I made LA/Ventura & SF/Bay Area market analysis & sales comps tools you can use

[Steven S.]

Hey, thanks for the time, this is my first post! ...second now since I'm re-posting it in the Market Trends & Data section with more of the output charts.

I'm a UCSD Real Estate Development 2020 grad with a background in coding that got into flipping SFRs in the LA/Ventura area. When we get them at a low enough price, we build them into 3-4 unit rentals via ADUs with a 10-12% cap upon stabilization, otherwise we buy flips that we estimate will make ~20%+ return annually. Checkout 3790 Somerset Dr or 7115 Royer Ave, two of our flips that sold last month.

To do this better (more accurately, efficiently, and with more confidence), I created RUNCOMPS. I've been using it for ~2 years now, honing everything from functionality to recently building out the front-end design and using it on every property that comes my way for evaluation.

To quash any self-promotion claims, I am only looking for FUNCTIONAL feedback & suggestions from investors/developers/underwriters like yourselves on how I can improve this app to work better for you/me/everyone. There are NO purchase options on the following page, I am giving you all full access for free so I can collect feedback from the community here:

app.runcomps.org

For LA/Ventura data: your_best_friend

For SF/Bay Area data: robby the man in sf

I just finished the SF/Bay area today, here are the first 3 homes I used as a test of the Sales Comps ARV estimate function, literally the first 3 I picked at random from RedFin sold < 1 week that looked renovated. Pretend we found a fixer in this area of similar BR/BTH/SF as this property for $2.5M and we wanted to quickly know what it would be worth renovated:

Then to help estimate if your renovated product in 6 months will be higher or lower in value, use Market Stats. Specifically, I like the Specific Zipcode function with the absorption and price plotted. Dipping absorption = lower price eventually, we want to see steady/climbing absorption and steady/climbing price, it indicates a good market:

• - Its critical to realize the data to the right of the red-dash is filling up as transactions occur in the current Q. So right now, I know the 16 sales in 94402 that have occurred since 7/1/23 have been lower in $/sf than the last Q average, hover over the line for exact metrics, all these charts are interactable.
• - Or use the 'LA & Ventura' or 'SF & Bay Area' options under Sales or Rents to get an idea of ALL markets and their performance over time.

Here are other market-metrics if you do a specific Zipcode search:

Here's some of the LA & Ventura-wide search (you can get the same for the SF & Bay Area by using a different login):

Hopefully this will stay up and I can get some feedback from you all! Looking forward to chatting below,

[Steven S.]

Quote from @Carlos Ptriawan:

I see, this is your software competition for comps and ARV:

privy
pellego.com 

Yes Pellego is much more of a competitor than Zipsmart, I envy their front-end UI, very easy to use and multi-faceted, allows users to get everything from market stats to underwriting a specific property--all from one clean web app. I like Pellego a lot, and appreciate the time & energy someone over there put into making this as useful as it is.

While their UI and feature integrations are top-notch, they join RedFin, Zillow, and other market statistics tools in mostly offering averaged-data for their charts:

Averaged data is good for showing general market trends, but can't be used for much else. So even if you are averaging the Zip, City, and County level $/sf data, you are still looking only at general market trends, nothing more specific. Here is my chart on Northridge, where you can see the 'High' (renovated $/sf properties), the 'Mid' (Average), and the 'Low' (distressed) transactions:

With my chart I am able to see that in Northridge the renovated homes go for $600-650/sf, the average goes for $500/sf, and the distressed goes for closer to $400/sf. That tells me everything I need to know to validate my purchase and estimate my resale $/sf without a 'magic' machine learning algo.

I'm sure they have the same data and could apply a similar technique to segment their market data further than averages, but I've yet to see it done!