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All Forum Posts by: Stephen Morales

Stephen Morales has started 12 posts and replied 344 times.

Post: Machine Learning to predict comps

Stephen Morales
Posted
  • Jacksonville, FL
  • Posts 371
  • Votes 185
Quote from @Eric Fernwood:

Hello @Johann Villalvir,

Congratulations your accomplishment.

Some background: I am an engineer and what I do in our investment services business is primarily data science and software development.

We use data mining software to evaluate thousands of properties based on about 40 behavioral characteristics of our target tenant segment. The software performs the following functions:

  • Eliminates all properties that do match our target tenant pool segment.
  • Selects sales and rental comps for evaluating rent and return.
  • Generates investor analytics. We provide actionable information, not MLS data sheets.

I’ve experimented with increasing the scope of our software. However, despite trying many approaches, I have failed to consistently meet our accuracy and consistency requirements.

Today, we use a hybrid solution. We reduce the number of investment properties to consider by about 99.6% using our data mining software. Then, we match the properties that passed the data mining engine against the specific financial situation and goals of individual clients. Next, we manually evaluate each property. At the manual evaluation step, approximately 60% more are eliminated. Additional software estimates renovation costs and provides actionable analytics. We have never shipped MLS data sheets.

Below are some reasons why taking the next step with software, has not been successful for me.

  • There is a lot of inaccurate information in the MLS. A recent example, "How much is the monthly association fee?" Answer in the MLS, "Yes."
  • Computers cannot accurately determine whether a property is located in a desirable or undesirable area for a particular tenant pool segment using photos or aerial maps. There are more location considerations. For instance, even if a property has excellent characteristics, it may not rent if there is a significant amount of traffic on the street. This determination can only be made if you know the specific street.
  • An onsite evaluation is essential. For example, if there is a barking dog next to a property, it will not rent. How can software determine the presence of a barking dog?
  • Zillow and OpenDoor attempted to use software to predict the sale price of properties and their results were/are bad because their software was poor and the inherent limitation of software to deal with subjective data. Zillow lost so much money that they decided to exit the flipping business, while most of the OpenDoor properties we see in Las Vegas are sold at a loss.

In my experience, software can only go so far when humans are involved. Our hybrid approach has worked well. If there is a better approach, I would like to understand what it is.

Thanks for your post.


This is a really interesting approach. sounds like you've created a robust framework for filtering properties efficiently. I'm am curious though, when you're evaluating tenant behavior and narrowing down properties, what kind of data sources are you using? I'm assuming you're primarily leveraging MLS data, but would you be willing to share a general idea of what those other datasets are that are used to improve accuracy?

I've seen how inaccurate MLS data can be, so I'm always interested in learning how others verify and refine their data. We always encourage users to do their own comps and not rely on automated valuations as they are more so a general guide then a highly reliable metric. There are some things you just can't automate I suppose.

Post: Is it worth buying I am looking to buy a rental property 439,000. First time Investor

Stephen Morales
Posted
  • Jacksonville, FL
  • Posts 371
  • Votes 185

You're unfortunately going to lose more than you're adding to your original numbers. 

As a first rental property I would definitely advise against purchasing a negative cash flow property just to claim losses or bank on appreciation. 

If you're local market is the issue I would definitely venture outside of that and look for other markets and go virtual. 

Post: PrimeTracers – Free Property Data & High-Accuracy Skip Tracing! No Subscriptions!

Stephen Morales
Posted
  • Jacksonville, FL
  • Posts 371
  • Votes 185

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Post: Introducing PrimeTracers: The Go-To Solution for Free Nationwide Property Data

Stephen Morales
Posted
  • Jacksonville, FL
  • Posts 371
  • Votes 185

Hey BiggerPockets community!

If you’re in the business of real estate, you know that accurate data is the key to finding great deals. That's where PrimeTracers comes in!

At PrimeTracers, we provide nationwide free property data to help you build custom, hyper-targeted lists. Whether you're a REALTOR, a wholesaler, investor, mortgage broker, private lender or in property management, you can easily access property records to find off-market opportunities, landlords, refinance opportunities, and distressed properties.

What We Offer:

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Why Choose PrimeTracers?

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  • Pay-As-You-Go: Only pay for skip tracing credits when you need them—no minimums or contracts.

PrimeTracers is designed to give you the edge in lead generation, helping you reach the right property owners and prospects to grow your real estate business.

Feel free to DM me or visit our website to see how PrimeTracers can help you streamline your marketing and lead generation. Let’s take your outreach to the next level!

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