New Podcast Content Ideas (JJ 670)

Transcript: 

Jack Butala:                         Jack and Jill here.

Jill DeWit:                            Hi.

Jack Butala:                         Welcome to the Jack Jill show, entertaining real estate involvement talk. I'm Jack Butala.

Jill DeWit:                            And I'm Jill Dewit, broadcasting from sunny southern California.

Jack Butala:                         Today, Jill and I talk about new podcast ideas. There's no meat to this show.

Jill DeWit:                            No, but it's good talking about the process and how we pick topics and how much that goes into them, because there's a lot.

Jack Butala:                         Yeah, you're right. It's fun, mostly.

Jill DeWit:                            It is, yup. Cool.

Jack Butala:                         Before we get into that, though, let's take a question posted by one of our members on the jackjill.com online community. It's free.

Jill DeWit:                            Okay. Jared asks, so this is awesome, he's leading into and getting a head start on House Academy is what this sounds like here. Jared says, "I have a buyer for some SFRs," so single-family residences, "but I'm not sure how to get the data that would let me know that the sellers don't have any mortgages. I looked in TitlePro247 and Real Quest Pro. In TitlePro, if I set the mortgage amount to zero, it returns zero results. The same is true for RealQuest Pro. Any advice on how to scrub out the houses with mortgages on them in the data pull? My assumption is that I would pull sale dates between 20 years ago and older, I assume, and assume if there hasn't been a sale in that amount of time, either the property's paid off or the mortgage is really low."

I like where his workaround-

Jack Butala:                         Well, and he's right.

Jill DeWit:                            That's a good workaround. Okay, if they've done it, they've been paying for it for over 20 years, maybe it's almost done. So, that was awesome.

Jack Butala:                         Jared's 100% correct in every statement that he made here. In Title Pro, zero sets it to zero, and on and on. RealQuest and TitlePro are overlays for datasets. DataTree, which is First American Title's data arm, pulls mortgage data, actual data on the [inaudible 00:01:57], from other sources, which is what we use. DataTree will be the dataset that's included with House Academy.

Jill DeWit:                            Mm-hmm (affirmative).

Jack Butala:                         So, your workaround is exactly what he explained. We've used that in the past, where you just look at the age of the mortgage or the age of the house that's purchased and kind of assume that, well, there's a good chance that they didn't refi, or, what. You're still just kind of throwing a dart at the board.

The absolute best way to do it is with DataTree, and again, it comes with the subscription when we release House Academy. It's a whole different world in there. It's 21st century. But until then, you've gotta do it this way, the way that he described.

Jill DeWit:                            Yeah, stay at it.

Jack Butala:                         And it works.

Jill DeWit:                            We'll hook you up, Jared. When we have a House Academy.

Jack Butala:                         Yeah. It works. It actually works.

Jill DeWit:                            Mm-hmm (affirmative).

Jack Butala:                         But it's just not as accurate.

Jill DeWit:                            Right.

Jack Butala:                         Wouldn't you like to just throw at the board and hit the center every single time?

Jill DeWit:                            Wouldn't that be nice?

Jack Butala:                         That's DataTree.

Jill DeWit:                            I know there's other things that you can pull in there,