the complete lack of any meaningful information, as well as op's reply to my comment that added no real useful information regarding the actual benefit of throwing deep learning at this, I'm still inclined to stick to my original feelings regarding this post.
Hey there. I found that regression models do okay when the feature-set is simple. And I can see that deep learning seems like overkill but I found that it can create models that does justice to the complexity of real estate.
It's not just technical decisions... the entire site is a single web-page with zero content except for trying to harvest emails. I mean, if you want people to spam such low quality stuff on HN, then I guess that's your prerogative. But I usually enjoy the much higher quality stuff that people post here on HN and I'd hate for the bar to drop this low.
Yes. It's completely overblown. To me, that demonstrates that the person behind this is either a) ignorant of the fundamentals or b) just riding the hype wave to attract the naive.
There is of course option c). That would be that taking a contrarian view on the technology will provide a strategic advantage to a business. But I don't see how that would apply here.
No privacy policy is kind of a red flag. I mean I'm assuming this is a proof of concept / work in progress, but I also have to assume you're gonna want to monetize it at some point, so I want to know what you're gonna do with my e-mail address before I give it to you.
What's funny is I'm not even sure if I mean that accusatorially or admiringly. Maybe both.