The IDEAL Investor Show: The Path to Early Retirement
The IDEAL Investor Show: The Path to Early Retirement
An EASIER Way to Look for Property Investment | Cash Flow Property
Tapan Trevedi created (and patented) the S.E.C.R.R.E.T.S method to evaluate an address for real estate investors. When applied correctly, a real estate investor can CONFIDENTLY make the decision whether to invest in an address or not - Let's talk about it in this episode!
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WHY LISTEN TO TAPAN TREVEDI'S INTERVIEW:
[00:00-03:57] Be a wiser investor
[03:58-06:07] Dry Backyard Problem
[06:08-09:51] Secrets Method
[09:52-16:29] Tools for Real Estate Investors
[16:30-19:52] Is it accurate?
[19:53-21:03] Sponsor: Franchising made easy
[21:04-27:21] What to look for?
[27:22-28:21] Access these tools
[28:52-31:37] Final Thoughts
Check out his stuff at: wheretoinvest.io
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Grab my 10k/month passive income strategy and weekly newsletters at https://tinyurl.com/iwg-strategy
BOOK IS OUT! Grab Your Copy and learn how to get your feet wet in real estate investing
Tapan: [00:00:00] A metric called Deal power. So you tell them what kind of deal you are looking for and what is the power of the neighborhood to give you that deal.
Axel: Welcome to the Ideal Investor Show. This is the podcast where we help you challenge your mindset and discover where you are. Let's go. Hello and welcome to another episode of the Ideal Ambassador Show, where we always bring you great guests.
Experts or people who have really cool stuff. And today we have one like that. We have Tapan. Trivedi. I hope I said that reasonably well. You did. Yes. Tapan. Yes. And he'll explain what it is. Tapan welcome to the show.
Tapan: Yes. Thank you so much for having me.
Axel: Absolutely. Um, so before we get into this awesome tool that you have developed for our real estate investing community, tell me a little bit about your background.
Kind of like how did you get into real estate and then ultimately developing this [00:01:00] tool.
Tapan: Okay, so I started in 2009 because. Uh, I, like many of us, I read Rich Dad, poor Dad, and I clicked on something and I took a few classes and, uh, got a rental, got my first flip, and the first flip paid for like one third of the salary, yearly salary.
And it took me like a month and a half to do that because in those days, you know. Doing flip deals was easy. Yeah. So, uh, uh, that's how I got started. And then I quit the job in about a year and a half and started accumulating rentals. I believe the nice little quip that we used to do in those days was keep flip three and keep one free.
Right. So it was like, if you. Three houses, you will have enough to keep one free and clear for [00:02:00] yourself. It's not the case anymore, but in those days you could. And, uh, we did a bunch of those. And started collecting the portfolio then, you know, uh, the biggest, my biggest trend that I consider is I ran a R in Sacramento, a real estate investment association, a real estate investment club for 14 years and pre pandemic.
I ran that for 14 years, one meeting a month, and a bunch of events throughout the year and. I had a chance to have deep, meaningful conversations with literally thousands of real estate investors, but kind of understand what a newbie thinks. Like what experienced people thinks, like what's the experience level, what is the graduation gradual path, how they go up and stuff, you know?
So I understood what it is, and. All throughout. The one common thing was that there's no cashflow in a lot of places. I just had this idea that there's no [00:03:00] cashflow in a lot of places because, you know, we are feeling this locally in Sacramento. I'm sure you're feeling it in. So then I started looking around to see how many places are like that, and at that point I just said things very vague, words like.
Places it's, there's no, it's either a metro area or neighborhood or Right. Census blog or census track or blog group or whatever. But I just said places in those days, and eventually I realized that there's total 380 metro areas in the USA. Out of that 180 metro areas are such that buying a rental locally.
That cash flows more than three or 4% is impossible. So that covers roughly 110 million population that's nearly one third of the country. It's a huge problem. I. So the only thing that [00:04:00] they can, we can do, all of us people that are facing, I call this the dry backyard problem, is go remote. We gotta go someplace else.
'cause our backyard is just not giving us any safe, decent deals. So what we do is you have to go remote and there's one of the two things we, we, we do, right? We either go ahead and depend upon the boots on the ground, or we go and take a trip. Ourselves. Right, right. And I have done a lot of the land and I, uh, in my, uh, webinars and stuff, I talk about the fact that there was one time that I went into to buy an apartment complex in Henderson, Nevada, and I was put into an almost life-threatening situation because I had no idea what was going on out there.
And I was just doing my due religions check. And that's when I realized, I was like, yeah, you can't just go places. So it's like, okay, why do I need to depend upon the boots on the. What they are saying before I go [00:05:00] there and figure out what it's like, you know? So that's when I started looking for data. I'm like, you know, precise knowledge will help.
And then I finally figured out the method that we are gonna talk about, the secrets method, and then I put together this tool I. Uh, where to invest, uh, the address evaluator where you just kind of drop in an address. It'll tell you everything that an investor would need to know. So that's how I came along my, my journey.
And then finally seeing the problem, tackling it and forming this tool.
Axel: Right? Yeah, exactly. So really quick, I mean, if I had that story right, just so for the audience to understand. I would probably have to go out and figure out somebody who can make something like that. How come that you knew how to make a tool like that?
Tapan: I failed a lot. That's, I have failed a lot. I have tried so many things because it become almost like my second obsession. You know, I just started, I've [00:06:00] visiting places and they're like, okay, this doesn't work. Okay, this doesn't work. This doesn't work. So the. Aspects of the method. Secrets. Secrets is an acronym, right?
Axel: Yeah. Yeah. So
Tapan: size, economic diversity, crime, residence, real Estate Equity and cash flow, team building and swings and trends, right? That, those are the eight things. So each, uh, uh, uh, data point in their, each, each dashboard, if you may, you know, uh, uh, has each, each part of the method has like, okay, what happens if you don't do that?
The size is when I went into a small town in Texas, uh, Kyle, Texas, and I had like this fourplex out there and I was just trying to get enough cashflow to pay my, what, what was my health insurance bill at that point? 'cause I was still trying to get my cashflow. So I was going like, okay, which house is going to play for which bill?
And I went into Kyle, Texas, and, [00:07:00] um. They issued a red tag for the sign for the fourplex not being bright enough, which was silly. 'cause you know, it's just a couple of bulbs, whatever, you know, if you, if you had to like, you don't need to red tag that, you know, but you do it. So I sent a contractor to the office and they charged me $12,000.
$12,000 for just changing three or four light bulbs. And that's when I realized if you go into small towns, uh, for metro area population under 200,000, then you are always going to be a sort of a target for them because they're looking for opportunities for income. And real estate. We are always a target.
So size, that's how I came up. Well, that, okay, we always have to look for a certain size area, metro area and certain size, neighborhood. And then economic diversity. I had friends that [00:08:00] invested in, um, North Dakota about seven, eight years. You, you, if you, you've been in the game for a while, so you know what I'm talking about.
Probably. Um. North Dakota when shale oil was found. Yeah. Right. North Dakota was hot. Like, uh, you could put like five to six up to 10 trailers and, and, and make a trailer park and put a fence around it. Solar and a few porta potties and roughnecks just needed a place to crash.
Axel: Yeah. They had no housing at all.
Yeah,
Tapan: there's no housing out there. And they would pay like up to. 2,500, 3000 a month for that, because they were making 10, 15 KA month. So they were like, okay, we'll just pay that and be done with it. But then shale oil disappeared. It's, it's a, it's a short time thing. And there was literally no other economy out there to support anything else.
And then all the businesses went down. So same thing with uh, uh. The US military. If, if the military base is the only thing that is supporting the town, then you should not, I I, I don't invest [00:09:00] there because the military actually rides itself upon taking everything out in 45 days if they needed to. Yeah, exactly.
So I love our soldiers. I, I, I love our armed forces, but economically you should not if, if that's the only game in town. Right? So we say that, you know, uh, uh, not a single industry should employ more than 25% off. The occupants of the metro area. So each, uh, uh, uh, part of the secrets method of like, I know what happens if you don't do that.
So that's, that's how we kinda came along that, you know.
Axel: Yeah. So can I ask, is, is it ultimately going to give, you said you can put in any address, basically. Are you ultimately gonna get a score or like a score card? Or, or how does somebody ha that is listening to us? Have to imagine.
Tapan: So the, there's two tools, right?
So one is a neighborhood finder where you, which is a reverse [00:10:00] search. You input your parameters, what you are looking for. I have $25,000 in capital and I'm looking for single family houses, and I'm looking for this level of single family houses. I'm looking for cats. Cash flow, right? And then you can specify whether you are looking for in Pennsylvania in this metro area or San Diego or whatever that is, right?
All throughout the country, specify a geographical location if you wanted to, or you could just leave it blank and uh uh, it'll show you the best neighborhoods all over the country for your criteria. And within that we have a metric called deal power. So you tell them what kind of deal you are looking for and what is the power of the neighborhood to give you that deal.
So we have that. That's the, that's the one tool. And then the other one is the address evaluator, where you go ahead and start with the address and say, show me I wanna buy [00:11:00] this property. What's the location around that? So those are the two tools that we have developed. Yeah.
Axel: Yeah. And I think the second one is probably most.
Suitable. I, I mean, at least our clients, um, what I'm always at, um, suggesting I have done it myself. I call it clustering, right? Where Yeah. You know, especially when like we work with turnkey providers, but that doesn't necessarily mean that we only buy from a turnkey provider. So if I take an example, we buy, like in Devonport, uh, Idaho, we buy our first single family property from a turnkey provider.
I know Iowa. I, I was sorry. Yeah.
Tapan: And, uh, I, I love the Quad Cities, I love the Quad Cities. One of my home run deals is in Davenport, so I, I, I know the Quad Cities very well.
Axel: Yeah. But what I'm, me too, and what I was getting at is, so you get one in Davenport and then I, you would say, okay, I want to build a cluster of four or five or so in this Quad City area.
So [00:12:00] that would really be helpful then to say, well, it might not necessarily be from a turnkey provider, but it is meeting the criteria and it is in the same general area. Because one thing I've also learned, and I think our clients would agree and our listeners would agree, if you have already a relationship with someone who is managing your property and you tell them, Hey, uh, I am buying another one or two, would you be interested to manage those for me as well?
I, I have not ever heard that. Somebody said, no, I wouldn't. Right. So it's very rare that a property manager that has capacity would say, I don't take something in addition to an existing client's portfolio already. So then having a tool where you can actually say, for my 25, 30, 35 grand, what can I find in this general, uh, area would be perfect.
Yeah.
Tapan: And, and that's, that's, that's, that's the beauty of this. And, and we, uh, we also have a team building tab. So we [00:13:00] have a, a local realtors, investor, friendly realtors, uh, property managers, uh, uh, hard money lenders, uh, brokers, uh, contractors, all those people that you can talk. We, we have. Sifted to a few.
We, we don't know, we don't have a rating system or anything, but we do make it really easy for you to go ahead and start dialing if you needed to. So we have, we do have a team building in there.
Axel: Thank you, Tapan. Coming back to what would be kind of like for somebody who doesn't have anything in front of them, they're listening to us, what would they have to imagine the output to be?
Let's say we are taking the, the one where you put in the address, are they going to get a report or a scorecard or an overall score, or how does the output
Tapan: Right. So, uh, uh, if they, if they do the. Uh, uh, address, right? Yeah. Uh, uh, evaluator. Then they can get this nice little PDF. Of all the, uh, a, a [00:14:00] eight aspects of their, uh, uh, address in a thing, and people are using it for various different things.
So multifamily syndications, people are using the reports as a location info in the, uh, a multifamily syndications. That's one. People are using it to raise capital because when you are raising capital and you are taking the capital someplace else, the first thing that they're gonna ask you is. Okay, where are you taking my money?
What's going on out there? Right? So you kind of show them this is what's going on out there. These are all the selling facts. These are, these are the, this is the good, this is the bad, this is the not so good whatever of the location. Right? So it, it, it, it, it allows you to make your investor feel more at peace with the location, which is one of the biggest, uh, uh, things.
So that's, that's. Uh, wholesalers are using it now. Uh, they are, uh, uh, uh, basically somebody [00:15:00] in, uh, in Ohio is a big place where a lot of people are using this, uh, uh, Ohio. Uh, because Cincinnati, Cleveland, uh, Toledo, all those places, they have good cash flow and, you know, uh, the typical wholesaling, the way it works is they kind of try to get a fixer and sell it to a flipper.
Axel: Right,
Tapan: right. And that's roughly about 8% of all transactions, the flipping or the value add, right? It's about 8% of all transactions. But when you consider just the buying rental for cash flow, that is in terms of investment, like roughly about 81% of the rest of the transaction within the investment world, right?
So what people are figuring out is that. If I can just get something that cash flows nicely at just 90% of the value and sell it, [00:16:00] it'll, it is a lot easier to sell that puppy to somebody in California, right. Than it is to find a fixer and try to sell it to a local Ohio person. So that's another use case that we have.
Axel: Okay. Very cool. These, these are the different,
Tapan: yeah.
Axel: So thank you for explaining that. The, the last thing I wanted to ask you about this awesome tool is obviously people would want to have some idea, and I'm sure that you're the perfect person to answer this. How do you make sure that the data is accurate?
Where do you get the information so that you can actually create that nice PDF?
Tapan: So we have. As of a month back, we have 245 different data sources. Okay, so each graph. Kind of comes with it. And they're all different level of refreshes, like crime refreshes almost every week. Okay. Uh, there's appraiser [00:17:00] data that refreshes daily.
As you know, there's other data that comes from the a CS and that's like about once a year. There's other data that comes every month and there's different level of refreshes for it also. But, um, it's.
We are pretty proud of what we have created and we stand behind our data, right? I mean, people are using it towards, so what you
Axel: say that that data sources are like publicly available data sources or are there some, there are some of them
Tapan: that are publicly available, but we have to go ahead and massage it so that they, they meet our criteria.
So here's the biggest thing. Okay. Um. What is the first thing that people ask you when you say, I am thinking of investing in, let's say I'm just gonna pull a city out of the hat. Let Davenport, let's say we both know Davenport, so, uh, what they're gonna say is, what is the best zip [00:18:00] code? Right? Or Davenport.
Right. And zip codes literally have nothing to do with real estate investments. Really. Zip codes were built so that. Mail carriers can deliver mail efficiently. Right? That's it. It just happened to be the lowest common user friendly group of de conglomerate that was available. That's, that's it, right? Uh, but neighborhoods is how people behave, right?
Right. So, uh, and I'll, I'll send you this one, uh, uh, uh, graphic of a single zip code in Cleveland that has eight different neighborhoods right within it, right? And the property values go from 565,000 median, all the way down to 1 0 3 median. [00:19:00] In, in different neighborhoods. So there's 5 65, 3 85, uh, 1 50, 1 0 3, 1 0 3, 1 0 5, and 2 0 8.
Eight different neighborhoods, eight different, uh, uh, median property values, different levels of crime. So if you go by zip code, you are messed up. So, so to answer your question, when we get the data. We go ahead and make sure that it's going into the right neighborhood boundary and not by the zip code.
That's the one big thing that we do. Right. So there's a lot of things that we do to the data to make sure it, it's very user friendly, accurate, and usable for our users.
Axel: Yeah, absolutely. And I think that is, and that's a tech, you know? Yeah. Yeah. And that's the super important thing. Hey, let's take a quick break for a message from our sponsors.[00:20:00]
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I remember once I did some. Analysis for somebody where a turnkey provider was of, was kinda asking if we would be interested to offer their properties to our clients. And I didn't know any better. I just basically wanted to do what I could find, put in the location, you know, in into Google, basically, and said, uh, and wanted to know what the crime rate was.
It basically said way above national average, and I, I, you know, you have to keep in mind this like 15 years ago. So I'm like, okay. I don't know that I want for our clients to have properties that are in, in an area. Later when I actually, I went there. You know, I, at the time, I was somebody who actually still flew around and went there and looked at it, but I didn't go there for the crime rate.
I went, went for another reason. And I talked to a person who still to this day, a friend of mine, and [00:22:00] he said, yeah, but see, what you didn't do is you didn't look at what this statistical value actually meant. I'm like, what do you mean? What? What are you telling me? He said, well, this particular thing that you looked into, it compared the crime rate in our area to a crime rate that was measured per 100,000 people.
Right? And so if you have a small location and they have one crime in a year. The whole location is 10,000 people. The percentage per 100,000 is off the charts basically. You know? Right. You know, and, uh, that's what I do. You wanna, do, you wanna hear what,
Tapan: what, what we have done for that?
Axel: Yes, sure.
Tapan: Our crime dashboard has.
First of all, two categories of crime, personal crime and property crime, right? And the personal crime is, uh, murder, rape, assault, and robbery. And the, uh, property crime, uh, are, [00:23:00] uh, burglary, larceny, motor vehicle crime, things like that, right? So personal crime brings down both property values and rents, property crime.
Brings down mostly just the rents. It doesn't affect the property values as much. It's some, so for each crime, we will give you where the neighborhood falls compared to all the neighborhoods in the country. We just have this nice little speedometer graph that you can see where it falls all around the country.
And then we give you another graph that tells you how it is compared to the metro area. So how, where it falls nationally and where it falls locally, you can make a decision like that real quickly because the thing is, we don't, we are not statisticians, right? How do we go ahead and, and determine anything in real estate by comps, right?
How do [00:24:00] we determine the value of rents? We look at similar rents in the in, in, in the neighborhood and figure out, okay, these are the rents. Of these units, how do we prep the value of properties? We look at comps. So we created neighborhood crime comps, right? That you know, you can compare the neighborhood all over the country and compare the neighborhood locally and figure out is this something that is tolerable or not?
And then we give you nice little guidelines, okay? With nationally read in more than one high risk. Don't, probably don't, don't go there. But, you know, if it's property crime, one of the property crime is red, everything else is green. That's a rental neighborhood. Your rental neighborhoods are gonna have slightly higher elevated crime.
You're not gonna get the top best a neighborhoods, uh, as your rentals. That's not gonna happen either. You know, so, so that's, that's how we tackle the crime problem, because we also ran into that same thing. It was like. [00:25:00] If I put something like the crime, the chances of being hit by crime, this crime is one in 41.
What does that mean? Like, I'm not a gambler. Like I don't know what that means. Like why do I, why do I need to compare it to like what? One in 41? What does that mean in poker? What does that mean on craft table? Do I need to do that? No. We need to go ahead and figure out what is it compared to the rest of the name.
Axel: Yeah, absolutely. And, and that's basically what what I was getting at when I asked you about the quality of the data because a lot of, you know, we oftentimes get information. Without necessarily looking in any level of depth on how that information or that data was actually put together. And you mentioned at the very beginning, like certain things get updated every week.
If you ha happen to hit at the wrong week in the wrong location, it might look like horrible and a month later it all smooths out if nobody actually does anything to it. You know? So there's all kinds of different. Things. That's the, I
Tapan: mean, there's [00:26:00] not, there's not that many wild swings in neighborhoods in terms of safety.
So the size, economic diversity and crime are the three main safety. So that's why they are the first. Yeah, yeah. Right. Then it's the uh, um, residence and real estate. What kind of residence, who lives there that. We have to watch closely because populations kind of go up and down depending upon the economic swings locally, right?
So that is the more, uh, uh, neighborhood population, graph, all those things. That's what we watch a lot closely. And then what kind of income swings are happening within the metro area and the neighborhood? That's, those are the two things that kind of vary a lot. And those we have seen change. In like six months, but weekly, just because we, we get the data.[00:27:00]
It doesn't make that big of a dent. It's, it's dependable data, if that makes sense. Like there's, there's not that many, the neighborhood, the neighborhoods doesn't change. They don't change like that. It takes time. It's a social change, right? I mean, and people Right, right, right. Figure out it, it doesn't happen overnight.
So that's the.
Axel: That's very good to know. Thank you so much. So now that we have basically teased people to really say, where can I, you know, how can I get this? How can I take a look at it? Where do I sign up? Tell us how, how, either with you or where do they need to go if they're interested to take a look at it.
Tapan: Yeah. So the website is where to invest.io. Okay. And the easiest way to kind of figure out what we are all about is the first thing you all want to know is. What kind, where to invest? Like what's the best city? What's the, where's the best cash flow city for me? Right? So what you are going to do is go to, we have created [00:28:00] a free quiz for you guys, right?
So go to quiz, where to invest IO slash Cashflow City. That's quiz where to invest io slash cashflow City and answer a few multiple choice questions and it'll tell you exactly. Uh, where to go. Uh, and it'll give you the top six cities that, uh, uh, match you and stuff. And then if you're interested in the exact neighborhoods, then our starting plan that just, just try us out monthly plan starts at like as low as under 50 bucks.
Right. And that's just on the website and stuff. And you can start it. Uh, no problem. Uh, it's, we want to go for the masses. Uh, uh, instead of going for the big data conglomerates and stuff like that. So, you know, we, we want to go for the mom and pop investors more than anything else.
Axel: Awesome. Okay, well, thank you so much, Tapan.
Last question I wanna, uh, ask real quick that has nothing to do with all that investing and, [00:29:00] and software stuff, is if you could meet anybody, who would it be and why?
Tapan: Uh, alive or from the past? Or could be anybody? Literally. Anybody. Literally, yeah. In current terms, I think Melania Trump would be one of the most interesting persons to me because she has had a front row seat to so much and she hasn't spoken pretty much anything.
Right. And what a story. I mean, she come from a. She, she's, she's, I'm from the third world. She's not from the third world I say, but she's from 2.5 world. She's almost there where she's from. When came and she made it to, when she
Axel: came, when she originally came, it was the third world.
Tapan: Yeah. And it's, it's, it's an amazing story.
Say what she will about her, but I mean. Talk about the will and she positioned herself and played this right. And whatever it is, I, it's a fascinating story that, uh, and I, I read her book and [00:30:00] it only scratches the surface and there's so much that I wanna talk to her about. So that, that would be my, my, my go-to.
Like,
Axel: yeah, that's an interesting choice. I think you're the first one. Who, who chose that one? I'm, it's kind of a little bit like the, the Djokovic, right? Like the tennis player kind of situation, because. He is a pretty crazy story too, you know, so
Tapan: Oh, is that, oh, I, I, I, I, I, I know I'll, I'll have to look up Jocko.
Yeah,
Axel: yeah. They're both from Serbia. Okay. Yeah. And, and it's, um, I mean, he is younger than her, obviously, but it's Oh, yeah, yeah. Even, even when he, I mean, for, for somebody like him to be trying to become a professional, sports, anything, you know, so yeah. These, these are always the most amazing stories for people who come from places where it's really, really tough, tough to ever get out of.
Tapan: Right. And, and it's, it's. Anyway. It's a, it's a, I would love to meet her if I can.
Axel: Yeah, absolutely. Cool. Well, when you do, [00:31:00] tell us about it. Okay. Yes, I will. Alright, cool. Tapan, thank you so much for coming on the show and I, I think you did something great and I will definitely take a look, uh, on behalf of our audience and, and give them some feedback of what I learned from it.
Wonderful.
Tapan: Thank you so much. Excellent. Thank
Axel: you.