 Hey there, Chad Boninger here for High University Libraries. Today I had the opportunity to present two over a dozen classes of business students who are doing a project to basically do a business concept somewhere in the realm of the ice cream industry. What follows is the best of those three recordings of the different sessions. You'll see the whole session here where I talk about Simmons, talk about BizMiner, and talk about Simply Analytics. So hopefully this video gives you a rundown of the kinds of things you can do when looking at your local market and trying to understand how the industry is doing in the local market as well as understanding consumer demand and things like that in your local geographic area. My apologies for some of the bad recording quality that you'll see. It just seems that Microsoft Teams didn't really record my camera in a good resolution. But once you get past that, the overall screen recordings are of pretty good quality. So it's a long video. You can skip ahead. I'll have timestamps for the various sections of the video below. Take care and best of luck with your research. Once again, I'm Chad Boninger. I am the head of user services and the business librarian for high university libraries. And y'all are doing segue into project two. Project two is actually one of my favorite parts of the cluster experience because this is where y'all get to be a little bit more creative. In your ideas, in your research, that sort of thing. So with that creativity comes some challenges. And what I mean by that is you're gonna be past the point now where you can just go in and type in ice cream industry in Ibisworld or Mintel or Statista or whatever and get some stuff. So you've already done that. So you're gonna use that information that you found to kind of build upon that as you head into project two as you create your kind of your own business concept, okay? Now what we're gonna do today is actually do a deeper dive into some data. So both consumer level data and industry level data, especially on the local level, okay? So to give you a snapshot of what we're gonna be doing today, let me share my screen with you here. And so one thing we're gonna be doing, we're looking at database called Simmons and we're gonna be looking at some granular level information to better understand particular consumers of ice cream and how they might overlay with other interest, okay? So I'll get to this in just a second when we talk about Simmons, okay? We're also gonna be looking at a database called BizMiner and this report here that I've generated is basically industry sales averages for ice cream parlors in the Franklin County, Ohio area, okay? So if you're gonna build an ice cream shop or do any sort of ice cream related stuff, BizMiner can kind of help you better understand how the industry is performing at a local level. Previously you've been looking at national level trends with IBIS World and statistics and things like that, but BizMiner allows you to get into a more granular local level, okay? Finally, we'll be looking today at Simply Analytics. So we're looking right now at a map in Simply Analytics that shows the percentage of people around Nashville, Tennessee by zip code who eat Ben and Jerry's ice cream the most, okay? So we can look at this kind of data to kind of understand information about our geographic area and our consumer and potential consumer demand of a particular product or a similar product to the type of product that we're gonna be making or selling or the service we're gonna be offering for project too, okay? So let me get started here. I'm gonna go back to my ice cream industry guide, okay? So this is the guide here and we're gonna go start first in the companies and competitors, excuse me, the consumers and customer section and here's where we can find Simmons Insights, okay? So I'm gonna open Simmons here. Let me close my previous rendition of Simmons, okay? And let me close my previous rendition of Simply Analytics so I don't confuse myself there. All right, so previously in project one we went to Essentials and Quick Reports and generated a demographic profile. That gives you the kind of just the quick kind of charts kind of stuff. So to remind you of that again, we can go to Quick Reports here and we've got a demographic profile here for example and we can go in under our dictionary, right? And we can scroll down to our food snack dessert example for example here and then here we find ice cream and here we find brands people eat the most for example and we can find Ben and Jerry's here, right? And then we can add that to our target and I'm flying through this because this is kind of review. We're gonna get to some more specific stuff here in just a second and then we run our analysis here, okay? Okay, so this gives us our demographic profile of our Ben and Jerry's consumer, all right? Now, if that wasn't a review for you, if that was way too fast, what I just did is actually in this video right here, okay? So that's a good way to kind of, if you're trying to better understand if you're gonna be offering kind of a more expensive type ice cream with boutique flavors and that kind of stuff, you could use Ben and Jerry's for example as a proxy for your potential product, okay? But everything I did there is in this video here, okay? As well as in these directions here, okay? All right, so that's a review of how to find these kind of demographic profiles. Now, these are great, but they're kind of limited, all right? So I'm gonna go back to the homepage here and the homepage lands on this cross tab. I don't know what cross tab 2.0 is, I haven't used that, so I'm just using cross tab here, okay? Now, give me a second, let me bring my notes up here, all right? So let's say you've got this ice cream product store idea, and you've gone out, and I'm just kind of making this up as I go here, okay? So you've gone out and you've got two potential store locations, okay? So one is next to a yoga studio, okay? And one is next to a NFL fan shop that sells jerseys and sports memorabilia and that kind of stuff. And you're trying to figure out like which location might potentially bring me in as a boutique, Ben and Jerry's kind of like ice cream shop. So you're like, well, so I got this NFL shop that looks pretty cool here and I've got this yoga studio, let me try to figure out with data which might be the best location for me to choose for my potential location for my shop, okay? So what I'm gonna do here, we're gonna use Simmons over here to create a cross tabulation report using the Simmons data to use data to determine which is better, which location might be better, okay? So, and this is kind of that creative kind of thought process that you can use with data sets like this as you move into project two. So what I'm gonna do is I'm gonna ignore the search box here, I'm gonna click on this dictionary here thing, okay? So what this is gonna do, it's gonna give me this option to create columns and rows over here on the right hand side. All right, so the first thing I wanna do is put in my columns, I wanna put in my ice cream brand, okay? So I'm gonna go down and find my ice cream brand here, all right, so we can go under our food snack dessert again and here's our ice cream and ice cream sherbet types people or excuse me, brands people eat the most and once again, my product is gonna be similar to Ben & Jerry's, it's gonna be a little bit more expensive, it's gonna be different kind of funky flavors and that kind of stuff. So I'm gonna drag Ben & Jerry's over here to my columns, okay? So what this says is of the whole sample size of the survey, which is about 25,000 people, 2,110 people said that they enjoy eating Ben & Jerry's the most, that's what the MO is right here, okay? Now, I'm gonna show you how this search thing works up here rather than browse, we're gonna use this search, but you can do both, okay? So I wanna find information about people who do yoga. So I'm gonna search for yoga and one thing I wanna do is right now it's kind of hard to tell but it's selected on answers only, I'm gonna go over here and choose the all option, all right, and then hit the little magnifying glass thing, okay, so here we see yoga, here we see there's an entertainment leisure category, there is a sports and fitness area, okay? Now we have information for people who just did yoga in the past year, okay? So people who might have tried it and did it once or did it once or twice or whatever. Here we have people who are the hardcore yoga people, they do yoga every chance they get, they've got their mat in the back of their car, they're ready to go at a moment's notice, that kind of stuff. So let's start with dragging the every chance I get people over here in my rows, all right? Oops, excuse, oops, sorry about that, let me clear that, that didn't work out well. Let me go, I dragged too many things, I meant to drag just the yoga right here, there we go. Got ahead of myself. All right, you'll see that the sample size here is 867, so we might wanna drag the occasionally over as well, okay? Now the occasionally we'll see if we get a few more people who have done yoga, so the more kind of niche something is your sample size may be smaller, okay? All right, so now, so we've got our yoga folks in here. Now let's go up here and search for, I'm just gonna search for NFL, all right? But once again, clicking all, all right? And we will search for that, okay? Now NFL is gonna bring up a bunch of stuff. You can kind of see by category where things are at, if we look under entertainment leisure, sports interest here, sports interest last 12 months, here's the national football league. And here we have people who are very interested, somewhat interested or a little bit interested, okay? So I'm looking for that kind of, let's look at the very interested folks, right? And then let's look at the somewhat interested folks, okay? So these are the type of people who are probably more inclined to visit the NFL shop to go buy a jersey or buy an autograph poster or whatever, okay? So once I'm satisfied with that, I've got some, I've got me on my main kind of thing I'm up, got up here and the things I wanna compare down here in my rows, I can go up here to the right and click on my arrow here, which is gonna run the cross tab for me, okay? Now what I'm gonna hope is I get some data that is somewhat meaningful, yeah. So if we look at this, let me kind of try to blow this up a little bit for you. And the first column over here is the total population, okay? So this basically says, you know, the total of the total population, you know, if we're looking at the top here of the total population going down the vertical, 23.9% of the total population is very interested in NFL football versus 14% of the total population is somewhat interested in NFL football, okay? So if we scroll over, here's where we have our ice cream. So we have our Ben and Jerry's, okay? And one thing I wanna notice right away is I see over here in the index, we've got an index of 173. So when you're looking at indices, all right, an index, the average of the total survey is usually 100. That's the, everybody who took the survey, the index will be 100. So here we could see this line here. We've got, these people are like 73% more likely to like a particular product, okay? So if we look over here on the left-hand side, we're gonna follow this left to right, okay? We can see of those people who do yoga every chance I get, and we're gonna use this horizontal one because we're going left to right, of the people who said, I like to do yoga every chance I get, 17% of them like Ben and Jerry's ice cream the most, okay? Okay, now if we look at that comparatively speaking to NFL football fans, of those people who are very interested in NFL football, 9.4% of them like Ben and Jerry's ice cream the most, okay? And that's why the index here is actually below 100, okay? So this is not the target consumer we're after with their ice cream shop, right? However, we can see both people who do yoga occasionally and people who do yoga every chance they get, these folks are gonna be probably more inclined to potentially visit our upscale, more expensive kind of boutique ice cream store than the NFL shop, all right? Now, it's TBD whether they're actually gonna do yoga, then go do ice cream or do ice cream, then do yoga. But anyway, you can see how the data points align to show that that's probably a more prominent indicator of my success near the yoga store as opposed to my success near the NFL shop, okay? Now, I'm gonna go back to the dictionary here and show you another way that you can look at this and let's just say for example, you also want to look at, you wanna target something like college educated females who are NFL fans, okay? It's a silly example, but this is, I'm just gonna show you how you can build a custom variable, okay? So what we can do here is we can start off up here and I'm gonna scroll down and look at our lifestyle demographics. And we can see here is demographics here and we have gender and we have females. So what I'm gonna do is I'm gonna create a custom variable down here at the very bottom. So I'm gonna drag female down here, all right? You'll notice everything's down here green, everything is good to go. I'm gonna do age now. Actually, let me do education highest level completed, all right, rather than age. And let's do bachelor's degree or higher. This will be college educated or higher females, okay? So I'm gonna drag that down here, okay? Now you can see it turn red on us. I'm gonna fix that here in a second, okay? And then we can go up and say, let's look at our entertainment leisure and let's do our sports interests and sports interests last 12 months. And you can see there's all these kind of things we can look at. Here's our NFL fans. And I'm just gonna do a little bit interested, okay? So let's do a little bit interested and we'll do that. Okay, now you see it's not happy with us, okay? So it's red down here. Now what we wanna do is we need to put in a qualifier to combine these three variables. Okay, so all we're gonna do is click in here and we can click on and. You can see it's red again and we can click on and here. And now everything's green, it's happy, okay? Now what we can do up here now is we can call this college ed, email, NFL fans. Now this is not all gonna make it on the little line there but we can see that to what we're looking at, all right? So now we're gonna actually put this on our rows here and we're gonna move this to our rows. All right, so here we have our list down here. Now you notice my sample size went way down because I did all those combination of variables. So we'll see if I actually get a good data pull here but just kind of give you an idea as far as what we're looking at here. All right, so here we see if we scroll over, this is interesting, look at here, that's pretty cool. I didn't intend that for that to happen but look, our college-educated female NFL fans are almost equivalent to our yoga folks in their likelihood of liking Ben and Jerry's ice cream the most, okay? So potentially I've dug a little bit deeper here. Maybe my initial understanding of the data because it did not dig deep enough would mean that maybe my NFL shop might be okay, depending on what kind of clientele go into my NFL shop that potentially might be next to my yoga shop, okay? So anyway, you can use this kind of data to kind of really tell your story on what kind of product you're doing, what kind of location you're doing, that kind of stuff. So the sky's the limit with Simmons when you're doing that kind of data for this purpose. You just have to be a little bit creative with it in trying to figure out what kind of data might be useful to you, okay? All right, so I'm gonna go and look next at we're gonna go under local market info, okay? So we didn't actually explore this area much for project one. The first resource we'll look at here is BizMiner. And I have a video down here that kind of shows you one aspect of BizMiner. And I'll show you both different ways that you can use BizMiner for this particular project. And BizMiner can be occasionally sluggish to load. So we'll hope that actually, hold on, I've got two instances open. That's probably why it's doing that. Let me close that out. Try again here. Okay, so there's three sections in here in BizMiner. I tend to use these two the most, the industry financial profile section and the industry market profile, okay? So the industry financial profile tends to be more financial oriented. So if you wanna know like what, how much do ice cream shops in Columbus, Ohio usually spend on wages or rent or what's their overall value or their inventories or that kind of stuff. So we can use this section here for that. The industry market profile will give you actual more or less kind of sales averages and that kind of stuff across the industry, how many average employees, the industry employees, that sort of thing, okay? So we'll look at both here for our purposes. So the industry financial profile here, the first thing you have to do is select an industry. And the way this works, you can either click and deep dive or you can do a search. So I'll just do a search for ice cream and click the hourglass here. And for my example, I'm just gonna use ice cream parlors. And once we do that, it adds the ice cream industry there. We're not ready to go yet. Like we can't click access now over here yet because we have to select a market area. So let's select a market area here and let's look at, let's look at Ohio. And you can see once we select Ohio, it will actually scroll down and give us other options to look at. I'm just gonna do the Columbus, Ohio area. And then we can do a sales class. So let's look at small businesses here. We'll just look at the, if you look at industry wide, it's gonna be every single industry entity. The small business would kind of give you kind of your comparing your company potentially to similar sized companies. So you're not comparing it to a huge outfit. So we're just gonna do the small less than $5 million. And we can go over here and click on access now. And we will click access now here. And this takes a second to load. You can see up here on the right-hand side, none of this is clickable over here on the left until everything up here is loaded. Okay, so this is one of those times when you're doing a presentation like this and you're like, oh, there it goes, data loaded. Okay, it's cool. I didn't have to make up any funny jokes or anything. So anyway, what you have over here, if you have the, so here's information about the, how many industries there were in the industry or how many industries or firms they analyze over the past five years or so, right? If we look at the financials here on the left-hand side, we've got industry financials. You can look at this by a balance sheet, et cetera. So here's like how much they pay for salaries and wages, this is the percentage. If we want to look at dollars, salary and wages, averages across the board, how much they pay for rent, things like that, how much they pay for what are the kind of expenses, what are their after-tax net profits, things like that per year, all that kind of stuff. So interesting way to kind of look at what's going on there. So, and what's nice about BizMiner is there's explanations over here. If you just kind of read thoroughly through here, as you're looking at the data, there'll be explanations on the right-hand side or throughout or little question marks that you can click on that will give you additional data for what you're looking at there. So if you're not a finance person yet, this will give you information about that kind of stuff. So anyway, other things like profitability ratios for the area, small businesses, ice cream parlors in the Columbus, Ohio area. So we're looking at this again on the local level. Okay. If we go back to our BizMiner homepage here, just to kind of give you an example of what else you can look at here are these industry market profiles. And once again, we can choose, I'll just choose ice cream again as my example. We'll search here and look for ice cream parlors. All right, once again, I can't click anything now until I make a choice of what kind of market area I want to look at. Now you'll notice here there's a radius option and what a radius option allows you to do. Let's say I have chosen my street address right next to my yoga shop for my ice cream parlor. And so if I had an actual address, and you can do this, if you have an actual street address, you can put that in the radius and it'll pull up just companies or just an analysis of that radius, five mile, 10 mile, whatever radius of the area, okay? I'm gonna do a radius search in our next database just to kind of show you how what a radius search might look like, okay? So I'm gonna select our market area here and just to kind of show you here, you can get a little bit more granular in this section. So if I just click on Ohio here, oops, let's try that again, Ohio. I clicked on Ohio and I didn't wait long enough. You can see what's happening. It's actually loading here on the backside. And what it'll do is it'll load zip codes, it'll load counties, it'll load cities. So we can find, you know, we can go in and click on individual areas once it loads for us. And hopefully it'll be a little quicker than this. There we go, there we go, that's good. That's what it's supposed to do, ha, finally. So here we see the metro areas we can look at counties as well as zip codes. You'll notice with the zip codes, you can select multiple zip codes. So if you're looking at multiple zip codes across a county or a city area, you can just kind of click, click, click, click, click and you're good to go. Apparently I clicked too soon and now freaked it out. The other thing you could do is, in addition to clicking on those, is you can go up here and search for a market. And let me search for, actually search for Franklin. And I actually searched for Franklin County before that did not work, but you see under counties here if we look for Franklin and eventually scroll down to Franklin, Ohio there, okay. All right, so now we find 67 operations that are in, BizMiner that are analyzed for ice cream parlors in Franklin, Ohio County metro area. So we can click access now here and once more access now, one more time. Now these reports take a little bit longer to load than the industry financial profile reports. Up again here in the right-hand side, you can see that they're loading. They just changed the interface of this pretty recently and when I first tried it, I wasn't very patient. I kept clicking, clicking, clicking over here on the left-hand side and nothing would happen because I wasn't waiting long enough for the thing to load. So we'll give it a minute here for this to load here. All right. While we're waiting on that, the industry financial profile, the first thing I showed with you with BizMiner, that is demonstrated right here in this video here about BizMiner, okay. So it shows you how to find, you know, profit margin and other industry financial stuff for a local market in the ice cream industry, okay. All right, so our data is finally loaded over here. We can download the data if we want to. I'm just gonna kind of go through some of the areas on the left-hand side to highlight what you might find in a full downloaded report. The first thing you'll see, there's a competitors tab here and so here we see if you're from Columbus or have been to Columbus, you probably recognize some of these companies here and so what they'll do here is, you know, they're showing you some of the key competitors in the area and they're also giving you information about them. They're giving you a sales bracket area, okay. So here we have a sales bracket right here. They're not giving you actual sales data because a lot of these are gonna be privately held companies, okay, so they're giving you a sales kind of band as far as what the approximate sales bracket is for these companies, okay. If you wanted better, more granular data for these companies, once again, you can go back over to our local market info section and then search for the individual companies here in Mergent Intellect. I'm not gonna do that today because we did that during our last session together, but you can search for the individual companies there and get more specific, albeit still estimated sales of those companies, okay. So, and then we have, we've got some tips here as well that kind of suggest how you can filter by industry, by location. So you can do a similar search for ice cream shops in the Columbus metro area and get a list that way with some sales estimates, okay. And this video here shows you how to do that, albeit it's an example using the coffee industry, but I give you the SIC code that you'll wanna use to replicate the search to align it with the ice cream industry, okay. All right, so here we have industry locations and that kind of stuff. So you can see they look at a number of different companies. We look at, we're gonna left-hand side, look at the market. So here we see how much market volume is done by small business versus startup companies. That's pretty interesting and would be interesting to look at from your perspective as you're looking to start a new company in this area. You can see there's also a share area so you can see like what percentage of the industry market share comes from startup companies, right. Here we have annual sales. Again, so this gives you average sales per site, okay. So if you're a startup company in 2021, according to the companies they analyzed, their average sales were in neighborhood of $431,000 for a startup company, okay. So, and again, you have all this explanation of what all this kind of stuff means and things like that. Sensation, I'm just gonna kind of skip around a little bit. Sensation is how many companies actually went out of business. So these are kind of failure rates, right. So this kind of gives you an idea as far as how volatile an industry might be as you're looking at opening in this particular area, okay. So it kind of gives you an idea as far as what, how viable a potential company might be or how viable companies have been in the past, okay. The demographics section here, this is not demographics of ice cream consumers. That's where we do that in Simmons or in Mintel or whatever, but this kind of gives you just a general demographics of the local population, which is still pretty useful because if you learned about particular demographics in Mintel, looking at ice cream consumers, you can still use this data, okay. All right, so that is BizMiner. Lots of cool things you can do with it. And I just showed you two samples and using the same industry, but you can kind of play around and find similar things for like restaurants or you can even find yoga studios or probably fan apparel shops, things like that if you were interested in doing that kind of stuff, okay. All right, the next to look at is your local market info as if we scroll down a little bit here. The last one on the list here is Simply Analytics. All right, so Simply Analytics, you don't have to do this, but I would encourage you to create an account with them. Just use your Ohio email address and whatever password you want to use. The reason I encourage you to do that is if you create an account with them, what it'll do is actually save what you were working on last time, okay. If you recall at the beginning of the session, I showed you a map, I closed out the browser tab and you'll see I actually still have this map, okay. So it's a cool feature that will remember what you're working on. And I appreciate that we have that option to create an account with them because despite the name Simply Analytics, sometimes it's not quite so simply to use. It can be a little bit of a challenge. And again, this is one of those databases that requires you to be a little creative with using it. And so you may have to spend some time in here with using this, okay. Typically, our university has 10 simultaneous users for the whole university, okay. And that costs a pretty penny, but our vendor has expanded access. So we have 50 simultaneous users for pretty much a duration of project two. So the vendors that do, for Simply Analytics are great to work with and highly appreciate them giving us additional seats so that we're not kicked out and we're trying to log into this thing, okay. Now, the way this thing works, you'll start off with like a new project, okay. So I'm gonna start off and let's say I really wanna open my ice cream shop either in Memphis, Tennessee, or in Chattanooga, Tennessee. All right, so I wanna open my ice cream shop in one of these two places. And I'm also just gonna look at the state of Tennessee as well just so I can compare those cities to the state averages, right. And then I can also even look at, this is the zip code I grew up in in Chattanooga, Tennessee. I'm gonna just go, I can look at this by zip code level. I can also look at this by county level. So there's Hamilton County, Tennessee, that's the county that Chattanooga's in, okay. So I've selected some locations, all right. You can do one location if you're just looking for a particular city or zip code or you can do as many as you want, okay. So I'm gonna do that and click Next. And then it starts you out with these seed variables, okay. So what they're doing here is basically they don't wanna start you out empty handed. And so I'm gonna do just total population and I guess because I wanna do kind of a boutique ice cream shop, I wanna do percentage of people who household income $100,000 or more. And we'll just, we'll keep median household income there as well, okay. So we can create our project here. And the first thing it's gonna do is load the map. I actually prefer to, because it just loads our first city that we chose, which was Memphis, Tennessee. I'm actually gonna do a comparison table first, okay. So here we're looking at comparing Chattanooga to Memphis to Hamilton County and all these are ordered. So we can say let's move, you know, we can move these around here, let's move. So now we're going from small to bigger to biggest. And then we're looking at Memphis over here as well, okay. So you can kind of move all this stuff around if you want. Now, I've already done locations and then it throws me in this data area, right. So I can go up here, I can search. I can search for say, let's search for ice cream and see what we get here. So here we have consumer expenditures. That's pretty cool. Ice cream related products household average. Let's do that, all right. And then you'll notice here, here is some data that looks strikingly similar to what we just saw over when we're looking at Ben and Jerry's ice cream in the Simmons database with the yoga people and the NFL people. That's cause it's the same data, all right. It's just, we're getting the Simmons data but we're gonna be able to look at that data on a local level. Okay, so now right now we're looking at people who eat a particular brand of frozen novelty treats. If we scroll down some more, here's people who eat frozen novelty treats brands. This is a really long list. You can filter this. So if I wanna filter by people who eat Ben and Jerry's, I'll just type in Ben there. And so here we see people who also eat Ben and Jerry's or people who eat Ben and Jerry's ice cream the most. Okay, so I'm just gonna click on percent and number. And while I'm in here, I wanna show you a little trade secret. If you click on this open data folder or any links in here, this will actually go and open the hierarchical list that you've seen me use in Simmons, okay? So here it opens the ice cream and sherbet folder and right now we're in the brands, okay? So we could also go in here and look at, again, if we're doing the same sort of stuff, if we look at, let's see, let's go to our, let's close the food here, for example. If we look at our entertainment leisure, for example, I'm missing it for right now. There we go, entertainment leisure. And we here we have our sports and fitness, participated every chance I get. And then if we scroll down again, all the way at the bottom, we should find, actually let me just filter here, that's a long list. Here's our yoga, right? So we've already seen this in our previous database. Now we can get that on the local level if we want to, okay? So once we're looking at this kind of data, we see, here we see, I've added these data sets and we're looking at these data variables on the left-hand side comparing them to our local market, all right? Okay, so now the difference here in this, the way this is presented is that, we're looking at what percentage of people in Chattanooga, Tennessee eat Ben and Jerry's ice cream the most, okay? So here we see it's 7.14% in this zip code 37421 versus evidently 9.45% in Memphis. So maybe Memphis might be a better opportunity for me. And neither of which are higher than the national average, okay? So I like to keep this USA national average over here so we can kind of see like, is our market kind of really a hot area for this consumer item, right? So here we see a lot of people in the 37421 area do yoga every chance they get. You know, they're pretty close to the national average of 3.84%, right? So you can do all this kind of stuff to align here, all right? Now, what it won't tell you is we're not able to say, all right, how many of these people in Chattanooga, Tennessee who do yoga also eat Ben and Jerry's ice cream or also NFL fans, okay? We can't get that cross tabulation data like we couldn't Simmons, okay? We can only just get the one variable for the one location, all right? So you can kind of do this. You can do this to your heart's content. You can then go over here and map the stuff, right? So if we're looking at mapping a map, now right now we're looking at Memphis. If we're looking at the state of Tennessee, for example, and right now we're looking at total population. If we wanted to change this, let's look at the percentage of people who eat Ben and Jerry's ice cream the most, all right? Now, this is probably not a big surprise, but you can see that the surrounding areas, the suburbs of Nashville, Tennessee, where they're a little bit more affluent, tend to dine on Ben and Jerry's more than other areas, so Memphis, a close second here, but the area around Nashville is probably if I was gonna open a boutique place, that might be where I wanna go, okay? So, and now we're looking at this by counties here as well, okay? Now you can also go in and let's say I did wanna open a shop and around like my neck of the woods where I grew up, okay? So I'm gonna do a location and I'm gonna do a custom location and I'm gonna do a radius location, okay? So my location, I'm gonna search for my old street address. All right, so you can't spell my old town anymore, all right? So we'll do that, nothing comes up, we'll just do an address search here and you'll see it doesn't exactly find the address. What it finds is it finds the county that my street is in or the city or the zip code or the census track or the block group. The block group is essentially my old neighborhood, okay? So that's as granular as they go. So I wanna click on the block group here and let's say, so let's say I'm gonna buy that old house and put an ice cream shop inside the house. Probably a dumb idea but you'll get the idea that this is just how we're building this location here, okay? So now I'm gonna look for, maybe people are gonna drive within five miles to my location and we'll just call this five miles from Chad's ice cream, all right? And we'll save that. And so now here is our five mile radius surrounding the area, okay? And you can kind of see I'm probably choosing a pretty poor location here because this is our percentage of people who like Ben and Jerry's the most and we're looking at by census tracks. Let's look at by block groups here to see if that changes anything. A little bit smaller, more granular level to see if there's, so maybe not too bad. I've got, this is where my block group is at and so I can see that the nearby people are maybe inclined to dine on my ice cream here. So what's cool about this thing is we've got this map here. We can actually export this map as a file but before we do that we can go in and customize this thing over here. So let's go over here and let's edit this map. And the first thing I wanna show you here is you can kind of mess with the way these category ranges are broken down. So I'm just gonna click on like quantiles local here. Oh, that's prettier, I like that. That map is nice, okay? So it's got a little bit more color in it. All it did was it changed the category ranges here. Made a little bit more interesting to look at, all right? You can kind of mess around with here and just choose whatever to see how the map is reflected in the color scheme based on how the data aligns, okay? And then we can change the color scheme here and I don't know, I think probably this, this is probably a nice neutral area to start with for ice cream. And then maybe if I want to I can go over here and change the color. So there's like, maybe I don't want this blue. Maybe I'm kind of wanted a more of a brown kind of chocolate peanut butter flavor kind of deal. So you can go in and kind of change the colors here. You can also go in and actually enter in your own HEX code if you want to as well. So if you're trying to align it specifically to a color you can go in and kind of enter in a particular color code, that kind of stuff. So a good way to kind of customize your map. I would, what I would do here is if you build a map like this, align it to the same colors or whatever your logo is for your brand for your new company, right? So it's a cool way you can kind of do that, okay? So once you're satisfied with that you can actually go up here and export this map. And if this is kind of allows you kind of go in and build this thing. So I'm gonna move this over here a little bit and you can actually continue to the layout and I can move this guy down here in the corner. So it's not in the way. I can go up here and add a text label and call it chads, ice cream, customers, right? And drag this up here and of course I can change the color of this and all that kind of good stuff as well. So and then once you do that you can export it to your PowerPoint slide and or as a PDF or JPEG or whatever and you're good to go, okay? So pretty cool stuff that you can do there. Also I'm in here, there's this quick report option. This is an area where if you're just looking for basic demographics of our locations you can see that all of our areas are right here. You'll notice one's missing. My radius location is missing. If you're looking at any sort of data set in here and you find something is missing you can go up here and view your actions and edit your view and you'll see I can now select five miles from Chad. So if I don't want USA anymore, I don't want Tennessee, I just want, I don't want Helmand County, I just want Chattanooga and five miles from Chad. I can do that, click done and I can once again drag these around so we're going from small to bigger to biggest and look in the data that way, all right? And while you're in here, if you wanted to you can actually click on these variables and when you do that they'll go over here and appear in your area, okay? Again, if they don't show up you can go to view actions, edit view and here's our age we just chose from our previous one. All right, click that, click done and we just added that variable there, okay? So lots of ways you can use this thing and again this data set here you can export this as an Excel file as well so you can save it for later manipulate it later, that sort of thing, all right? So that is simply analytics. Again, not quite so simply to use I do want to show you I don't have a specific video for the ice cream industry but if you're looking at simply analytics and you click on my tips and tricks guide here this page here will show you things like how to build geographic comparisons, right? So this shows you how to build the tables that it just kind of just showed you how to do, right? Or how to map your data, right? So how to create a custom map and that sort of thing. So you can use this to kind of follow along with how to do that for the ice cream industry, okay? All right, once again, anywhere in on my site you can click on get help from Chad and that will show you my various help options typically email teams or schedule appointments probably your best option. If you do email or teams and I don't have a ready answer or if I'm likely to be like, hey, you know it's probably easier to kind of talk through this let's make an appointment. I'll probably encourage you to do that. I do want to tell you again that, you know my appointments book 24 hours in advance, right? So if you were booking right now, the soonest you'll be able to book will be like 9 a.m. tomorrow, okay? So just think about that as you plan how you're doing your research, okay? So definitely want to help you out but I want to make sure you all are aware of how planning works and that sort of thing. So okay, I will pause there and just pause for any sort of questions or anything like that or I can bid you audios.