From Chaos to Clarity: The Art of Data Storytelling

In this episode, we sit down with James Eagle, a data visualization specialist who spent two decades in asset management at HSBC, Fidelity, and Vontobel before co-founding PlotSet. James helped win $41 billion in assets from sovereign wealth funds by making complex data instantly clear, and now creates viral animated visualizations for Visual Capitalist that transform how millions understand the world.

Takeaways

• Data visualization is a tool for delivering clarity.
• Storytelling is essential in both writing and presenting data.
• Laziness in communication leads to ineffective data presentations.
• Understanding your audience is crucial for effective visualization.
• Static bar charts are often the most effective visualization type.
• AI can enhance data visualization but can also spread misinformation.
• Every chart should convey a clear message to be valuable.
• Emotional engagement is key in data communication.
• You can create effective visualizations without coding skills.
• Practice framing information to make it relevant to your audience.

Create Your Own Charts: https://plotset.com/
James' Newsletter: Killer Charts Blog: https://killercharts.blog/
Get the Book "From Chaos to Clarity": https://amzn.to/4r9nHpA

Transcript

0:01

James Eagle, welcome to Productivity. Thank you very much, Santiago. James, you have had an incredible journey from HSBC, Fidelity, and now you're a co-founder at PlotSet. What was the moment you realized that data visualization was your thing? Oh my gosh, that's a huge question. I know that sounds like a simple question, but it really isn't a simple question. So if you, mentioned those two companies, I worked for probably five different asset managers over the course of my career. When I was working as an employee and I think the moment that I just, found that when I started to pivot was probably around about 2018. So I was working at Vontable here in Zurich and my job. at Vontable was as an investment writer. And I had this problem. I didn't know if people liked what I wrote because I got no feedback. I didn't get any feedback because I got feedback from important people like senior management and um from uh portfolio managers and analysts. And they all said, you're doing a great job, James. Good stuff. This is really great. Really, you know, and basically my job at the time was to write about markets and economics and all these, these very complicated topics. But I didn't get, when I say important people, they weren't really the important people. The important people were the investors who were our clients. I didn't get any feedback from them because I didn't have any contact with them. So I had no idea if what I was writing was being read. The things I was writing was being read by the people who really matter who are the investors. So I decided, well, What do do? um I'm not really into social media. Well, I wasn't at the time. um But I do have a LinkedIn account and I know that you can write articles on LinkedIn. So that's where I started. I started writing articles on LinkedIn and it turns out that I was a terrible writer. It was a complete disaster. It wasn't that I was writing badly like in, well, I was writing badly, but I wasn't, I wasn't, it wasn't the grammar or the English that was bad. It was, The fact that what I was writing was just really boring and no one cared about what I was writing. And I realized that I was working at this company, earning a nice Swiss gallery, earning all this money and adding absolutely no value. And that was the first pivot. The first pivot was things need to change. I don't want to just, I mean, I could just turn up and earn that salary and no one would say a thing. No one would know that I was terrible, but in my mind I was and I wasn't happy with where I was. And so when I left Vontable, I went on this journey of discovery. wanted to know what it takes to make people listen. How do you communicate better with people? can we communicate better with investors and talk about complex topics in a way that they understand? And that's where it started. So I continued writing. I became a freelance investment writer. I became a lot better at writing and I got some great clients from doing that. I hustled, I did a few different things. I failed a lot, tried a lot, experimented. I tried a YouTube channel that didn't really go well. I worked as a head of IR for a battery company which no longer exists. I did a lot of different things and I stumbled into data visualization. And the way that that happened was somebody told me, or asked me, said, James, how do you create a chart like this? And I said, I don't know. It looks amazing. was this kind of animated bar chart was racing along and they call them animated bar charts. I'd never seen anything like it. And I thought, okay, let's find out how it's done. Turns out it was done using something called JavaScript and a package called D3. um And that's what I discovered. So I um used to code when I was a teenager, just as a hobby. And I found that actually it wasn't that difficult. um to pick up, partly because the technology nowadays is a lot easier and it's got even easier now with AI. Bear in mind, this is before AI. So I learned how to start making these charts. And so it really kicked off. is, so I left in Vontel in 2018. We're talking end of 2020. That's when I started creating these charts and they just exploded. It just went viral. they went all around the world. They were shown in boardrooms in Wall Street that were used by, in press conferences by heads of state. And before I knew it, my work was everywhere. And that's basically what happened. That's how I ended up doing what I do. And I'm still doing it. Wow, that's quite the story, James. In your time at those investment firms, what were the biggest misconceptions about data and data visualization? You were not that much in data visualization back at the time, but with what you know today, what were the biggest misconceptions about data that you would fight against today? I think it wasn't so much that there were misconceptions. There was just a certain degree of laziness. And I was part of the problem because I never really thought about data visualization as a tool to deliver clarity. I mean, bear in mind that I was already a bad communicator. I could barely communicate in English properly in what I was writing, even though I thought I was great. This was the problem. It was ignorance. So oh I was writing badly. um And I think in a way, we also present data badly. So, and it all boils down to, in my mind, storytelling. So when we write, we are telling stories. When we present data, we are telling stories. And it's our ability to say that or express that in a clear way that matters. um You know, and I always use this analogy, you know, like if you have, say, for example, you went back in time um and you met a caveman and the caveman is sitting around a fire with his son. And the caveman is telling his son how to kill a mammoth because one day he'll need to do that in the future to keep his tribe alive. Would he give him um a complicated five point plan or would he tell him a crazy story? I think the crazy story is what I, mean, as a dad, that's what I would do with my son. If I was a caveman, I would tell him the most craziest bad-ass story you could possibly imagine. I would make sure that he's listening to every single word that I'm telling him. because I know that one day I won't be around and he will have to probably go out there and hunt a mammoth and save his tribe. And it's the same with data and it's the same with writing and it's the same with everything that we do in life. The way we communicate can have a profound effect, not just on the people we love and are trying to help, but also on our clients and the interact and the people around us. It's a form of information transmission that we have been using since the dawn of time. know, since cavemen times, we've been painting pictures and walls to tell stories for generations. We've been developing maps to help explain to others how to find their way in the world. And maps are actually the first formal data visualization that we had. the problem is that nowadays in the world that we live in, there is so much information and so much data that it's become harder to communicate. even with AI. In fact, AI has made it even harder, even more difficult to communicate. So back then, I would say that the misconceptions that we had, there was there were certain things that we knew and certain things we didn't know. So one of the things that we knew was that in the investment industry, understanding risk is everything. And that a lot of the time we have a very poor understanding of risk, because we we are not genetically designed. We haven't evolved fast enough to understand the data saturated world that we live in right now. So I think there was always an understanding that we struggled, that we struggled to understand the world that we're in and that we haven't evolved fast enough to understand the world we're in. But where we really failed was finding the solution to those problems. And I think the solution was using data visualization as a tool to communicate. And going back to what I said before, the biggest problem we had was that we were lazy. And we still are lazy. We're lazy in the way that we communicate with data and in the way that we write. So we often don't think about what this chart is trying to convey, whether or not someone will listen or read or care about the chart that we're presenting. in front of somebody. And if the chart doesn't convey a message or if the chart is ignored, then it's a pointless chart. So if you produce, for example, a chart of the S &P 500 and nobody looks at it, then there's no point in producing that chart. And I think the problem that we had in that time when I was working in asset management was that we were producing far too much content and not thinking about whether or not that's actually making an impact in the world. I believe that every time that you speak, write or make a chart, if it has no positive impact on the world, then you're failed. Then it's a failure of communication um and the world will not be better as a result of that. And in this day and age, that's very, very valuable because that's very, important because um failure to communicate can have disastrous consequences, whether it is, um you know, failing to communicate to your investors to explain to them the risks that they face, or a failure to understand yourself about the risks that you see, you know, so I think it's, I think those are the kind of the misconceptions, it's not so much misconceptions, I would say it's more laziness and unwillingness. to try and understand about the importance of how you communicate with data. James, what's the biggest time waster you see in corporate meetings that proper visualization could eliminate? um So that's a good question. um I don't think it's so much the I think it's more, it's not, it's, I think the biggest kind of. It's difficult to say because it's not the way that data visualization works is first of all, you get the data, right? Then you explore the data. And once you explore the data, you understand the story behind the data and then you create and visualize the data. So in a corporate meeting, the problems that you often find is that there's no exploration. It's dominated by assumptions and opinions and, and, and, and that for me is where things grind to a halt because you go into a meeting and it's full of human biases, full of opinions. And in my mind, opinions are cheap. Anyone can have an opinion, but backing up an opinion with something that's tangible and real is much harder to do. So it's not so much that data visualization um solves that problem. I think it's more about the structure in which you arrive to that data visualization that can help. So first of all, you know that there's something that you need to look at, which is the acquisition process of getting data. So you download data, you find data, you've got this information in front of you, right? Or you don't. So sometimes in meetings, they have no data, but they have lots of opinions. But let's assume that they have the data in front of them. The second thing that you need to do is basically you need to find out the story behind that data. What is that data telling me? Now, if you go into a meeting and you make a lot of subjective assumptions and you say something like, I don't know, retail sales have gone up 100 % because people are really into AI. It's an assumption. You've got no information, no data, nothing to back up that point. You've just made a statement. Therefore, the business should do this. um Now, maybe you could download the data and have a look at it. And then maybe you could do a Skanky diagram to see where the retail sales came from. And then you find, actually, um most of those retail sales are not going into AI-related products. They're going into something completely different. Then suddenly you realize that, actually, um the story here is a little bit different from what we interpreted. So it's not that you're saving time, but you're saving time from not going in the wrong direction by using data visualization or using basic um data visualization frameworks or workflows that you would go through. So thinking from step by step, how do I get from? How do I interpret the data set? How do I see what the story is? And how do I visualize this to make everyone else understand? And obviously, you can't really data visualize something in a meeting. But you can certainly understand where you need to be or what the story you need to tell is if you need to report that to someone higher up in management. And a lot of the time, that's what I'm doing. So I meet with clients. We discuss a bunch of ideas. We usually have hundreds of ideas, but during that time, we can figure out what the story is behind eh what they're trying to tell. We can figure out where the data is supposed to come from, and we can understand how we want to visualize it within a relatively short period of time. And then it's a matter of me going away and creating the data visualization, which they can then use their clients to explain something that was previously very difficult to explain. So I guess it's not so much that you use data visualization in the meeting, but you use certain disciplines which are part of the data visualization process that get to get you that allow you to create a data visualization that allows you to explain a complex topic. We've discussed a bit about business and data and visualization, but how do you use visualization for personal productivity? um It depends. I would use, right, so this is a little bit out of my area. um But a classic example would be, let's say, for example, you work in a large company and you report to a CFO and this company has multiple businesses all around the world. And every quarter you need to compile all the sales data. And you need to present that information to the CFO or even the CEO so that they can make important strategic decisions for the business. So to do that, you might build a dashboard, a dashboard that visualizes information that's valuable to that CFO or to that CEO so they can understand what decisions to make. And feeding that dashboard is a lot of data that comes from lots of different marketing teams and sales teams all around the world. um So that is an example of where m if you set up in the right way, you can use data visualization to make yourself more aware of your business and the risks that your business faces and give a very quick understanding of where the revenues and sales are coming from. um So if you're running a very large business, um if you don't have those basic data visualizations tools, you're actually at a massive disadvantage versus your competitors. m These days, in this day and age, most companies do this now. They have the right type of enterprise software in-house. um And they automate a lot of these processes as well. uh So they're constantly collecting data from their business lines, visualizing it in dashboards. And then their management teams are able to interpret those data visualizations and make the right decisions for their companies. um So in terms of productivity, uh That's one example uh I would use. uh It's not so much productivity, um it speeds up the decision-making process. So you're able to know what you're supposed to do. Other examples, personal examples, I would use this for example. Say, for example, you've got an iPhone. You need to get to a meeting. A classic example of data visualization is Google Maps. So a map is a data visualization. So you go into Google Maps, and you say, I need to go here. And you press it. into your phone and then you follow the map and you get to your meeting on time. That is something that has made our lives easier. there are so many other, there are lots of personal ways in which we use data data viz, which you don't realize the weather forecast you watch on TV. So that's another example of data visualization. So when you are, when you watch TV, the anchor, the TV anchor will, the weather, the weather forecaster will say, hey, this is what's happening in Switzerland. It's going to be snowing in Zurich tomorrow. um And as you can see, the snow is coming in from the mountains. And they show it visually. And that is a data visualization. um And yeah, so there's multiple ways that we actually already use data visualization to make our lives easier, um whether it is um looking at um I don't know. So the weather forecast, a map. In hospitals, they use data visualization to see, um like for example, if a pregnant lady's baby is healthy, or if you've injured yourself on the ski slopes and they want to see if you've fractured a bone, they'll use data visualization to see what's going on beneath the skin. So there's multiple ways in which um data visualization, it's not so much productivity but it just makes our lives easier uh and whether it's in business or in our personal lives. You've consulted across oil and gas, renewable tech, What is one visualization mistake you see everywhere? So oil and gas, um they use data visualization a lot. So a classic example is, for example, if they're doing an exploration project or a production project, uh they will do a seismic report where they will try, without getting too technical, um what they do, it's like doing an ultrasound on the ground to see what's underneath the ground. And they will use that to interpret what's going on, where to try and find where to do maybe, for example, a test drill to build a kind of a test well during the exploration project or to boost production. So often they use a lot of data visualization already when they're doing these projects. The problem I often see is that they're very, very hard to interpret unless you're an expert. So I think sometimes in our industry, and this goes with finance as well, we make our lives harder than they need to be. By making the data visualizations overly complicated. And this is something I've seen in oil and gas. This is something I've seen in the financial industry. Like you look at a presentation or a deck and you're looking at it and you're thinking so hard, ah, what is this showing me? I don't understand. And I think for me, like I have a three second rule. If I look at a chart and I don't get it, it's a shit chart. I don't want to look at it. I don't want to look at that chart. Move on because you shouldn't have to cognitively think too much every time you see a data visualization. um If you're doing that, then um I think the question you need to ask is could I have actually done this with words better? Could I have used natural language to communicate this point? And if I could, then I'm... It should not be a data visualization. When should someone not use visualization? Are there cases where a spreadsheet is actually better? Uh, yes. I mean, my tickable problem isn't so much this, the data visualization or spreadsheet problem. It's often, should I animate this chart or should I not animate this chart? And this is, um, this is a struggle that I personally have my clients. So often they'll come to me and say, we want to do an animated chart with music and drama. And here's the story. And then I tell them, don't animate it. If you animate it, it's not going to, it's not going to be as effective. as if you just presented a static chart. Sometimes you need to see, um you have to kind of stop and think, am I delivering something that's clear and um something that makes sense? The classic problems I see is a lot of chart junk. So unnecessary text, um unnecessary imagery added to the chart that adds no value and unnecessary animation. And I know that sounds crazy because that's what I'm known for. I'm known for animated charts. That's what people like love to see from me. They like to see me make those animated charts. But honestly, sometimes a chart is better left alone as a static chart because you're absolutely adding no additional benefit from animating it. You're not making it easier to understand. Sometimes animation can guide you, it can make you focus on the data set more because you're looking for the outcome. And other times, the outcome can be understood within seconds with a static chart. So the biggest challenge that I see is, first of all, trying sometimes to convince a client that they don't need to animate a chart. They just need a clean static chart to tell the message they want to tell. And then the other challenge I have, as I mentioned, is making the chart overly complicated, putting too much text in the chart, uh putting too many graphics or unnecessary things. And finally, I haven't mentioned this, distorting the chart. So um not using clear axes, the way that starting the axis at a strange number, or adding 3D effects that just literally add no value um and actually make it harder to interpret the data that you're trying to view. For someone that cannot code, you say you use D3.js, what is their path to start creating effective visualizations? I think if you've made a chart in Excel, then um you've already taken a giant leap in that journey. So data visualization, it's a bit of a buzzword, but effectively what you're trying to do is you're creating um an image with data. And a classic example of that is just a simple Excel chart. um So that's where you start. You don't need coding experience to do that. You just need to know some basic kind of Excel functions, which most of us know, to create a simple chart. um And I think also what I would do then is I would think about kind of the basic lessons, like thinking about eh how do I make uh How do I make a chart impactful m following basic principles of data visualization? um So there was a guy called Edward Tough um and he produced a really good book which you can Google. um Written in 1983. Let um me just pull it up. So, cause I've forgotten the actual name and that's basically what I use. for everything. So when I feel that I'm kind of deviating. um So his book, let me just find the actual name because he's known for his principles in data visualization. uh You can order it on Amazon. So his famous book, he's done quite a few, but the one that I always go to, I'm just gonna find the one that I use. um The visual display of quantitative information. Yeah, I was never going to remember that. But I have this book and he produced this in 1983 and it is a brilliant book. He's quite strict in terms of the rules that he applies to data visualization, but I use that for pretty much everything. And I would say that having basic good principles focusing on clarity is really important. And I think that's where you can start. And then if you want to take it to another level, uh you can learn to code and you can do all these things, but you don't need to. Remember, we've got a lot of technology nowadays. We've got things like AI. So you can create charts using AI. ah You can go into Claude or you can go into ChatGPT and you can ask it to create a chart for you. um You can also uh use tools um like PlotSet, which is a company that I've co-founded, um which can help you actually create charts without using code or having any design experience. And you can create animated charts with that. You can create interactive charts where you can interact and embed into your websites or whatever you like to do. So we're very fortunate nowadays that we're in a position where access to information is easier than ever before. We have AI tools to make our lives easier as well. So really, you don't need to be a expert coder or a graphic designer to produce beautiful data visualizations anymore. The technology has empowered us to be able to do it yourself. Your charts, James, are incredible. They seem to be designed by genius. How can people develop these kind of visual thinking skills? And is this something you need to be born with or something that you can develop? First of all, you're already born with it because you're a human being, you're a homo sapien. And as a homo sapien and a member of the human species, you are naturally already a storyteller and a visual thinker. And unless you have a serious mental deficiency, I don't think this is something that you will have any difficulty doing. So I know that sounds very dramatic, but honestly, it's the truth. So first of all, what I do, is I get a piece of paper and this got nothing to do with data visualization. This is more about how do I make someone listen to me? And um I write on top of the paper, why should they give a shit? I'm sorry for my language, but I'm going to use that word because it's very important. But I write that because it's about framing. It's not about you learning a new skill. It's about how you frame information. So if you start off the conversation as How do I make this person actually care about what I'm saying? Then you're oh probably heading in the right direction. So first of all, that's what I do. I write that and then I write, well, okay, how do I make them care about, um I don't know, um small cap equities? All right, how do I my mother care about small cap equities or smaller companies? She doesn't even know what smaller companies means. Okay, so maybe I need to explain why small companies are very valuable. Well, smaller companies, they are valuable because I don't know, they represent the real economy in the country that you live in. They're not some international multinational company that drives revenue outside of the country and probably doesn't generate many jobs inside your company. Maybe it does or maybe it doesn't. But it represents the real economy, which means that it's a real growth driver of jobs, which means that it impacts um all kinds of industries and and things in our own country and you know like i'm just running making things up as I go along here but this is the kind of thought process that you need to have so suddenly i've made it relevant to my mother because i've linked it to the country she lives in and then i can say smaller companies do things like um they are the types of companies that deliver essential services to you, like for instance, your dental care when you go to the dentist, that's an example of a small business or whatever, or they provide you with these types of services. So you understand where I'm going. first of all, the word I would use here is relevance, but you can say relevance, but how do you make something relevant? You make something relevant by making it emotional, interesting, and part of someone's life. And I think that's the skill. So you don't need to learn any special skills to be a visual thinker because you already are. It's in your genetics. You don't need to learn any special skills to tell a story because you're already doing that. In your daily life, you're telling stories all the time. When you meet your friends, you tell stories. You say, my kid did this and he did that. You're telling a story. So storytelling is something that comes easy to us as human beings. What you need to practice on is thinking about what people care about and what impacts them in their lives emotionally. And if you can do that, then they will listen to you and then your data visualizations will be ah interesting and people will follow them and like them and share them. If you just produce charts that you like, that interest you, and no one cares about, then it goes back to the story that I told you at the beginning of our conversation when I realized that no one was reading what I was writing because it was boring. You see? So it's more about framing the way that you tell a story um that matters rather than um developing um new supernatural skills that you already have. You're already a great storyteller. You're already a visual thinker. You can do data visualization. You just need to produce something that people care about. James, how is this gonna AI artificial intelligence change data visualization in the future? um It really depends how you look at it. you could say that um AI is uh our biggest enemy. AI spreads misinformation. AI can be used to create false narratives using data visualization. All of this is true. And these are very real dangers. However, AI can also be a powerful weapon to stop those things as well. um You can use AI to debunk conspiracy theories to analyze data to find the truth. And I think when you look at AI as a tool, as a powerful tool to help you understand the world and to fight against disinformation and misinformation, then perhaps AI can actually be one of our greatest allies in helping understand the world that we live in today. So yes, AI if misused can be dangerous, but it can also be very, very useful. You could use AI to help you discover those data stories that matter, to understand huge data sets that you yourself may not be able to physically and mentally and cognitively understand. You can use the AI to help you structure ideas and find the truth behind complex stories. So I would say that AI is actually a tool that can be a force for good in the world that we live and actually help make the world more understandable and clearer in our eyes. But it's really up to us on how we use it. I'm gonna throw to you five rapid fire questions, answering 30 seconds or less. Number one, what is the best free tool for beginners? Probably PlotSet. I would say that because I'm a co-founder of PlotSet. It's super easy to use. Just type in plotset.com and there's literally hundreds of templates that you can use to create uh interactive charts, animated charts, static charts, any kind of chart that you'd like to make. So that's what I would use personally. I do use it. So a lot of data visualizations that you see that I produce that go viral are made using PlotSet. Most overused chart type that needs to die. most overused chart type that needs to die. um Die is a very um extreme word. I wouldn't say you need to kill it, but I think pie charts are overused quite a lot. I'd say that racing bar charts on the animated side are used a little bit too much as well. um But I don't think they need to die. think context is important. um And often there are certain kind of like rankings in terms of where, know, there are certain rules that you should follow. when you're doing data visualization. But if you don't understand the rules, just think, is this chart clear? If it's not clear or it's confusing, and if there's a better way to visualize it, then use the better way to visualize it, even if it doesn't feel sexy. So I would never say that anything needs to die. I'd say that there's a time and a place for data visualization. And there's also a better way of explaining things. And if you don't know if there's a better way to explain things, ask your friend or your neighbor. if they can think of a better way to visualize something. What is the most versatile chart you recommend people to use? Static bar chart, hands down. And I know that sounds strange because uh I create these animated charts, but honestly, the easiest and most robust chart out there is a static bar chart. I don't know why. I mean, it's just a very, very good chart um ever since William Playfair developed it. I think back in the 1700s, it's probably the most robust former chart. I always find myself gravitating to a bar chart often when I've got a data visualization problem. think I'm thinking to myself, I'm not talking about racing bar charts. I'm talking about static standard bar charts, vertical bar charts. And the reason being is that it's just, they're just so easy to read. You look up the Y axis, you can see, you can measure the bars properly. It's easy to interpret and they just make logical sense when you see them. yeah, bar chart. static bar chart. And number five, what is a story you would love to visualize in the future? um I'm trying to do this now and I've done one already. So I visualized the circular effects of revenue in the tech industry. So like right now, it's very, very difficult to understand exactly what's going on in tech and whether or not the valuations we're applying to AI companies like Google or Meta or OpenAI are realistic. and I think that the, Microsoft rather say open AI. but I, and I think the problem that we have there is that there's just so many different variables. So at the moment I'm trying to understand it because a lot of the time what you're seeing is that these companies are kind of, um, they're, doing business with themselves. And so they're artificially to an extent driving up their revenue. And then that in effect pushes up their valuations. to those kind of trillion dollar heights that we're seeing now. And you wonder whether or not, um I wonder whether or not um a lot of this is being fueled by this kind of circular kind of recycling of revenue and also this kind of, uh and also the amount of money that's being invested into those companies because of the US dollar. US dollar is the reserve currency of the world that sucks in. a lot of investment into the United States, which goes into those growth sectors like technology. um And so I've started trying to visualize that. I did a data visualization of that last year. But even right now, I'm not completely satisfied with it. I'd love to continue that journey and really map that sector in an even clearer and more visual way in the future. Let's give some advice to our listeners. um If you could say to the audience, if they could take away just one thing from this conversation about visualization, how to be productive visualizing, how to use visuals correctly, what would it be? Always think about who you're presenting to. That's it. mean, that's why I said, like, I get a piece of paper and I write, why should they give a shit? And that was the life-changing event for me personally, when I realized that you need to care about what people feel. And I'll emphasize the word feel, because this is something that is often forgotten when it comes to data. Data is emotional. We treat it sometimes in a very sterile way and a very kind of like, well, it's either A or B, it's black or white, but it's not. Data makes people feel emotional. Charts make people feel emotional. Even data scientists get emotional when they see a badly produced chart. um And that's part of who we are as human beings. So never strip out the emotion from the content that you're producing. Always think about how people feel. So if you're producing a chart and you want someone to listen to um or not listen, you want someone to take in the data visualization that you've presented to them, then think about the emotion or the feeling that someone has when they view it and how that changes their life. can people get in touch with you and get to know your charts, your work, your services? Just type in James Eagle into Google. You'll find me on LinkedIn. I'm a top voice. I'm pretty easy to find. ah You can see my work. ah And if you want to do what I do, go to plotset.com. James Eagle, thank you so much for this very insightful conversation. Many golden nuggets to take out, many, many. I will need to listen to this two or three times to make sure I understand and I apply all of them. But I'm taking one particular thing away, which is your audience, who you are talking to, and the story is what make your visualization or your chart or whatever you do. efficient and effective. Thank you so much for being with us. Thank you very much.