This is the text transcription of the above video Experience the Honesty of Sell-Star
(From the Video): So, this is just one overview and example of the 150 neighborhood Sell-Star services. And what we're going to concentrate on is this price per square foot above grade—the price per square foot for anything other than the basement in this particular neighborhood.
And what we've done here is we've laid this out on a spreadsheet—the last 100 home sales, and you'll see that it goes from the lowest sold price of $180 a square foot, to a high sold price of $342 a square foot.
Every neighborhood has this kind of spread—some a little bit less, some substantially more. It's the goal of sell star to explain to you what creates this spread. Because once you understand what creates this spread, you understand what creates value in your home, what the buyers for your neighborhood most demand, how to prepare your home for market and how to maximize the value of your home with limited effort and expense.
Now the very first thing that I really want to dispel for you is essentially the way the entire real estate industry values your home. If you've ever had a CMA done by a realtor or an appraisal done, you know that they look at square feet, and let's say your home has 2500. And another home, one of the comparables they’ve chosen, has 2700 another has 2900, and the third has 2800. Because each of those homes are bigger, they automatically reduce the value of your home based on that mathematical function, you know, and there's no standard, there's absolutely no standard. There's no rule that says how much a square foot of your home is worth. It's all rationalized and deduced by the person making that analysis.
Same thing for bedrooms and bathrooms. If your home has three bedrooms, and all three of the other comparables have four bedrooms, they're going to reduce the value of your home by the value of one bedroom. Same thing as before: there's no rule that says what a bedroom is worth.
Same problem on bathrooms and for finished area of basements—realtors and appraisers reduce your value if has less of something that another home has—all based on their opinion.
Below grade finished means the basement finish area, the amount of the basement that is finished. In this case, this home is about 50/50 half finished, half unfinished. This one's fully finished with 838 square feet of basement available, and a third with 1100 of unfinished space or zero finished space.
They may make an adjustment based on the year of construction, how old the home is. And they love to make adjustments based on your lot size.
Now we've got this spreadsheet set up based on the lowest price per square foot for this neighborhood that's sold to the highest price per square foot. And we'll see right away why this this does not work. Let's scroll all the way down. And we'll look here and in the upper price per square foot is one of the smaller lots. Close by is another small lot. So, what I'm saying is there's no consistency—as in large lots equal large values.
And part of what Sell-Star does is figure out what the buyers were really paying using the last 100 buyers, not three. Evaluating the last 100 buyers, we figure out what they paid for. And in this case, and this is just really quick based on this spreadsheet—we're going to analyze this statistically using Sell-Star in just a minute—but you and I can already see on the basic spreadsheet that lot size is not statistically relevant for the buyers in this area. Nor is the age. Now most of these homes are within 10 to 15 years of each other. And statistically you could see why that wouldn't be very significant.
We're also going to statistically test all these using Sell-Star in this video. Let me explain, Sell-Star does not have any pre-biased assumptions on value. Sell-Star's goal, it's only purpose, is to figure out what buyers in your neighborhood—each one of these Sell-Star analyses is done custom in your neighborhood—most desired by demonstrating what these last 100 buyers actually paid more to obtain. There's no preset values in Sell-Star.
Let's look at finished basement. We've got some zeros, 813, and 1300 square feet. And let's go all the way down to the top selling prices. And you'll notice, oh it's very similar. And so what I'm saying is Sell-Star is going to look at all this to determine what these buyers in this neighborhood paid for. And your neighborhood may be a little bit different. Don't think because one analysis, if there's not that much difference in value, doesn't mean your neighborhood isn't different than that. And so again, these all have to be custom designed.
Let's look at bedrooms: lowest price per square foot had four, we have an occasional five bedroom. Typical seems to be about four, we've got some threes, we've got some six. Let's go all the way down to the highest price. All fours and threes. So, it's exactly the same if you look at this, based on the lowest priced homes, in fact in the lowest price homes there's not even any threes. So what we're saying here is the buyers for this neighborhood are not going to freak out whether it's three, four, or five bedroom home. It's not going to make that big of a difference in how much they demand homes in your neighborhood.
Let's look at bathrooms really quickly. And again, we're going to prove this all statistically on this video. I just wanted to warm you up so you understand what's going on here. We've got some threes quite a few threes and fours. We've got a two. But that's almost heading toward the middle part of the curve to some threes and fours, a lot of threes and fours, occasional five. Now sliding all the way down to the top priced homes per square foot. Oh, no. We've got some twos. So, what this is telling us already logically, is your realtor should not be breaking out a comparative market analysis and bludgeoning your value because you only had two or three bathrooms in this neighborhood. And again, we're going to go through this statistically, I just wanted to warm you up to the concept of the way things have always been done.
I'm kind of going out on a limb here a bit. The way things have always been done, I think are quite wrong. And I'm going to show you through the Sell-Star System why that is. It's not my opinion; it's not my bias; this is statistically proven. And let's go into that right now.
So right now, what we've done is we've snuck into the brain of Sell-Star. And I just want to reiterate, this is not about math and data science and statistics. What this is really about is just giving you honest, truthful information about what buyers in your neighborhood most desire and pay the most to attain. And that's what it all comes down to.
But let me give you a quick overview so that you know that I'm giving you the truth and the proof on what these buyers really want. So remember, our spreadsheet, our little Excel spreadsheet? That's it right here. And this is a second version of it. This has what we call quantitative data, which would be the square feet and bedrooms and baths, and lot size and all those things. The qualitative data are more descriptive text things. And these are the ones that typically trigger the highest emotions, you know, refinished hardwood floors, new carpet, park-like backyard, new paint, those sorts of things. And we look at both of those. But we do it from different analyses.
And these little modules, these little nodes that you see—this is not like some PowerPoint presentation. Each one of these things is a complex algorithm on its own. It's performing thousands of statistical or mathematical functions based on what I've told it to do and the purpose of my analysis. And again, none of these have any preset values or biases. They figure out what the buyers spent their money on, so that we can tell you.
Now bear with me while we try to zoom out a little so you get a little bit of perception of what the system's like. This just gives you some idea—that tiny little orange dot is our spreadsheet data from your neighborhood's last 100 home sells. And these are some of the system analyses that I had to put together to give you this unbiased truthful advice on what the buyers most desire. Let me zoom back in so this starts making sense.
So, the first thing I do is I take our spreadsheet data, the information about home sales in your neighborhood, and I come down here and I run what's called a clustering algorithm. And it's how I assign QValues.
Remember on our spreadsheet, you had the lower price-point of $180 in this example, and the high price-point was $340. What we're doing here is we're allowing the system to parse or group this valuation information into different what I call QValues, quality values. It's all part of my system. The clustering algorithm may create a $180 to $215 group. And then it might create a $216 to $245 group. It does this on its own after being trained, so that we can figure out what kind of qualities those homes had. And why they were at those price points.
In other words, when you give buyers more of what they want, your home sells for more money. And that's what we're trying to figure out. So, the first thing we do is cluster those into groups, and I won't drag you through all of these, but there's thousands of little steps going on here.
We're going to go over to the initial regression analyses. So, what we're going to do now is using that exact same spreadsheet that you and I looked at, we're going to let the system look at it statistically on this first initial regression. And it's going to look at all that physical criteria that agents typically value your home on: bedrooms, bathrooms, square feet, garage spaces, lot size, all those things, plus a few of my own proprietary measurements that I'll just kind of gently explain to you at that time.
And I've had to do a few things to prepare it. But we're going to go ahead and take a look at the linear regression and the output that the system came up with. What's going to be pretty cool here is the stuff that you and I looked at on our spreadsheet, we've kind of got the truth and proof here of what was important to those buyers.
And essentially, of these statistics that are below, small numbers are better, big numbers are worse. Small numbers are what we want. And in fact, we want a threshold, a statistical threshold of 0.05. And what that means is when it's that number or less, statistically the system has derived that this is important to buyers; does that help?.
As these numbers become bigger than that, these characteristics of homes become weaker and weaker. And honestly, most statisticians throw out anything bigger than 0.05 because the system is saying it's too inconsistent—you shouldn't be using that as a key value. And it's very interesting because it blows a lot of stuff out of the water that agents do automatically.
The style of the home has some impact on buyer demand and value in this neighborhood. The multi level or split level, and the two level, have some impact on value. And I can tell you also that the ranch styles, we generally have to pull those out separately, because trying to compare those square footages is just not fair. But it's telling you that buyers have a preference of these two styles. However, they're both bigger than those numbers at 0.05. And so, it's kind of a weak connection.
Now, above grade finish area. Let me spread this out for you a little bit here. Above grade finished area, again it's one of the better scoring criteria variables, but it's still kind of weak, it’s weak. I mean, in other words this statistic is saying buyers' are happy to get the extra square footage, but they're probably not going to reject your home, for give or take a couple hundred square feet. Does that make sense? Have you been told that before? I bet you haven't.
Next, below grade finished area is essentially how much basement is finished. Again, it's well above that 0.05 criteria and statisticians would throw that out. You and I would probably look this look at this as a big gray area. If you have it, great! I think it would help in this case. Your own neighborhood may be very different. But in this neighborhood if you don't have it, I'm not going to be the one preaching to you boy if only you had a finished basement...or because you don't have a finished basement I'm taking value away from your home. No, no the buyers have proven that's not super vital to them.
The rest of these variables are just blown out of the water, like bedrooms. Remember when we looked at the spreadsheet we had some that were two bedrooms in the highest price range and some that were five bedrooms and the lowest price range. Well this is proving that statistically—this is the truth and the proof—that the bedrooms are not going to kill your value at all. If you have three bedrooms and your comparables have four, nobody should be taking value from your home.
Main level bathrooms and bedrooms, same thing. Okay, if they're there, on the main level bedrooms, it seems to have a little bit of a pull for the market. But a statistician would throw this out big time.
Unfinished area—now this is dead center and doesn't matter to buyers.
Year of construction—again, most of those homes are within 15 to 20 years of each other and doesn't matter to buyers.
What I'm saying is, when you only look at three homes like a typical realtor, they're making these deductions based on what they've been told to do. What we're looking at is what the marketplace, the last 100 buyers, said was important to them.
Now, here's what blew me away. And I'll be honest with you, I never expected this, and I've been at this statistical-algorithm-technology stuff for almost 20 years now.
QKeys are my own device. And what that stands for qualities-Q, that are key to value based on what the buyers demand and what they'll pay for. And I've created six groups.
And I know why this one did not make the cut of 0.05. Because there just was not enough information. And essentially, what the system looks for here is negative comments, you know, you could think of the most extreme has foundation problems. And right, that's going to be a big one. But it could say something like dated or outdated needs updating. And most brokers aren't going to admit to that even if that's true. And so, this one just didn't have enough data to make the cut.
Now, QKey five is the opposite of that. That's the condition of the home. Now what was interesting is we'll go through this too, and I'm just going to touch on these. But QKey five is things like you know, fresh carpet, updated, remodeled, new windows, new roof, new paint, you name it, whatever it might adding to the positive condition of the property. Really important to the buyers.
But I did not think that so many of these typical realtor valuation criteria would be kicked out, I really didn't, I really didn't. And so many of mine would—my proprietary analyses—would be so vital. And again, 0.05 or below is good. And so, when you see dead-on zeros, you don't get any better on that analysis. So, for these buyers in this neighborhood, those general conditions are really important.
QKey One are things like, if you will: park like yard, hardwood floors—qualities that connect with the buyers emotionally that you can see and feel, okay? Again, when your home has more of those, the buyers desire it more, and they pay more for it. And we're just giving you the truth and proof on that.
And so, what I've got here, and I don't want to drag this out forever, this is stuff that would only be important to you when we were talking about your exact neighborhood, and this is just a neighborhood—one of the 150—that we service and I don't want to go through all the details and make you crazy.
This one I do want to say I was a little bit shocked with. And this is how we're going to end this. QKey four is essentially what I look at for kitchens and bathrooms because kitchens and bathrooms should be really important. This one really fooled me in this neighborhood and again your neighborhood could be completely different. Please remember that.
But in this neighborhood strangely enough major remodels did not matter very much to these buyers. Now don't get confused. They wanted the Kitchens and Baths in good condition. Okay, well maintained, but for whatever reason, and this is why I can't allow my own biases into this—I have to look at the statistics in this location, this neighborhood—It did not matter to the typical buyer when looking at 100 buyers' actions, not three, whether they had a full blown, you know $50,000 kitchen remodel. And I was a little bit shocked! I didn't expect that and that's why I keep my own biases—my own expectations out of the analyses. I've been in this business for 34 years, but it was amazing to me. And again, this could be quite different in a different neighborhood.
This is based on the actions of the buyers of this one neighborhood. Every one of these analyses must be custom designed. And in this case, they want nice stuff. And they'll pay for a nice stuff. They don't seem to really want the full-blown crazy remodel, down to the studs and rebuild type thing, particularly on the Kitchens and Baths. They just want it nice. They're not going to pay extra for that. Have you ever been told that before? I bet you haven't.
We're going to end it there. I apologize this went so long. But I think it was important for you to see this stuff. And if you and I ever get to meet and we ever sit down together on this thing for your neighborhood, I promise you we will go into so much more detail. You will know more than any realtor you ever meet about your own neighborhood.