Valuetainment - 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

Harmful content

Misogyny

1

sentences flagged


Summary

Summaries generated with gmurro/bart-large-finetuned-filtered-spotify-podcast-summ .

In this episode, we re going to look at data in a completely different way than you ve ever looked at it before. You ll learn about the 4 different ways to analyze data and how to use them to your advantage.

Transcript

Transcript generated with Whisper (turbo).
Misogyny classifications generated with MilaNLProc/bert-base-uncased-ear-misogyny .
00:00:00.000 So three people can go to the same exact restaurant and look at the whole thing from a complete
00:00:03.580 different lens. One can go and say, I just want good food and good service. Another person can
00:00:07.760 go and say, I wonder if this waitress is going to do a good job because they used to be a waitress 1.00
00:00:11.700 and they're watching all their mannerisms. Another person can go in and say, look at the way I
00:00:16.180 walked in, the menu, the chef, the plates, how they're lined up because they own a restaurant.
00:00:21.460 Today, I'm going to give you a lens to look at data in a way maybe you've never looked at before.
00:00:30.000 Okay, so stick around to Leverian. I'm going to give you a PDF on how to go use this with
00:00:35.760 your employees, your team, your staff, so you can get better data and get better results
00:00:39.300 to drive your company to newer heights. Let's get right into it. There's four different ways
00:00:43.600 to analyze data. The first kind is the descriptive analytics, then it's diagnostic analytics,
00:00:49.180 then it's predictive analytics, then it's prescriptive analytics. The first one, descriptive
00:00:53.760 analytics, is basic. You're researching and summarizing historical data in order to identify
00:00:59.140 patterns. How many sales did we do in the month of January compared to February compared to March?
00:01:04.400 It's very basic. It's very descriptive. Number two is diagnostic, which is understanding why
00:01:09.780 behind what happened. Why did we have a bad March versus last year? What happened? What were the events?
00:01:15.140 What happened? Did COVID change it? Did new laws come out? Did we lose a customer? Did we gain a
00:01:20.260 customer? What happened there? So it's the why. Number three, predictive analytics is studying those
00:01:24.640 to predict what's about to happen next. Well, the way we did last October and the way we're trending
00:01:31.040 this Q3 versus last year, Q3, this October, we're probably going to end up only doing $2 million.
00:01:37.240 We're only going to end up doing $3 million, or we're poised to have the biggest month ever because
00:01:41.460 we have this. But if you look at the data and you see patterns that you're not happy about your numbers
00:01:46.740 and you look at the predictive analytics saying, oh my gosh, if we go the way we're going,
00:01:49.960 we're going to have a bad October, that's when you come up with prescriptive analytics to say,
00:01:53.780 what changes do we need to make in order to change results? You would be amazed how few salespeople,
00:02:01.080 sales leaders, executives, and entrepreneurs actually look at data this way. I'm telling you here that
00:02:06.280 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
00:02:10.640 next side, which has different forms of charts to look at numbers. I remember the moment Tom came to
00:02:17.940 track my credit score back in the days. In 2003, I started tracking my credit score. Every month,
00:02:24.960 on the 18th, I would go to truecredit.com. My credit score was 484, 495, and 499. I raised that
00:02:31.100 to an 820, but I tracked everything. But that was a very basic way of doing Excel. We're going to look
00:02:36.040 at it in a completely different way. So number one, from line chart all the way to the highest,
00:02:41.380 which is technical. So what is a line chart? Analyzing numbers over time. You're looking for trends,
00:02:46.280 and it's one-dimensional. Pretty much the chart you're looking at on the screen,
00:02:49.280 that's what it's going to look like. Column chart, you're comparing 2021 to 2020. It's a vertical
00:02:55.120 chart. You're comparing May of 2020 versus May of 2021. Q1 of 2020 versus Q1 of 2021. Basic stuff so
00:03:04.020 far. You've probably seen both. Next one is a bar chart. So bar chart and column chart are pretty much
00:03:08.820 the same thing. The only difference is column chart is vertical, bar charts are horizontal,
00:03:13.720 and maybe you can add a little bit more to a column chart with different categories. Like
00:03:17.920 maybe it's one or two or three categories. You can add age. You can add different things to it.
00:03:21.880 Now we go to pie chart. Pie chart, you look at exactly what it sounds like. It's a pie chart. So
00:03:26.720 you sold a million dollars of real estate. Okay. What percentage was it homes between zero to 420?
00:03:34.260 What percentage was from 420 to 720? What percentage was 720 to a million, million to 2 million,
00:03:39.720 and up, right? So that's the pie chart. Pie chart can look at a lot of different things.
00:03:44.300 You ate food today. What did you eat? How much carbs? How much protein? Everything with that is
00:03:49.120 a basic pie chart. You've probably seen that before. Next is an area chart, which is a line chart at the
00:03:54.660 bottom plus a bar chart combined. So it looks something like this where the coloring tells you
00:04:00.420 how you did, what the sales was. So slightly more technical because it's telling you now multi-dimensions
00:04:06.440 of data combined together. Then you have pivot tables, which pivot tables are, they seem simple,
00:04:12.920 but a pivot table with somebody that knows how to use Excel spreadsheets, they have formulas behind
00:04:17.040 them. It could have a, you know, if you punch in a number in there, the formula is already calculating
00:04:22.920 it to say, well, if this is what you did based on a formula that we use and the commission that we pay
00:04:27.200 out, we're going to make $780,000. And you can kind of play with it to know if we did this much numbers,
00:04:33.160 here's how much money the company would make. Okay. So that's the pivot chart. And then you have
00:04:37.220 scatter chart, which you've probably seen the scatter chart with the dots on it, what that
00:04:41.080 looks like. That's comparing two numeric values. It could be cost and quality. And there's a lot of
00:04:48.320 things that you can track with a scatter chart. Then we have area map, which some call it scatter
00:04:53.280 map. This is kind of like how, you know, we were trying to find out COVID, what state has the most
00:04:58.360 people with COVID cases. And then it would show it to you. Region. If I want to know what country
00:05:03.300 has the most COVID cases, you would typically see that on a scatter map. If you want to find out
00:05:09.440 what the zip code has the most, six figure earners. If you want to find out where crime is the highest,
00:05:14.680 you know, they would use a scatter map. Very effective. And last but not least, it's a little
00:05:17.880 bit more technical, but it's a tree map chart. It's broken into subcategories. You know, maybe you want
00:05:23.780 to categorize your real estate loans that you did, what different loans you sold, you know, what
00:05:28.300 different products you sold. You may be a financial company. You do loans, you do real estate and you
00:05:33.420 do escrow and you do insurance. So maybe loans is going to be read and within the loans, it's going
00:05:38.040 to sell, you know, you did an interest only loan and then you did a 30 year fixed loan and you did
00:05:42.940 a 15 year loan. So it'll show you which one of that is the most. Then real estate sales unit, it can
00:05:47.620 categorize it as well. Escrow can categorize it. Insurance, it can categorize it all on one sheet, right?
00:05:53.080 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
00:05:57.440 simple, but this is what I want to do to you while you're looking at this. For me, I'm growing my
00:06:03.160 business. I'm a sales guy. Salesperson, you look at basic data. It's not complicated data. Then you
00:06:08.500 go become a sales leader and you try to drive your guys through just, you know, motivating them. You
00:06:13.480 can do more. You can do better. Try this script, try this overcoming objection, but then you have to
00:06:17.960 go look at their trends. And I remembered the things that changed because I came up with something
00:06:22.360 called DMA, you know, daily monitoring activity where everybody had a specific data of how many
00:06:27.540 calls they made, how many appointments they ran. And then we broke it down to how many they closed
00:06:32.280 based on their closing ratio to see how hard they were working. Accountability went higher.
00:06:36.680 Effectiveness went higher. Everybody made more money. Then you go into becoming a, you know, a CEO,
00:06:42.400 a founder. You start a company and then you get to a million dollar level, $5 million level,
00:06:46.740 $10 million level, $20 million level. Almost each level you go to, you plateau. If you don't unpack,
00:06:52.640 based on the right kind of data, you're not going to know why your company is slowing down.
00:06:57.080 You're not going to know the root cause. You got to get deeper. It's like solving an issue and saying,
00:07:01.560 why do we have such a bad customer service? Well, it's because we don't say, how may I help you?
00:07:06.740 We say, how can I help you? Well, because I don't know. We need to use a better script. No,
00:07:11.000 because it takes 48 seconds before somebody picks up the call. You got to get that to six seconds.
00:07:15.680 But because you're not tracking the data, you're not going to know that. You say you're going to follow up
00:07:19.260 within 24 hours, but 20% of the time you follow up, 80% of the time you don't. And the only reason
00:07:24.100 you don't have that data is because you don't track that data. So you go a layer deeper and deeper
00:07:28.440 and deeper and deeper to find that exactly the root cause of what's taking place. And if you can't
00:07:33.860 address it, your business grows. So having said that, if you got value from today's content,
00:07:38.880 give it a thumbs up, subscribe to the channel. If you want today's PDF, text the word chart
00:07:43.600 to 310-340-1132. Text the word chart, C-H-A-R-T, not plural, singular, to 310-340-1132. And if you're
00:07:52.560 international, click on the link below to subscribe to the newsletter, and we'll send
00:07:58.300 this PDF to you as well. And if you've never watched a video, How to Strategize as an Entrepreneur,
00:08:03.600 click over here to watch the video, How to Strategize as an Entrepreneur, because it has
00:08:06.580 a lot to do with what I just talked about today. Take care, everybody. Bye-bye.
00:08:13.600 Bye-bye.