We aim to balance thoroughness with fairness to ensure compliance.

There are several great resources for data. 

. - Property type (single-family homes, duplexes, or small multifamily)- Min/max square footage or number of bedrooms and bathrooms- Desired cash flow or ROI metrics to ensure profitability- Property Condition (turnkey, light cosmetic fixes, or heavy rehab)- Neighborhood type (A/B-class areas for appreciation vs.

The differences lie in how they aggregate, update, and present the data.

This ensures the landlord is notified any time the policy is changed, canceled, or renewed, making it easier to track without relying on the tenant.The difficult part is enforcement.

That puts any of their data sets into serious question.

I'm data driven and would love to immerse myself in IL, AL, MC specific property, demographic and investor-centric data sources the same way I've done in my previous area of focus.

I’m exploring ways to automate my deal analysis process and was wondering:1.Is there a way to programmatically pull MLS data?

This conveys confidence and ensures you don’t end up overpaying or taking on unfavorable terms.Negotiate More Than Just PricePrice isn’t the only factor in a deal—other terms can often be just as valuable.

To ensure you’re acting ethically:Full Transparency: Be upfront about your intentions and ensure the organization has all the information it needs to make an informed decision.Fair Value: Offer a price based on fair market value or justify any discount with clear benefits (e.g., taking on deferred maintenance or providing a quick, hassle-free transaction).Win-Win Mindset: Emphasize how the sale could help the organization, such as freeing up funds for its mission or relieving the burden of maintaining a distressed property.4.