Quote from @Joe Daniel: Quote from @Dave Harlan: Quote from @Joe Daniel: Hey Dave, lots of investors build their buyers list by tracking activity from local public records especially recent cash purchases, LLC transfers, and repeat buyers in the county.It helps you identify who’s actually buying right now instead of collecting random emails.If you ever want to talk through ways to source or organize that data efficiently, happy to share what I’ve seen work well for others. 

Clean, localized, well-segmented data tends to outperform UI once costs tighten.From what I’ve seen working with different datasets, how those addresses are sourced makes or breaks downstream efficiency.Curious how you’re sourcing or filtering the addresses that feed into the API flow — manual criteria, stacked lists, or something else?

Your just buying data.

Check it out - if you are interested I can give you pro access to test it out.

I spend about 10 minutes per house analyzing the online data to determine if it's worth a physical visit.

Economic data this morning reinforced the same theme markets have been grappling with all week: cooling but not collapsing.

We specifically look for areas in the suburbs to build but there has to be SOME data to support a new venture.

The property is high on lead they said they had a test done , I’m definitely worried about opening walls or ceilings that have huge cracks in them and disturbing the lead.

House hacking a duplex/triplex is a solid first move A few things that help early: lock in one target area, run conservative rent comps, and stress-test the deal with higher expenses than you expect.

I started looking into more things a LLM (large language model) would be capable of doing and started working on a couple features to help with some of the repetitive data entry I was doing every month.I'm curious about learning how people do bookkeeping and some of the things they dread doing?