Over the decades, today's interest rates are historically pretty typical.

Beyond (formerly Beyond Pricing) – Useful for dynamic pricing and also provides some solid market data.   

that we’ve learned in our 24 years, managing almost 700 doors across the Metro Detroit area, including almost 100 S8 leases:Class A Properties:Cashflow vs Appreciation: Typically, 3-5 years for positive cashflow, but you get highest relative rent & value appreciation.Vacancy Est: Historically 10%, 5% the more recent norm.Tenant Pool: Majority will have FICO scores of 680+ (roughly 5% probability of default), zero evictions in last 7 years.Class B Properties:Cashflow vs Appreciation: Typically, decent amount of relative rent & value appreciation.Vacancy Est: Historically 10%, 5% should be applied only if proper research done to support.Tenant Pool: Majority will have FICO scores of 620-680 (around 10% probability of default), some blemishes, but should have no evictions in last 5 yearsClass C Properties:Cashflow vs Appreciation: Typically, high cashflow and at the lower end of relative rent & value appreciation.

Lots of data there.

that we’ve learned in our 24 years, managing almost 700 doors across the Metro Detroit area, including almost 100 S8 leases:Class A Properties:Cashflow vs Appreciation: Typically, 3-5 years for positive cashflow, but you get highest relative rent & value appreciation.Vacancy Est: Historically 10%, 5% the more recent norm.Tenant Pool: Majority will have FICO scores of 680+ (roughly 5% probability of default), zero evictions in last 7 years.Class B Properties:Cashflow vs Appreciation: Typically, decent amount of relative rent & value appreciation.Vacancy Est: Historically 10%, 5% should be applied only if proper research done to support.Tenant Pool: Majority will have FICO scores of 620-680 (around 10% probability of default), some blemishes, but should have no evictions in last 5 yearsClass C Properties:Cashflow vs Appreciation: Typically, high cashflow and at the lower end of relative rent & value appreciation.

Problem with underlying data and assumptions.2.

I’m also using Facebook Marketplace and Rentometer for SFH/MFH, but—like you said—MHP data is a different beast.

1) I think it’s “funny” that not one news article I ever read for the last 5 years had headlines like “Housing at historical record lows!

I have the contract to use them sitting in my email now so I saw a preview of all the data and it's pretty incredible.

The model flagged listings that could likely generate more revenue with better descriptions.4.Market Comparison: Using Zillow Zestimate APIs and AirDNA, they compared similar properties in the area and forecasted how much more the property could make if the photos and descriptions were improved.5.Property List: All of this data was organised into a Google Sheet for further review.6.Automating Outreach: They used Claude to generate personalised outreach emails and DMs to homeowners, pitching offers for the properties.The entire process revolves around identifying undervalued homes that look worse online than they actually are.Has anyone seen anything like this?