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- November 02, 2021
Next Level Entrepreneurs Secret Weapon - Analyzing The RIGHT Data
Episode Stats
Length
8 minutes
Words per Minute
213.43826
Word Count
1,763
Sentence Count
124
Misogynist Sentences
1
Summary
Summaries are generated with
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Transcript
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Misogyny classification is done with
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So three people can go to the same exact restaurant and look at the whole thing from a complete
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different lens. One can go and say, I just want good food and good service. Another person can
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go and say, I wonder if this waitress is going to do a good job because they used to be a waitress
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and they're watching all their mannerisms. Another person can go in and say, look at the way I
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walked in, the menu, the chef, the plates, how they're lined up because they own a restaurant.
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Today, I'm going to give you a lens to look at data in a way maybe you've never looked at before.
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Okay, so stick around to Leverian. I'm going to give you a PDF on how to go use this with
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your employees, your team, your staff, so you can get better data and get better results
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to drive your company to newer heights. Let's get right into it. There's four different ways
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to analyze data. The first kind is the descriptive analytics, then it's diagnostic analytics,
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then it's predictive analytics, then it's prescriptive analytics. The first one, descriptive
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analytics, is basic. You're researching and summarizing historical data in order to identify
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patterns. How many sales did we do in the month of January compared to February compared to March?
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It's very basic. It's very descriptive. Number two is diagnostic, which is understanding why
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behind what happened. Why did we have a bad March versus last year? What happened? What were the events?
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What happened? Did COVID change it? Did new laws come out? Did we lose a customer? Did we gain a
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customer? What happened there? So it's the why. Number three, predictive analytics is studying those
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to predict what's about to happen next. Well, the way we did last October and the way we're trending
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this Q3 versus last year, Q3, this October, we're probably going to end up only doing $2 million.
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We're only going to end up doing $3 million, or we're poised to have the biggest month ever because
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we have this. But if you look at the data and you see patterns that you're not happy about your numbers
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and you look at the predictive analytics saying, oh my gosh, if we go the way we're going,
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we're going to have a bad October, that's when you come up with prescriptive analytics to say,
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what changes do we need to make in order to change results? You would be amazed how few salespeople,
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sales leaders, executives, and entrepreneurs actually look at data this way. I'm telling you here that
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there is a level you will hit if you don't look at data the right way. So now let's take a look at the
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next side, which has different forms of charts to look at numbers. I remember the moment Tom came to
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track my credit score back in the days. In 2003, I started tracking my credit score. Every month,
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on the 18th, I would go to truecredit.com. My credit score was 484, 495, and 499. I raised that
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to an 820, but I tracked everything. But that was a very basic way of doing Excel. We're going to look
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at it in a completely different way. So number one, from line chart all the way to the highest,
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which is technical. So what is a line chart? Analyzing numbers over time. You're looking for trends,
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and it's one-dimensional. Pretty much the chart you're looking at on the screen,
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that's what it's going to look like. Column chart, you're comparing 2021 to 2020. It's a vertical
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chart. You're comparing May of 2020 versus May of 2021. Q1 of 2020 versus Q1 of 2021. Basic stuff so
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far. You've probably seen both. Next one is a bar chart. So bar chart and column chart are pretty much
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the same thing. The only difference is column chart is vertical, bar charts are horizontal,
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and maybe you can add a little bit more to a column chart with different categories. Like
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maybe it's one or two or three categories. You can add age. You can add different things to it.
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Now we go to pie chart. Pie chart, you look at exactly what it sounds like. It's a pie chart. So
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you sold a million dollars of real estate. Okay. What percentage was it homes between zero to 420?
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What percentage was from 420 to 720? What percentage was 720 to a million, million to 2 million,
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and up, right? So that's the pie chart. Pie chart can look at a lot of different things.
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You ate food today. What did you eat? How much carbs? How much protein? Everything with that is
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a basic pie chart. You've probably seen that before. Next is an area chart, which is a line chart at the
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bottom plus a bar chart combined. So it looks something like this where the coloring tells you
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how you did, what the sales was. So slightly more technical because it's telling you now multi-dimensions
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of data combined together. Then you have pivot tables, which pivot tables are, they seem simple,
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but a pivot table with somebody that knows how to use Excel spreadsheets, they have formulas behind
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them. It could have a, you know, if you punch in a number in there, the formula is already calculating
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it to say, well, if this is what you did based on a formula that we use and the commission that we pay
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out, we're going to make $780,000. And you can kind of play with it to know if we did this much numbers,
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here's how much money the company would make. Okay. So that's the pivot chart. And then you have
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scatter chart, which you've probably seen the scatter chart with the dots on it, what that
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looks like. That's comparing two numeric values. It could be cost and quality. And there's a lot of
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things that you can track with a scatter chart. Then we have area map, which some call it scatter
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map. This is kind of like how, you know, we were trying to find out COVID, what state has the most
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people with COVID cases. And then it would show it to you. Region. If I want to know what country
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has the most COVID cases, you would typically see that on a scatter map. If you want to find out
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what the zip code has the most, six figure earners. If you want to find out where crime is the highest,
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you know, they would use a scatter map. Very effective. And last but not least, it's a little
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bit more technical, but it's a tree map chart. It's broken into subcategories. You know, maybe you want
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to categorize your real estate loans that you did, what different loans you sold, you know, what
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different products you sold. You may be a financial company. You do loans, you do real estate and you
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do escrow and you do insurance. So maybe loans is going to be read and within the loans, it's going
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to sell, you know, you did an interest only loan and then you did a 30 year fixed loan and you did
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a 15 year loan. So it'll show you which one of that is the most. Then real estate sales unit, it can
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categorize it as well. Escrow can categorize it. Insurance, it can categorize it all on one sheet, right?
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So I can go a little bit more detail than data. I don't want to do that with you. I want to keep it
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simple, but this is what I want to do to you while you're looking at this. For me, I'm growing my
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business. I'm a sales guy. Salesperson, you look at basic data. It's not complicated data. Then you
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go become a sales leader and you try to drive your guys through just, you know, motivating them. You
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can do more. You can do better. Try this script, try this overcoming objection, but then you have to
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go look at their trends. And I remembered the things that changed because I came up with something
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called DMA, you know, daily monitoring activity where everybody had a specific data of how many
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calls they made, how many appointments they ran. And then we broke it down to how many they closed
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based on their closing ratio to see how hard they were working. Accountability went higher.
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Effectiveness went higher. Everybody made more money. Then you go into becoming a, you know, a CEO,
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a founder. You start a company and then you get to a million dollar level, $5 million level,
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$10 million level, $20 million level. Almost each level you go to, you plateau. If you don't unpack,
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based on the right kind of data, you're not going to know why your company is slowing down.
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You're not going to know the root cause. You got to get deeper. It's like solving an issue and saying,
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why do we have such a bad customer service? Well, it's because we don't say, how may I help you?
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We say, how can I help you? Well, because I don't know. We need to use a better script. No,
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because it takes 48 seconds before somebody picks up the call. You got to get that to six seconds.
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But because you're not tracking the data, you're not going to know that. You say you're going to follow up
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within 24 hours, but 20% of the time you follow up, 80% of the time you don't. And the only reason
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you don't have that data is because you don't track that data. So you go a layer deeper and deeper
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and deeper and deeper to find that exactly the root cause of what's taking place. And if you can't
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address it, your business grows. So having said that, if you got value from today's content,
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give it a thumbs up, subscribe to the channel. If you want today's PDF, text the word chart
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to 310-340-1132. Text the word chart, C-H-A-R-T, not plural, singular, to 310-340-1132. And if you're
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international, click on the link below to subscribe to the newsletter, and we'll send
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this PDF to you as well. And if you've never watched a video, How to Strategize as an Entrepreneur,
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click over here to watch the video, How to Strategize as an Entrepreneur, because it has
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a lot to do with what I just talked about today. Take care, everybody. Bye-bye.
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Bye-bye.
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