How AI Can Analyze Data for You: Fast, Easy, and Complete | Lesson 7

[00:02] spreadsheets, reports, sales figures, marketing metrics, financial data, and more. But the big problem is that having data doesn't mean knowing how to make decisions with it. Because in practice, many people open a spreadsheet

[00:18] full of data but don't even know where to begin. Which numbers really matter, what's growing, where 's the problem, where's the solution, and so on . And in today's video, I'm going to show you how to use

[00:31] artificial intelligence to transform this data into action points. My name is Tainara Business in Mind channel. Here you'll learn everything you need to know about artificial intelligence. The idea behind this video is not to throw a spreadsheet into an

[00:45] artificial intelligence system and ask it to analyze this for me. Because analyzing data professionally isn't just about looking at numbers; it's about understanding what's happening behind the scenes, finding patterns, recognizing dips, identifying

[00:58] opportunities, and transforming all of that into practical actions, which is the most important thing. that a campaign had 10,000 clicks. What matters is understanding whether those clicks turned into sales, whether the cost made sense, whether any channel performed better, and so on. And this

[01:16] is where Manus comes in. That's exactly the work it will do for you, in addition to making it easier to visualize data that's in long and tedious spreadsheets. Let's start with a very practical example, and the link for you

[01:29] to access and use humans is in the description and in the pinned comment. By using this link, you receive 1000 extra credits. When you click, this screen will open. Then all you have to do is click continue, complete your

[01:42] automatically added to your account. Imagine you have an online store that sells a variety of home products, from decorations to furniture. Over the past 12 months, this store has compiled a spreadsheet with

[01:57] sales data, showing products sold, categories, months, number of orders, and much more. And in this case, it's this spreadsheet here. So we have registration ID, date, month, product, category, environment, channel, state, campaign name,

[02:13] number of orders, units sold, average price, revenue, unit cost, total cost, profit, gross profit, margin, and average ticket. important thing that I'll mention at the end, but I'll take this opportunity to

[02:26] reinforce it now, notice how there's no client's name here, no WhatsApp number, no email, no CPF (Brazilian tax ID), nothing. So, when we feed data into artificial intelligence, we'll always remove the

[02:39] sensitive data. Then you can duplicate the original spreadsheet and remove that sensitive data. Here he also explains a little better, then, the months, the categories and all the products. Oh, and most importantly, when I come down here,

[02:53] look, there are quite a few requests on this spreadsheet. be difficult to answer So, here on the menu, I'm going to click on more, then view. And here he even shows

[03:09] some examples of prompts, such as analyzing e-commerce sales and categories, and also the output format. So, graph. There are several graphs here. We can select a specific one or let him choose.

[03:22] We offer the option of slides, website, spreadsheet, and report. So, I'll select the chart first. We will attach the spreadsheet. So, I'm going to click here, add from local files. Okay, I've selected the spreadsheet. And my

[03:35] prompt ended up like this. Analyze this sales spreadsheet for the last 12 months different categories. I want you to identify seasonal sales patterns, fastest-growing categories, declining products or categories, and

[03:50] growth opportunities. Also here, let me remove the space, strategic recommendations based on data. Having done that, Manus has already completed the task. And we can even see here, step by step, the process he followed.

[04:04] So I'm going to get off here. Ready. He reported that he created 10 high- quality charts and a detailed strategic report based on sales data a summary of the graphs, where he explains each one in more detail. For

[04:17] example, first, seasonal patterns, monthly revenue and orders, highlighting the PEAK in January 2026. Key findings, but it's better if we look directly at this report that it provides. So

[04:31] here we have an executive summary, identified seasonal patterns, best-performing products, fastest-growing categories, declining products and categories , growth opportunities, and strategic recommendations, in addition to

[04:45] adding key indicators or KPIs here at the end . And here it already gives us the option to turn this analysis into a website. So, if I wanted to, I could just click here to create a website. Well, I can also download it in Markdown, PDF, or

[04:58] Doc format, and I can save it to Google Drive or OneDrive. If I click on the three dots here, I can even edit it in Google Docs. And here, in the share section, you can share this file with another person. Okay, let's take a look at the graphs

[05:10] he created. So, here we have the first chart showing seasonal patterns, monthly revenue, and orders. So, here it lists the period from June 2025 to May 2026, with this yellow line representing the orders. So on this

[05:24] side we have the revenue and on this side the number of orders. He always so it's very easy to interpret the data. Here's an overview of revenue by category over the last 12 months. Each line represents a category that

[05:38] is listed above. Top 10 products by total revenue. Growth by category, first quarter versus last quarter. Products experiencing the highest growth. Products experiencing the biggest price drops. Revenue share by

[05:51] category. This chart turned out really well. Average gross margin by category. We also have here an opportunity matrix with margin versus growth, where size equals total revenue. Heat map and

[06:05] products with consistent growth. So, you see how you have a range of charts here that you could use. When you transform spreadsheets into charts, it becomes much easier to visualize what's happening. And this

[06:17] first demonstration serves to show you the complete workflow. You start with a raw spreadsheet, ask humans to analyze the data, they find patterns, create charts, and in a few minutes you have material that could

[06:30] easily be used in a meeting, presentation, and more. And So I'm going to select one of them, see, can do it like I did, right? Or if you're in preview mode, there's already a little button

[06:44] here to edit on the canvas. So, we can put it in full screen. Okay, so here we can switch to the handheld tool , where you can move around more , where you can move around more easily through all the graphs

[06:56] an image to add to this same frame, or generate a new image to be again, which will not replace any existing image. And in the editing tools, we can add comments. So, I'll add something here and make a

[07:11] comment. Or I can select a specific area, for example, this one here. And I can request a change from humans. Furthermore, by clicking on the image, we have the option to enlarge it, then convert it to HD, remove the

[07:26] background, and edit the text. So, I'm going to zoom in here, see? I'm going to click on edit text. It'll load a bit and then I can change it, right? So, for example, I can select the one above and add two dots or

[07:39] a dash and click save. Here you can also download just this image. delete. The delete function is useful when you request variations of a chart and you've already found your final version. In that case, you can keep that version and delete the

[07:53] use. I'll show you later, but you can view all the files that were created and generated in this conversation. Now that humans have transformed the spreadsheet into graphs and shown an overview of the data, we're

[08:07] going to take it a step further. But first, take the opportunity to like this video, subscribe to the channel so you can stay updated and help us reach 300,000 subscribers. I want to start by thanking all of you who

[08:19] are always here following our content. Leave a comment below, even if you already knew humans, or if you already use it, but if you want to get ahead and find out about the latest news from A

[08:32] before everyone else, then I invite you to join our free WhatsApp group. And rest assured, it does n't contain good morning messages or people sending stickers; it's simply news that we've hand-picked.

[08:44] your phone at the QR code displayed on the screen or click the pinned comment. There you can also find our free materials, such as courses, prompts, and spreadsheets. So, take a look. Well, a

[08:58] professional analysis doesn't end when you find out which products will sell the most or which months performed best. This is just the first layer. The next step is to understand why that happened and what can be done

[09:11] about it. So, instead of asking for charts and a general summary, I'm now going to ask humans to delve deeper into the analysis with a strategic perspective. The idea here is to use the result of our first demonstration as a basis and ask him to

[09:26] investigate the patterns found further. So, the prompt ended up like this . Now, delve deeper into the analysis based on the generated data and graphs. I want you to identify it. So I listed here what I would like him to

[09:38] identify. Finally, organize the response into a strategic analysis, explaining what each finding means and what action could be taken. Hey, look how interesting what he did here is. He performed an advanced cross-referencing

[09:50] of the data and created eight new complementary charts to illustrate the hidden patterns, anomalies, and opportunities that were not evident in the initial analysis. Here he includes a summary that will also be in

[10:04] our strategic analysis, but now in greater depth. So here he added hidden patterns and correlations, consistency of growth, anomalies and outliers, evidence of campaigns and channels,

[10:19] business opportunities and practical recommendations, plus we now have new data as well. For example, gross margin trend by category or gross margin by channel versus category. Products with underutilized potential, which

[10:33] have high margins but lower revenue, in other words, an opportunity for scale. After generating the charts and deepening the insights, we'll transform that into a more professional deliverable, because often you don't want to analyze the

[10:47] data just for yourself. You need to present this analysis to a manager, a client, your team, or even use this material in a decision-making meeting. So now the idea is to take everything that Manus has already identified in the

[11:00] other demonstrations and turn it into an executive report. And the prompt ended up like this. Now transform all of this analysis into a professional executive report for the store owner. The aim of the report is to assist in

[11:13] decision-making for the coming months. Structure the report as follows: I've included what he should add here, which are these points here, and ask him to use clear, objective, and professional language, as if this report

[11:25] business meeting. Again, here we have the final result that I can expand upon, and we can even edit this document; you can change it. So this can make changes within Humans itself and then just save, right?

[11:42] So here you can also, for example, change the formatting of this text, make it bold, italic, put that line above the text, put that line above the text, mark it as code, or add a link. And

[11:54] download, share, and everything else. So, I'm going down here, see? See how he added spreadsheets here too, but in a much more organized way, right? So, with a general summary, like in these

[12:06] operational efficiency indicators, we also have an analysis of seasonal patterns. See how many spreadsheets he brought here, and this makes things much easier. Instead of just text, it's easier for me to glance at it here. OK I understand. So, the rug

[12:18] had this revenue, this gross profit, this margin, this number of orders, and it's stable, right? It would be better if I explained it in a little text, wouldn't it? So here, in addition to these spreadsheets being selected by category, right?

[12:31] So each one has a title. Again, there's text here too, but we have a that's also why an executive report is important , right? It's not just a complete analysis of the data where you

[12:45] have a lot of text. I'm coming down here. He even set goals for the next 30 days and offered final considerations. The most interesting thing is that he also included the graphs here, the most relevant ones where he made adjustments. And he

[12:58] also brought a PDF, look. So, we now have that entire document in PDF format, which makes it even easier to view, especially since the background is white here, right? This gives more prominence to the text and tables. So I'm going to come

[13:11] seven pages long. And I can download it here too , okay? I can download it, convert it to Google Docs, save it to Google Drive, or save it to OneDrive. Now, after analyzing the spreadsheet, identifying patterns, generating charts, and

[13:24] transforming all of this into a report, it's time to move on to an even more visual stage. The idea now is to transform everything he already knows into a dashboard, because a report is great for explaining what happened and

[13:37] presenting recommendations. But a dashboard is best when you want to track key indicators quickly, visually, and in an organized way. So, instead of constantly going back to the original spreadsheet or

[13:50] consulting the report to search for information, you can ask humans to create a visual page with the key data from the analysis. For example, now transform this analysis into a visual dashboard to

[14:02] track the performance of this store. Create an organized page with, ah, I added here everything he should add to this dashboard, which is this part here. Finally, the dashboard should be visual, clear, and easy to understand,

[14:14] as if it were being used by a manager to track e-commerce results and make decisions quickly. And here is our dashboard. So here we have an overview with total revenue for the last 12 months, total

[14:28] orders, average order value, gross margin, best category, leading product, best month, and monthly average. Going down here, we have revenue and profit with an overall view, see. Actually, he's quite... you see how dynamic he is?

[14:42] example, that in November the revenue was R$ 427,000 and the gross profit was R$ 161,000. But it does n't stop there. We also have a monthly trend, where he put here monthly revenue, separated by

[14:55] each month. Look how interactive it is, how much better it is than that standalone chart you add to a presentation. Here we also have the orders and average ticket price, and the evolution by category. Wow,

[15:07] visually than you having to search for, "Oh, okay, this line, this thing, and here, what's the number again?" Right there in the middle, which one could it be, what easier. If you hover your mouse over this section in October, you can already see the

[15:20] evolution of each of these categories listed below. Monthly gross margin . We also have a product ranking section here on the dashboard . So I'll keep passing this along so you can see. Full ranking. The categories are

[15:33] revenue, margin, orders, and growth. Quite a lot of product is also falling in price . Now here's an analysis of the categories. Alerts. And this one is very important. Okay, then. What do we need to do? And let's

[15:46] look here at what's on alert and we're going to set this to zero. And then we'll also look at the opportunities, OK? So here are two critical factors that require immediate action, five high factors to monitor closely, and two

[15:58] moderate factors to track the trend. So here are the warnings, for example, the large abstract painting had a 66% drop in the quarterly comparison. And here, too, is the context of the warnings. He lists the opportunities, which is

[16:12] also very important. For example, underutilized high-margin products, the consolidated potential impact of these opportunities. And here are some recommendations as well, such as margin protection, growth acceleration,

[16:26] portfolio management, an action plan for the next 30 days, and goals for the next 30 days as well. And this is actually the last lesson of the week of knowledge designed by humans. These seven lessons will teach you how to use humans

[16:39] like a professional, automate tasks, and save hours of your day. We've also created a playlist with all the lessons so you can follow the complete sequence. The link is in the description and in the pinned comment, but

[16:52] hold on, don't leave yet because I'm going to show you more things in this video, including an advanced feature. And the interesting thing here is that I can edit this dashboard. So, I can come here and describe my change

[17:06] to Manus, and it will make that change. Or I can just come here and change the text if I want to, right? In addition to the desktop version, we also have a mobile version of this report, okay? So, I'm going to go back here to the overview, see?

[17:21] So, you can also view it in a mobile app format, including the graphs, okay? Wait, let me climb up here. Coming back here. Well, here in the chat I can ask for the

[17:36] edit it here. So, I can publish this dashboard and share the link with also has a database, file storage, a control panel, SEO analysis, it has quite a lot of features here. O o manus ele não

[17:50] cria um design, ele cria algo funcional. So, he creates the back end and the front end. So you can publish this here and use it normally, just like you can create websites, tools, and applications. And I showed you more

[18:03] details about these settings here, including publishing, buying a domain, which you do all through humans, and I also taught you about the command prompt. Well, all of this is compiled in lesson five, which is appearing here in the cards,

[18:15] description and in the pinned comment, but it's also within the playlist that's here as well. So, how can it get better for you? And after you've created an analysis like that, you have the option to create something even more interesting.

[18:29] You don't need to redo this process manually every time. In fact, you'd be wasting your time, because there's a way for you to automate this analysis. you do frequently, a monthly sales analysis for example, a

[18:42] weekly campaign report, e-commerce tracking, or product performance review, you can transform that process into something reusable. In other words, instead of explaining from scratch how you want

[18:55] the analysis done every time, you can save this process here as a skill or ability. Therefore, whenever you have a new spreadsheet, you can reuse the same analysis process. It's like creating a specific analyst model

[19:08] for that task. And we can even do that right here in this same conversation. To do this, we're going to activate the skill creator ability, which is this one here. If you don't have one, you can click here to manage skills. And then you're going to

[19:21] skill creator. Or if yours is in English, it will be "est skill creator", okay? So we're going to select her, okay. See how she already looks like this? In this written text format? It needs to stay like this, okay? And I'm going to use this prompt. Create a

[19:36] professional e-commerce data analysis. sales spreadsheet, SK should analyze the data and deliver a clear, strategic, and visual overview to aid decision-making. SK must follow this process. So I listed

[19:50] the process here, which is basically a summary of everything we did here. The final result should be organized into an executive summary, key metrics, visualizations, problems or warnings, growth opportunities,

[20:03] action plan. Use clear, professional, and decision-oriented language. Whenever important information is missing from the spreadsheet, make a note and explain how this might affect the analysis. Now I'm going to

[20:17] send it. And if you haven't already, leave a like on this video and leave a comment too. Guys, I've mentioned this in other classes before, sometimes it feels like I'm talking to myself here, like you're not talking to me. We can

[20:29] Actually, I really like your comments. We're always reading and responding to as many messages as possible. We can already see it here. So, can see the steps he is taking. While he's creating it,

[20:43] I want to show you that here, by clicking on "see all files" in this task, you can filter by documents, images, code files, and links, or all of them. And you can even download in batches. So, here in the images there are several

[20:57] graphs, I could come here to this batch download option or download from here. I can also locate it in the conversation, preview it. And here in the usage section you can see how many credits you have already used for this task, as well as

[21:09] pages viewed, commands executed, APIs and calls, and files created 23 files. Okay, here it provides a summary of this skill, and it indicates e-commerce sales spreadsheet I send in the future. This

[21:24] skill includes complete instructions with a seven-step process. So, exploration, validation, metrics, analysis, charts, reporting, and delivery, among others. structured template for the final report with all

[21:37] click on "add my skills". Okay, I put it to the test. Now in a new chat, I'm going to come here and use my skill. I'm going to select e-commerce analytics and ask you to perform a professional analysis of

[21:51] sales spreadsheet. I'll upload the spreadsheet here and show it to you shortly. I 'll just send it here first. Ready. And in this case, it's this spreadsheet here, where we also have several, oh, several sales, just referring to the month of May

[22:05] this time, [clearing throat] right? And here are the other categories that now he's added a few more. Okay, let's go back to the guys. So it's here. Starting with our executive report. So here we have the

[22:20] period, the date of the analysis, and the source, which is our spreadsheet. So, executive summary, key performance indicators, with a table here as well, seasonal patterns, best performing products and categories . Another

[22:34] spreadsheet, products in continuous growth, spreadsheet. So you can see how it becomes more visual and easier to read, to understand what's in this report. 's already there. It also includes alerts, products and categories experiencing decline,

[22:48] growth opportunities, short- and medium-term strategic recommendations, and an observation about the data. Furthermore, it also generated our graphs here. So I'm going to show you now, based only on this spreadsheet that has the

[23:03] sales for May, including future sales that I asked him to include until the end of May. Remember that you can also ask him to edit this example, on edit in canvas. And beyond this e-commerce example, you can

[23:17] use this type of analysis in many other scenarios. For example, in sales you can create a quarterly review, compare regions, identify trending products, and generate a presentation ready for the meeting. Then you can

[23:30] turn all of that into a presentation as well. In customer research, you can analyze form responses, satisfaction ratings, complaints, and suggestions to uncover patterns, recurring pain points,

[23:43] and opportunities for improvement in both your product and your customer service, which is very important because sometimes you are losing many sales due to poor customer service. Now, in market research, you

[23:55] can compare competitors, prices, features, positioning, and differentiators. Furthermore, it can be combined with Manus' Wide Research functionality to collect market data and then transform

[24:09] positioning maps, and strategic reports. Regarding wide research, it involves a broad search. So, we have Deep Research, which does a deep search, and we have Wide Research, which does a broader search, it's

[24:24] can collect more data. And I explained more about this feature you can find in the playlist that's in the description and in the pinned comment. In the area of ​​finance, whether personal or business, you can analyze

[24:38] business, you can analyze revenue, expenses, cash flow, and monthly trends to create visual reports, identify trends, and prepare presentations for partners, managers, and others.

[24:51] You can also use it in marketing to, for example, compare campaigns, example, compare campaigns, acquisition channels, conversions, cost per lead, ROY, and performance over time. But the main point is this:

[25:04] whenever you have data in a spreadsheet or structured files, humans can help transform it into something more useful: charts, reports, dashboards, visual pages, and practical recommendations for

[25:17] decision-making. And you can adapt this skill to your format, for example, there. Okay, I prefer that he creates a presentation in the final results with this analysis, because then he can add the graphs as well, or not. Ah, I prefer

[25:29] a PDF, where the analysis, the report, and the graphs are all in one file. You can do it that way too, you can adjust it, you can dashboard format, whichever you prefer. But it's important that I be

[25:44] honest with you. AI greatly speeds up this process, but it doesn't eliminate the need for a final review. She may make mistakes, misinterpret some data, or reach a conclusion that needs to be validated. You have to understand that what

[25:57] So, what he added there in terms of suggestions for next steps, practical actions, you interpret that as suggestions, and then you analyze it to see if it makes sense or not. Furthermore, if the spreadsheet is too cluttered,

[26:10] with confusing columns, missing data, or inconsistent information, the analysis may also be less accurate. Another point is that not every graph will automatically be the best at explaining that data. Sometimes you'll

[26:25] need to request adjustments, change the chart type, or simply simplify the visualization. Also, be very careful with sensitive data, especially customer information, financial data such as account numbers, etc.,

[26:39] and any type of confidential information, okay? But I have a huge spreadsheet here, everything's perfectly organized . I have several metrics, but there's the customer's name and their email address there. What do I do? Well, you

[26:51] duplicate the spreadsheet, delete those columns, and that's the spreadsheet you you duplicate it, you can include in the name "manus version" and "ia version" to make it very clear which file you are going to upload. So, think about Manus AI,

[27:07] which will greatly speed up your work. He will organize data and also generate insights. But the final decision still needs to go through human review. So, as you've seen, AI can completely change the way you

[27:20] analyze data. The most important thing to remember is that analysis isn't about pretty charts; it's about understanding what's happening behind the scenes so So go ahead and test it out now with your spreadsheets while the

[27:34] content is still fresh in your mind. And remember that the link is in the description and in the pinned comment of this video. By using it, you will earn 1000 extra credits. When you click the link, this page will open here.

[27:46] Then all you have to do is click continue, complete your registration, and the credits will be added. automatically in your account. And to continue learning how to use humans professionally, also watch the other

[27:58] lessons in this playlist here. I hope I was able to help you, and see you in the hope I was able to help you, and see you in the next video.