Att TOM data, Datatree, there are a lot of API where this information can be handled.

If you have a few rentals and your budgets for expenses, vacancy, cap ex are working adding another unit isn't something you need to stress over "testing" because I always view my risk as being my portfolio as a whole not property by property. 

Real Estate Agents take state RE tests, pass, get their license and then go get listings and in several cases with no formal sales training.

For landlords using DSCR loans, how are you stress-testing rent assumptions and expenses before locking financing?

Here're some sample questions to test his technical competence, in any order:We're making $200k in salaries between myself and my spouse.

This morning’s economic data painted a picture of steady but unspectacular growth paired with ongoing disinflation, reinforcing the market’s current wait‑and‑see posture.

For those using DSCR loans, how are you stress-testing rent assumptions and expenses before locking financing?

100% agree — list quality beats volume.From working with different datasets and campaigns, one pattern that keeps showing up is that segmentation by actual seller pain points (not just surface filters) drastically improves connect rates and conversation quality.We’ve also seen that dialing efficiency improves when data is refreshed and cleaned more frequently, even if overall list size is smaller.Curious if you’re seeing similar lift when lists are stacked by motivation vs. single-criteria pulls?

The investors and operators that still transact consistently tend to be the ones who underwrite conservatively and pressure-test numbers before anything goes out.From my side, a big part of what I do is helping connect investors who value clean data and realistic assumptions, so fewer people waste time on deals that were never going to pencil.

One thing I'd add: once you narrow down to 3-4 markets using your framework, test them with actual deal flow before committing.