In this week’s In-Ear Insights, Katie and Chris discuss how marketers and business folks should approach data visualization, reports, and dashboards. What are some of the best – and worse – practices in data viz? You’ll also learn the secret of great data visualization: user stories. Tune in to find out how!
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Machine-Generated Transcript
What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.
Christopher Penn 0:17
In this week’s in your insights, we’re talking data visualization, sort of the basics of what you need to know and how to think about data visualizations.
Okay? When you think about data visualization, particularly how to make choices about how you’re visualizing data, how do you think about it?
Katie Robbert 0:38
I usually think about the lowest common denominator.
And what I mean by that is the person who has the least amount of context with the report that I’m about to give them or with the data that I’m about to give them.
And can they understand the story within, you know, five or 10 seconds? Or does it need more explanation? And so when I’m starting to put together any kind of visualization, that’s the thing that I have, you know, running through my head of like, is this understandable? You know, if I put together a pie chart, is some going to understand the data point that I’m trying to convey? Or would it be more understandable as a bar chart, and obviously, there’s different applications for those different visuals.
But really, the goal is to make sure that you can communicate the point very quickly with the visualization.
And so that’s how I approach it.
I always think, can I understand this? Or can someone who isn’t me understand this within 10 seconds? If not, I keep going back and keep going back?
Christopher Penn 1:45
Gotcha.
I really like so Dr. Andrew Abella came up with this almost a flowchart a number of years ago, I think, like 2009, was when he made this chart.
And it’s a really, really handy flow chart.
Let’s go ahead and bring it up here.
Essentially, you start in the middle, and you asked, What would you like to show this four types of visualizations, right, this comparison, where you’re comparing stuff like one thing to another thing? There’s distribution, which is looking at sort of the statistical layout of your data, there’s composition, which is a fancy way of saying what’s in the box, right? And then there’s a relationship? How do variables relate to each other, which is different than comparison? And based on that you then kind of work through and say, am I looking at things over time looking at among things? Am I looking at a single variable, multiple variables, and we’re looking at static, or dynamic compositions, and so on, and so forth? And I think this is a really, this is one of the charts I rely on when I’m trying to figure out like, what is it that I’m trying to do with this, this series of data? Looking at, for example, like SEO data? For inbound links, let’s use that example.
What am I trying to show? Well, some most of the time, for example, I’m trying to look at a distribution like of incoming links, what are the ones that are have a lot of PageRank? What other ones have less PageRank? What does that distribution look like? To your point, when you’re looking at a pie chart, it’s a composition.
So answering, like, what’s in the box, like how many, what percentage of our site visitors are into sports versus movies, and so on, and so forth.
So I think having a guideline, a set of guidelines like this, like a flowchart is probably one of the things that is most helpful to people and annoying.
It’s one of the things that people just don’t teach you in school.
Katie Robbert 3:36
They don’t I mean, I, having been in, you know, different jobs, you know, and seeing a lot of reporting, I think that pie charts are overused and probably overused incorrectly.
And a lot of times, you know, so you have here the quick question, and then what would you like to show? The thing that doesn’t happen before that is? What’s the point? What’s the purpose? What’s the question you’re trying to answer? And so, you know, apologies, but not you can’t get away from doing that kind of planning, you still have to know, what’s the question you’re trying to answer.
And so Chris, you you brought up, you know, SEO backlinks.
And so it’s great that you want to show a distribution, but what’s the question you’re trying to answer when you’re saying I want to show SEO backlinks? Is it that we’ve lost traffic? Is it that we are gaining backlinks is, uh, you know, something else entirely.
And so starting there, then you can get into well, what do I want it to look like? You know, I think that one of the challenges with data visualization is cramming too much onto one screen.
And then, you know, to your point using the wrong type of visualization, so you’re not really getting the story across
Christopher Penn 4:58
and that is the most important word of all of this to story.
When you’re setting out that purpose, one of the things that will make data visualization and reporting much easier is having written down user stories to say, this reports purpose is to communicate inbound link distribution to a marketing manager so that they can choose which sites they want to pitch for inbound links, right? Suddenly, that clears up a lot of stuff, because no longer once you understand that, then you go, I know it’s a distribution thing.
And so now I need to plot a distribution, I’ve got a lot of data points, I’m going to choose a histogram.
And I’m going to slice off that top 10%.
And that’s the those are the sites that I want to go after to pitch for inbound links.
But without that user story, you You’re right, you can get lost Whoa, okay, well, do I want a relationship? Do I want to compare, you know, domain authority with traffic and stuff like that? And that’s not the question.
The question is, what should I be pitching?
Katie Robbert 6:03
Do you feel like so we know that the whole purpose of you know, the chart sometimes gets lost? Do you feel like people get too wrapped up in the making the visuals like aesthetically pleasing, versus actually conveying the story? You know, so we’ve worked with other consulting agencies, and, you know, the first thing that we remark at is, wow, that’s a really nice and boss, you know, thing and a drop shadow.
And you know, all of those things, but it still doesn’t tell me anything like, I guess so you’ve you’ve actually taught about, you know, data visualization, you’ve taught sessions at events about it? Why do you think people get so wrapped up in the actual aesthetics of it versus the purpose, the point that the data itself?
Christopher Penn 6:53
Well, do you want the honest answer or the politically correct answer?
Katie Robbert 6:57
You know, I’m always after the honest answer, but make it PG because this is a family show.
Christopher Penn 7:03
I like to meet the family that watches this for entertaining.
The honest answer is, the more time you spend us that x means the less time you are capable of thinking about what the data is communicating, right? It means you don’t know what you’re doing.
If you’re spending all your time making it look amazing.
There’s a, I would say, there’s a sweet spot, right? There’s Wow, you do that on a napkin.
There is why you spent 100 grand on a designer, and then there’s a wide range in the middle.
And the reality is, you should spend 80% of your time, maybe 90% of your time, figure out does this communicate what I want to communicate and then spend 10%? Yeah, make it look like not horrible, but even still, if you draw a half assed chart on a whiteboard, but it communicates the point that you want to make and get the decision made.
The chart did its job, right.
That’s the data visualization did its job.
And the more time you obsess on the look, the less time you’re spending on the substance is answering the question.
I remember, we were working with one client, and they had another agency come in, and that made this dashboard.
They try to make it look like the interior dashboard of an automobile with like wood paneling and stuff like that, and speedometers and graphs.
And here’s here’s a pro tip.
And this comes from our friend and colleague, Avinash Kaushik, if you see a speedometer dial on a dashboard, you immediately know the dashboard was made by an idiot.
Because that is never, ever a useful measure a measure of progress.
If you’ve got to measure progress, you use a bar chart.
So if you see speedometers and dials, you know, the person the Dash was made by somebody who doesn’t know what they’re doing when it comes to data visualization.
So that would be my answers the after minimally, inoffensive graphics.
I would want I would rather someone spend all their time figuring out how does this communicate the point I need to make and how does this make the decisions I need to make? Not does this look awesome?
Katie Robbert 9:16
But it’s so fun to look at.
It’s a spit ometer it’s interactive?
Christopher Penn 9:23
Yes, it’s and there is something to be said for aesthetics.
But it’s kind of like it’s difference between Well, no, that’s that’s a family show.
It’s the difference between like a Toyota Prius, right decent car gets the job done.
Versus like a Lamborghini.
Right? You spent all your money on the appearance and for the purposes of getting to the grocery store.
A Prius is not worse than a Lamborghini.
Like you can’t go 144 miles an hour to the grocery store.
You shouldn’t probably unless you’re you’re like you live out in the desert in the grocery stores.
100 Miles And it’s flat roads and nothing around and no police.
Functionally, the priests will get you to the store in the same amount of time will cost you less money on gas, and fulfills the objective of getting the thing done.
A chart that is a simple bar chart with minimal adornment has a clear legend shows where the data source came from, has clear labeling, and is just black and white is perfectly fine.
As opposed to one that, like you said, is embossed and has all these things and and you know, 14 fonts and stuff spent spend your time on the analysis? Spend your time on? What does the three was? What happened? So what? Now what?
Katie Robbert 10:49
You know, it’s interesting, because I’m thinking back to all of the quote unquote, slick presentations that I’ve seen in over the course of my career.
And you know, how many times like bosses have given me back reports and say, you know, you need to make this look even nicer.
This is going to the board.
And I think you just sort of like, crack the case on why that is, it’s because you know, the data is useless, or the data doesn’t tell the story that it was supposed to tell.
So let’s distract everyone with the pretty pretty colors.
Christopher Penn 11:22
Do you remember? I’m sure you saw my face? Do you remember what one of our former colleagues said about one of our analyses? I was
Katie Robbert 11:30
I was going to say that, but I was also afraid to poke the bear.
You know, and the quote is, you know, it doesn’t look expensive enough.
And, you know, thinking back on that situation, like we knew right there, and then that the person who had said that clearly didn’t understand the data itself, and therefore want to hide behind all the bells and whistles, and say, Look how pretty and attractive and eye catching this thing is, versus let me explain the utility of this report and how it’s valuable to you the client.
And so that’s exactly the trap that people get into is okay, if I don’t know what the thing does, let me just like smile.
And you know, put on a nice outfit so that I can distract people from the fact that I have no idea what I’m doing.
Christopher Penn 12:18
Exactly.
Now, to play devil’s advocate for friends who are really good designers, stuff like that.
There is absolutely value in making something look clean and clear and easy to understand.
But it is not about adding adornments a lot of the times with data visualization, it’s about taking things away.
It’s kind of like the old quote about Michelangelo, you know, how do you make the statue I chipped away everything that wasn’t David, in this block of marble.
The same thing is true for data visualization.
Can you take more away, because one of the things that and again, this is another wonderful truism from our friend, often the higher up in an organization you go, the less data you show.
And the more explanation and analysis and recommendation you make.
You don’t need 44 widgets on the dashboard.
Right? If you have 44 KPIs, you have no KPIs, you have no understanding of what a KPI is, you have one or two at most three KPIs, what are the 123 numbers that you’re going to get fired for? That’s what goes on any data visualization.
And then you spend all your time saying, Here’s what we know about this, here’s why these things happen.
And then here’s what we’re doing to either make the problem go away, or make the results even better.
Katie Robbert 13:39
You know, it’s interesting, because it sounds like the less is more mentality.
It transcends industries, it transcends a lot of things.
And so there’s the famous Coco Chanel quote of you know, before you leave the house, look in the mirror and take off one piece of jewelry.
And the whole point of that is because we have a tendency at the last minute to like, Okay, did I do enough? Do I need this thing? Did I do I need this thing.
And the point of the quote is, you know, you’ve probably overdone it.
So start editing yourself, start taking off, like, the extra bracelet that you put on, take out the extra chart that you threw in because does it add any value to the story.
And this is why having peer reviews is also a really good idea for all of your reports and visualizations.
And so, you know, Chris and I, when we’re putting things together, whether it be for clients or for, you know, events, those kinds of things we always give the other person Hey, I put this together.
What do you think, you know, without really giving too much context, because the point is like, Chris, give something to me to see if I can figure out what the story is.
And vice versa.
I’ll give something to him and he’ll say it’s good but it’s missing XYZ thing.
Because you yourself, you’re going to be to you know, focus with blinders on to really see the way that other people are going to see it.
And so having that trusted peer that you can, you know, get feedback from is really going to help strengthen your ability to tell that story of division with visualization, because I remember from last time, oh, okay, I remember when Chris told me, if I do this, then it clusters up, you know, it confuses the story, you know, so therefore, let me try it without it and see if it’s stronger this time around.
Christopher Penn 15:27
One of the things I really like about that Coco Chanel quote that is implicit, or does not spelled out is that it is reliant on confidence, right, that you have confidence in yourself, if you are putting together a report or a data visualization or an analysis, and you feel like you need to add more stuff, what it reflects is that you don’t have confidence in what you’ve put together, which means that you shouldn’t ship that report.
Right? I mean, obviously, if you have a deadline, you have a deadline to me.
But it means that you don’t understand the underlying data enough to know okay, I can just put up this one graph.
And any questions somebody asks me about that I can answer those questions.
I don’t need to put it in the report.
You know, somebody says, Well, why did this go up here this time period? Oh, that was this? Why is it down year over year? That was because of a pandemic, you know, why is, you know, your data, if you understand your data deeply, then you can put a minimal amount of visualization in and still answer any question that’s thrown at you, but you that confidence comes from knowing your data.
Mm hmm.
Katie Robbert 16:30
I think that that’s a really good point.
Because you know, back to, you know, adding more charts, more graphs, more embossing more, you know, little animations, it really is just a distraction.
Because is it pushing the story forward? If I have a drop shadow on my bar chart or not? No, it’s not.
Yeah, it looks cool.
But it might not be answering question.
And again, this is not a knock at people who are really good at designing, but most analysts are not also designers.
You know, it’s that sort of blanket statement is not true of everyone.
But most of us, we can do one or the other.
And we need to sort of focus on do we need the data to be correct? Or do we want it to look really slick and pretty? Or can we get all the data correct, and then partner with someone who can then make it look a little bit nicer.
So you know, we have, you know, our trusted creative director that we work with, and he will look at something and go, Okay, I know how to better represent that.
But the data itself stays intact, the integrity of the report hasn’t changed.
He then is the person who then goes through with that creative, I have to say, let me just rearrange this a little bit and give you a template moving forward, to make it look a little bit better.
Christopher Penn 17:51
Exactly.
Yeah, having things like style guides and stuff.
And templates is definitely a way to ensure consistency.
But also, you know, having a professional designer, like our friend, Pete Bueller, look at something and say, here’s what I think you’re trying to communicate, right? And then you work with that person to say, Okay, well, that’s actually not what I was trying to communicate.
So it’s clearly that you didn’t understand the date or the question being asked, as a refresher, Katie, what goes into a user story?
Katie Robbert 18:21
So a user story is a simple sentence with three parts.
So as a persona, that’s the person who needs the question answered, as a persona, I want to, that’s the intention.
So that, and then you say the outcome.
So as a CEO, that’s me, I want to understand how many backlinks we’re getting from our content, that’s the sowhat.
So that the outcome is that I can take action on it, whether it be increasing the number of guest posts we’re doing or decrease, because it’s, you know, a bunch of junk.
And so the user story, you know, it’s interesting, because we were talking with someone last week, who misunderstood what a user story was meant to do.
So this person started talking Well, we have, you know, a dozen or so different buying personas.
And I had to clarify, no, the dashboards are not meant to reflect the people buying the dashboards are meant to reflect the people making decisions.
And so the user stories are for decision makers.
Now, that may be customers at some point.
And so as a customer, I want to understand the price of this product so that I can make a decision to buy it.
That’s a completely acceptable user story.
It stands alone and it stands separate from as Chris Penn, I need to set the price of the product so that my customers know what they’re buying, and how much they’re paying for it.
Those are two different user stories and therefore those would be two different actions to different dashboards.
Christopher Penn 20:03
And I think that’s a really important point at the end there is that not only does a dashboard have a user story, you know, but with any data visualization, any data visualization, including a single chart on a dashboard, probably should have a user story behind it so that you’re clear what it is to try and communicate with this chart.
And if you can’t come up with a user story, for a visualization, it’s probably time to remove it because it doesn’t serve a purpose.
Katie Robbert 20:28
That’s exactly right.
And so I think, what is it that you say, Chris, data without decision is a distraction.
And so if you have data that you can’t make a decision from, then it doesn’t belong up front, it doesn’t belong front and center, you know, maybe you have, you know, secondary or tertiary sets of dashboards that are like, just nice to know, like, how many Twitter followers do we have? Are we going to make a decision with it? Probably not.
For us, per us personally, but is it nice to know, sure.
It doesn’t belong up front where I need to just sort of like, look at something and make a decision about it.
And so that also sort of helps you structure and organize your visualizations in terms of priority, what’s the most important, and it’s completely acceptable, once you have those user stories, to use that as the anchor for every dashboard, so put the user story up on the dashboard, so that it’s very clear, as part of the story, what decision you’re meant to be making with this dashboard.
So as a CEO, I want to understand the growth or decline of the number of backlinks so that I can, you know, take x actions, stick that right at the top of your dashboard, and then have the corresponding chart and it’s okay, it’s very clear and simple, I can still understand all of that within about 10 seconds.
Christopher Penn 21:49
Exactly.
The other thing I’d say is that with dashboards, with presentations, reporting any kind of data visualization, it is perfectly okay for there to be words on it, including possibly like entire paragraphs, because again, the goal is not to just dump everything that you know, the goal is to help somebody make a decision.
So rather than saying, Well, I have this chart of say inbound links, but you know, it doesn’t tell the story, I want to tell someone to add four more charts that maybe will will suggest like no, if the one chart tells the relevant data, and you need to spend some time explaining it, and you know, maybe you’re not presenting in person, it is okay to have a couple of sentences next to the chart saying, Here’s what this is, here’s why it’s happened, here’s what we’re doing about it.
And for the decision maker, that’s going to be a lot more useful.
Three more charts that they then have to spend time thinking about.
It’s it’s somewhat condescending to often say that, you know, people are idiots, but people are pressed for time.
So if you if the one chart is really all that’s needed, and then you need to explain with it, then just make the explanation right, save somebody, the time having to ask you the questions.
You know, what the user story is, you should you know, what the chart says, and you know, what the two or three questions they’re gonna ask next, which is why and what are you gonna do about it? If you do all that, then that one chart suffices, and you don’t need add more stuff.
Katie Robbert 23:15
And I think that that’s a really important point as well is anticipating the questions and answering them proactively.
You know, and so if you have the user story, then you know what questions are going to be asked? And so getting ahead of that, and putting, you know, on the chart on the report, you know, in the video walkthrough, here’s the user story, here’s the data.
And then here’s all the questions that you’re likely going to ask about it.
Let me go ahead and answer them for you.
You’re saving people so much time, and you’re demonstrating your ability to pull out those insights and do critical thinking.
It’s a win all around, it’s sort of a 360 win.
Christopher Penn 23:54
Exactly.
One of the things that our friend and colleague Tamsin Webster says is the fastest way to build rapport and impress someone is to artfully restate the problem that they’re having, right? If you have the user story down, then when you go to present that when you go to explain that, that is essentially the problem that you say that you’re trying to solve.
Now, if the person disagrees, then you know that you got to revisit your user story.
And at that point, you can say, Okay, let’s stop this presentation, because it’s not gonna add any value.
Let’s refine the user story, and then we’ll come back to you with improved visualization that actually answers the question you have.
Katie Robbert 24:29
Yeah, it’s an it’s a really good solid technique for making sure that you are understanding the assignment and so Chris, if you say to me, you know, we have a backlink problem, then I can take the opportunity to say so it sounds like Chris, you as the person responsible for you know, pitching out our content, want to understand, you know, how many backlinks we’re getting, so that you can do something about it.
So I have just restated, you know, your declaration as a Using a story and you can say, Yeah, that’s exactly it.
Okay, great.
Now I have a direction to go in.
And now I can start to put that report and that visualization together with the data to say, Okay, this answers the question, here are some suggestions about what we can do about it.
And you’re like, Oh, my God, great, Katie, you just saved me so much time.
Here’s 80,000 more dollars a year.
Big promotion?
Christopher Penn 25:21
What?
Unknown Speaker 25:24
No, okay.
Christopher Penn 25:25
One of the you’re the CEO.
Yes, your decision, not mine.
Good point.
Well, one of the things that I know that, like we get feedback on from clients is, you know, we can build dashboards, like, literally in the middle of the meeting, they’ll say, I need to see this, and stuff like that.
And you know, we put it together and like, Oh, my God is magic.
And it’s not magic.
What we’re doing, you know, this is sort of giving away the secrets is we’re asking the person for the user story, right in the meeting.
And then once we have the user story, it’s just because we know the user story, we don’t need five charts on the dashboard, right? We know the one chart is going to answer the question that they have the user story, if they have supplementary questions, we can add stuff.
But the reason why we can build dashboards in real time for people is not because we’re especially good at, you know, graphic design thinks it’s because we’ve gotten the user story part down.
Katie Robbert 26:16
I wholeheartedly agree with that.
And I feel like it’s fine that we’re giving away that, you know, quote, unquote, secret pro tip, because you are very good at manipulating the data very quickly.
Because you, Chris, as the data scientists understand the data so well, that you know exactly what data points to go after.
And that’s also part of, you know, building that rapport with clients is understanding their data better than they do.
So that even as they’re starting to state the user story, your brain is already four steps ahead of you, like I know, they’re going to ask for this particular thing.
Let me start pulling it in and answer the question as they’re finishing their sentence.
Christopher Penn 27:00
Exactly.
So to wrap up, get good at user stories, because when it comes to data visualization, if you know the use of story, building, the data visualization is straightforward, maybe not easy, but it is straightforward.
You need less data visualization than you think you really only have to answer the questions being asked of you.
And if the person isn’t clear about the questions they want to ask, then it doesn’t matter how much data visualization you do, because it’s never going to satisfy their needs until they’re clear what they need.
And the more time you spend on putting it up is the less time you’re spending on analysis and analysis.
And insight is where the value is.
So if you’ve got comments or questions about data visualization, and you would like to discuss them with us and with over 2200 other marketers pop on over to our free slack.
Go to trust insights.ai/analytics for marketers, where you can ask and answer questions all day long, about all things marketing, and analytics, and wherever it is that you watch or listen to the show.
If there’s a platform you’d rather find it on, go to trust insights.ai/t AI podcast where we’re on most platforms.
Thanks for tuning in.
We’ll talk to you next time.
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