 Hello, everyone. Welcome to this week's Product School webinar. Thanks for joining us today. Just in case you didn't know, Product School teaches product management, coding, data analytics, and digital marketing courses online and at our 15 campuses worldwide. On top of that, every week we offer some amazing local product management events and most online webinars, live streams, and ask me anything sessions. Head over to productschool.com after this webinar to check them out. Today we have an awesome guest presenting. I'd like to introduce you to Dave Mathias. Dave is the founder of Beyond the Data, where he helps customers be user focused and data fluent. Over the years, he has worked in various product roles in small to large companies with a consistent focus on data and analytic products. He believes that customer problems are solved through a mixture of people, process, data, and technology, and is a strong believer that advising clients mean you teach them how to finish, how to fish, and how to solve real high value problems. Feel free to leave any questions for Dave in the comments, and I'll be sure to ask him them at the end. And without further ado, let's welcome Dave. Thank you so much for joining us today. Thank you, Dan. And I am going to share my screen. Perfect. Okay, excellent. Okay, so welcome, everyone. Great to be here today and always enjoy talking about product and talking about data. So we're going to be mixing those two today with using data visualization from product people or for product people. And so there might be a little noise in the background just to let you know, but we'll try to keep that down as much as possible. So what's the agenda today? Well, we're going to talk about data visualization, how it plays a role in product and how. And what are the ABCs of effective data visualization? Where to start and how to continue learning. But before we start, successful data is more than just charts and graphs, because that's what people oftentimes think about. But really data is just one component of a number of things. Of course, user experience is vital nowadays and more and more emphasis is put there. But things like gamification and behavioral science and more come into play when you're actually thinking about data visualization, how it's going to benefit, whether it's your end users in your product or whether it's even how you're relaying information to sales or to other areas. So where does data visualization play a role in product and how? Well, there's a number of places and these are just a few that we're going to talk about is communicating with executives. Of course, that's oftentimes, you know, using charts and graphs. It's great to help executives understand the material you're trying to put out. Enabling sales is of course another component. Understanding marketing is critical. Understanding your customers, of course, because that's one of the core things as a product manager. And of course, even integrating within your product itself. And here's an example of that and some of the stuff they've done with data visualization. So types of data visualization, though, because people oftentimes think of one, but not the other. So exploratory is the one that people often don't think about. So you have data and you want to understand what that data looks like. Well, use exploratory data visualization to help yourself understand what that data looks like. And then of course, there's the storytelling aspect that we're all used to when we talk about data visualization. So let's go through some of the ABCs for effective data visualization. And this is not an exhaustive list, but I think these are the key things that if you nail these things right, you're going to be well off. So first thing, it's got to start here. There's a reason why it's at the front is, what's the value to the user? So asking yourself all the time, what is that value to the end user, whether you're including it in the report, data base, or whether you're going to be putting in your product all too often, things are just put there because you need to check the box and know, think about how data visualization is used, what's that value. Of course, understand your audience. So empathize with the audience, ask the questions, who, what, when, where, and how. So those questions, who is your audience? What do they want to understand using data visualization? When are they going to access your data viz? When are they going to? Actually, I repeated that one. Where are they going to access your data viz? I did not repeat that. And how are they going to use your data viz? So asking yourself those things and really understanding those users. And reality is, is you may have one different user type, right, that's accessing that information, whether it's an infographic or whether it's in your product. But one thing to really keep in mind all the time is keep it simple. Bar charts, line charts, scatter pods, you know, they sometimes seem boring, but done well. That's really the way people are going to understand how to interpret your visualization. And they're going to get the most bang for your buck. Because that's what you're there for. You're trying to relay information to help them, you know, change behavior or understand some action or something. But if you try to make a fancy data viz that people have a hard time understanding, it doesn't matter. So things like, like I say, a line chart when, especially when you have continuous data like this, like dates, you'd want to use. On the other hand, scatter pods are great, you know, can relay a lot of information, but the bar charts and others that are standard things to avoid, though, those, those word charts, I mean, they're, they're, they're nice to show a little, they're fancy and all that. And certain, certain areas yesterday, those certainly stay away from 3D, stay away from complicated pie charts, things like that. And there's a whole bunch of other things that are bad charts. So just keep it simple. Another thing that often comes into play is color and really thinking about how you're using color for a number of reasons. One is you know, graded color is great when it's continuous. But remember humans are not able to absorb an unlimited amount of gradations and really process the data. So think of that 5, 8, 5, 10 scale of how many gradations you're going to make and go accordingly. On the other hand, you may have data that's called categorical data. For example, states or, you know, models of cars. And that categorical data, you're going to want to use very colors when you have that. The other thing, of course, to always be aware of, though, is bad use of color. Be aware, you know, accessibility is so important nowadays. So what kind of colors do people typically have colorblind? You know, certainly the red, green, the blues are two of the most popular with the colorblind. But in another way to, you know, account for that, even if you want to use red, green, is you can use shapes, size, textures and other ways to help differentiate between the colors in a different way. So you have the two colors that you can be using lines that go across the green to help differentiate for the person that's colorblind, for example. So any good product manager, you should be empathetic. So that's no different than in data is if you're a product manager. So use a little text to provide context. This is one of the things I think I see most underused is when you have a graphic, whether it's in your product or whether it's infographic or whether it's sent in an email, provide that text to go with it. What's that takeaway that you want out of that charter graph? And also make sure to label, label, label, label things, the titles, your accesses, etc. And think about text size and font because not everyone has the same eyes as you. Really understanding this goes back to the empathizing with your audience and really knowing who your audience is. If people are going to have a harder time, make the font a little bit larger. Data-vis experience. So just a user experience, there's data-vis experience that you're going to have. So what's that experience like that that user is going to apply? And there's some different ways that this could happen that we'll be touching on. Just as a reminder, don't do too much. So just try and throw that out there. Once again, this goes along with being simple. But so we talked about different audiences. One of the things you'll notice, and like Fitbit is a great example, I think of a company that does a great job in their application with Data-vis, especially even hitting on this novice nerd concept. So sometimes you're going to have people that are very novice to your data or novice to data visualization. And you'll keep it very simplified for those users. On the other hand, you're also going to have the more complex, they meet with somebody that's regularly using data or they're really wanting to nerd out on that data that they're getting out of their Fitbit or out of whatever product or whatever dashboard you're showing them. And now those super nerds, sometimes you're going to have to play to both of those and understanding how to integrate into Data-vis, how you can play to both of those is something that takes a little time to do, but when done well, it's very beneficial. The other thing to think about is exploring versus informing. So when I say explore, you think of the New York Times and some of the stuff they do with their Data-vis. If you've ever, if you haven't looked at that, you should look at that. They do some great stories, really complicated Data-vis. It's really an exploration that you're going to go through. On the other hand, sometimes, especially like when you're going to communicate something to your executives, you just want to have a quick amount of information. You have your KPIs, you might have a simple bar chart. You have some really simple things that you're going to let them take a few seconds, process the information, and then be able to act. So really understanding who that audience is once again. Are you wanting that audience to explore? Are you wanting to inform? Are you wanting both? And then how do you make sure that the right user gets to the right channel is important? The other thing is what Data-vis is a great way to experiment more than a lot of things. You can really do a lot of great experimentation in Data-vis and see how it works. So it's one of those things put out there, especially if you're talking about putting in a product. But even if you're like using it into like say communications to your sales team, test things out, see how it goes, you know, typical A-B testing and see what works best. But one thing that often happens is people put these Data-vis or they put a dashboard and they put something out there and it just stays out there. They don't know if it's being used. They don't know what's well like, what's not like. They just sort of throw it out of the world. So you really got to think about getting input, tracking usage, and then iterating all of that. Because if you're not doing those three things, then you really are wasting your time and your user's time most likely. So when you're talking about this, where's a good way to start? Now, it sort of depends on what you're looking to do. Certainly you might be just starting out and you're going to, you know, you're a new product manager and you're just getting a Data-visualization. Well, maybe you want to start using an A-communication or report that you normally provide. So maybe it's a report with a lot of words and a lot of tables and now you're going to, you know, try to incorporate some Data-visualization. That's a good place for you to start practicing with things. Design some Data-vis that would help you better communicate with that audience. So really understanding if it's sales, you know, what they're after, how do you, you know, adapt some of those concepts of Data-visualization that you take your existing communication or report. And then make sure to, like I say, get that input from those folks, you know, test it out, see what they say, and then integrate that Data-visualization communication or report in this case. But of course, we can be doing the same thing when we're talking about incorporating in a product. And then of course, like I said, the last stage is always test, iterate and repeat. Just like anything else, you want to, you know, it's never going to be perfect, but you always want to be looking at trying to make it better. So those are just the ways to start with a communication or report. But like I say, you can take the same steps and you can integrate those steps into a putting it in your new, putting a dashboard, for example, in your app. But once again, you're going to have to think about, you know, if you have an app that's desktop version and mobile version, you know, how does that relay that information to those mobile users versus those desktop users? And then really assessing, you know, does this, you know, help benefit the user? Is there that value like we talked about in the beginning? Or whether it's something that users really don't do without. And maybe if there's a few minutes, it might go through some couple of examples of things that are out there. So knowing that we're short on time, I do want to make sure to put some things to continue learning. And then maybe we'll go into a couple of examples before we take questions. So some online learning that's out there, you know, there's tons of great YouTube videos, there's this thing called Makeover Monday. It's done, you'll often see it in the Tableau format. There's what's called Tableau Public. And Tableau is just a data visualization tool. It's just one of many tools that are out there. But there's this thing that called Monday Makeover. It's done out of the UK. They basically publish data. It comes out on Sunday. The whole idea is to put together a data visualization based off that data roughly in an hour and publish it out there. And so it's one of those, it's been going on for years and it's a great way to practice your skills. And also you have access to different types of data so you can get better at both doing it yourself, but also seeing what other people did with that same data. Another site that's great is Information. It's beautiful, but like I said, New York Times, a bunch of other things online. Also in person, you know, there's tons of things like there's a ton of DataViz meetups out there that are, you know, specific in cities. I know in the Twin Cities we have those with Chicago and San Francisco and Seattle and all these cities have these DataViz meetups that are there. But if you're in a city that doesn't have one, well then create one. Get people together that are interested in DataViz and, you know, you'll learn better and you'll also be helping the community. So some great books that are out there. The Big Book of Dashboards. It's a great dashboard book, Storytelling with Data from Colin Nossbaum. It's a great book out there. And then of course, there's one that's more recent called Data Visualization Made Simple. I interviewed our author, she's out of New York. And it's really, I think, pretty exhaustive book on Data Visualization. I was really impressed with it myself. So another good book to take a look at. There's another podcast out there. But I'm going to list two, Storytelling with Data. So that's Colin Nossbaum who did the book up above. But she also has a podcast called Storytelling with Data also. Great one. And then I'm going to put a plug out there, Sheamus Plug for the podcast that my business partner and I do call DataAble because we focus on everything that's the non-technical side of data. So DataViz included. And so that little Sheamus Plug. But let's take a few minutes and dive into a couple examples. So before going into the thank you and all that, have a few examples here. So this is Fitbit. So Fitbit has, like say, a great app that's out there. They have a lot of, and this is just one example of DataViz. This is sort of their dashboard on mobile. And they do a great job of using color. They do a great job of varying of text. So you can see here, okay, most important thing for me is how many steps I'm walking. So I have that as a primary thing. It's biggest. It's easy to tell. It's green because I hit the goal for the day. Same with these other things. Then there's other things when I scroll down here. There's a curious how much sleep for a night. Yeah, bad night of sleep. What's your current heart rate? And then of course, when you finish of these things, this is where I say, you know, you're going from novice to expert, you click on these things, you're going to get more depth. And that's really, you know, this is a great novice because I can quickly identify information that's out there. But then I can dive in deeper and really understand, okay, on my sleep, for example, okay, I slept this long. What are the different levels of REM sleep that I have? What was the average throughout the week? What's my last week versus this week look like? Things like that. So you can really get into nerd out if you're looking to nerd out with that data. So like I say, here's some good on this easy to calculate, simple color icons, etc. Some, an opportunity here, I think for them to make it better is the top card when you switch from the, you see those arrows at the top, that's switching days. But when you switch days above, it doesn't switch days below with like sleep and heart rate and all those things. So I think that's an opportunity that they could do to better create a better user experience. Here's an example of one that I don't think is so great. And sorry, audible, but I'm a big fan of audible. But at the same time, I think they do a really bad job with their data visualization from an obscene Android app. And so this is a few months ago, I took this picture. It's one of the several data visualizations that are there. It's an example of really a dog like why do I care about like how many books that I have right now in my library on the 77 books? Okay. And it's pretty much a straight line. And I imagine most people on audible have that similar straight line. So is it going to really change my behavior? Does it give me information that I really need to know? Do I really need that table to understand that? No, I don't think anyone. So yeah, it's clean and easy to understand, but it really doesn't provide much value. Like we're talking about that first thing doesn't encourage me to really buy more books. I don't see anything. I don't see anything that says, Hey, you're buying less than the average user. You're consuming less. It doesn't talk about, like, Oh, okay, there's there is a listening time one to the left. You'll see, but the listening time is simple numbers. There isn't really any straight visualization, other than just reporting out your numbers. So does this make me feel better about myself? Does this help my more of my behavior at all? Once again, all those questions, I think I know at least for me, you may feel different. But because of that, I just think they could do a better job with their database. So I'm going to show one more example, because I think it's a good example of another thing outside of a typical product. And so this is a company in actually Minnesota, where I'm actually from. It's called a sleep number. They do these nice beds. They have this whole select or this number that they say, Hey, you sleep at this number, your partner maybe sleeps at a different number, you can each rest more comfortably. But this is showing an in-store demo that they have. And it's a great example of data visualization used. It's a way to empower a retail salesperson. And you could see, of course, like overly happy customers, probably not as happy to realize. But they're looking at it. It's pretty easy to understand. They see their body. They see the pressure points where it's at. You also see where it's got a single score where it comes down to it's got both, you know, both on one on each side. So once again, it's a great example, a great tool to say, Okay, use data visualization, not just in a mobile app, if you've been using a product, but maybe you're using it to empower sales to better do their job, which is what's happening in this case. So like I say, this is a great example for a number reasons. I'm not sure if they actually do this or not. But of course, another great opportunity would be to say, Hey, here's a printout of your sleep number and where, you know, where your pressure was and all that. And here's a coupon or some kind of a thing that I'm going to give with it to take with you in case they're not buying right away in the store. So that is what I was going to cover now. And I wanted to leave time for questions because I know we only have 30 minutes in total. So before I open it up for questions, Dan has any, but here's some ways to get ahold of me. So a number of things on Twitter, on LinkedIn, whatever, like reach out to me, check out the podcast data able, love to get your feedback. We're probably maybe 14 or 15 episodes in private tapes, another 10 or so. So we're still relatively new to this podcast game ourselves. So love to get input and how would you make that better? Because the product manager audience is certainly one of those audiences that we think is beneficial for this. So that's all I have right now, Dan, if there's any questions. Awesome. Thank you so much for that presentation. So I'm only seeing one question here now. Let's see if people post them now while I ask you this next one. So one question we always ask all of our speakers is, do you have any advice for aspiring product managers, a piece of wisdom, a quote or anything you feel like would help them excel? Yeah, that's a great question. So I think there's a lot of words for advice, but I think the biggest word of advice is to say yes to things when you're young in your career, but quickly learn how to say no. You're going to have to say yes because you're going to want to learn, you want to take in a lot, but then being able to say no and really focus on the things that are going to make impact on your product are really important for product managers as they're evolving from that early stage product manager to a more tenured product manager and successful. Awesome. Thank you for that advice. So we have one question here, which are the best tools for someone starting with data viz? So I think you mentioned a couple books and podcasts and other good things, but do you have a favorite or a best one for someone starting off? Yeah, so there's a few that I'm going to list because I don't like to pick favorites, but I think there's several that are out there that are really good. So Certainly Tablo has a public version, which I think is a really good way to get involved with data visualization. It's a very strong community that's out there online too, so especially even if you're an area that doesn't have a very engaged database community, you can still get involved with the online community there. There's also Power VI, which is from Microsoft, has really been upping their game a lot, and their free version is probably the best free version of any of the platform products that are out there. So it's a great thing. You can just download a lot of horsepower. It's really good for not just visualizing data, but also editing data. So one of the things that when you get data, a big part of it is preparing data to be in a form that's ready to visualize. It has a lot of good horsepower. Power VI does to do that. Tablo has a version of that, like they call it Tablo Prep, but it's a fairly pricey product to get. But then there's other products out there like Click and Domo and others that are out there that are great products. But I tell most people is like, find out what products if your organization has one, because that's one you really should try to understand from a product perspective. But if you don't have any in your organization, you're looking to just try to bring something on. To be honest, right now I'm telling people to say, Power VI is something you can bring in there. It's free to try out. You can do some stuff. And maybe you want to switch to Tablo or switch to one of these other things if you go broader, because you could really do a lot of these things with whichever product that's out there. But Power VI is just a good one because it's free nature and the horsepower that it offers you to start out with. Awesome. Thank you for that. So I think that's it. We don't have any other questions here in the comments. So before we wrap it up, I wanted to give all of our listeners some more information about our upcoming courses and events. Product school offers, product management, coding, data analytics, and digital marketing courses at our 15 campuses around the US, UK, and Canada. If you're located near campus, make sure you stop by one of our weekly events every Wednesday and Thursday. Also, you can find us on social media at product school and be sure to keep up with the latest product management content at the product blog at productschool.com. You can also find a recording of this webinar on our YouTube channel, Product School San Francisco. And that's it. So thank you all for joining. Enjoy the rest of your day. And I hope to see you next week. Thank you so much for your presentation. Thank you. I look forward to anyone reaching out. Have a great day.