It doesn’t matter how good your data visualization is, how reliable your data sources are, or how much technical know-how you have – if what you are doing doesn’t connect with your audience so they understand it and can take action.
Hi. This is Ryan with Playfair Data TV. In this video, I’m going to be talking about why it’s so important to understand who your audience is going into any dashboard project, as well as providing some very specific tactics on how to handle different audience types.
Audiences are critical to dashboard design. That’s why it’s my very first what I call, vital question, which is, who is the audience? It has lots of implications. It’s basically the common thread between all of the strategic frameworks that we implement here at Playfair Data, but at a very basic level just to understand why it’s so important to know who an audience is going into a project before you design anything. Consider the following audiences.
So let’s say that you’re designing something for a C-level stakeholder. That’d be the first audience type. With this type of audience, I’m trying to spoon feed them the insights, or better yet, the recommendations on what to do because of our insights.
I am not going to get bogged down in the detail. This audience does not necessarily want to mess around with figuring out what URL do I need to go to on Tableau Server to look at this report? What are my credentials? Which folder am I going to go to?
Once they do find the dashboard that they need, I’m not going to have a giant table with 50 things on it so they have no direction on what to look for. My job is an analyst. I am trying to make their life easier and find those insights for them, and then communicate those insights in a way that causes them to take an action.
So with that C-level audience, that’s going to look a certain way. It’s going to be very high level, straight to the point. Another type of audience that I very likely am designing for are co-workers or colleagues for you. For me, it’s my stakeholders on the ground. As a consultant, I’m dealing with a lot of analysts myself trying to build decision-making tools that make their lives easier.
These people know how to analyze data. They probably know how to use Tableau to a certain extent, so the two products that I make between these two audiences are going to look very different. If it’s a power user of Tableau, I’m not going to restrict them to that very high level insight and recommendation that I might with the CEO.
With a power user, I might build in some interactivity that allows them to do their own analysis to discover what’s relevant to them. I’m very likely using tactics like dashboard actions and filtering to allow them to explore the data set. The point is, these two things are going to look very different from each other.
And then a third audience. Not necessarily relevant for everyone, but I’m a big– I’m a heavy Tableau Public user. It’s a free version of Tableau, but you have to publish all of your dashboards to the public web. I’m a big fan of sports, so a lot of my visualizations are about sports data. When I’m publishing these visualizations about sports, they’re being viewed by people that are not necessarily data people, and in fact, more often than not, they’ve never heard of Tableau.
So the reason that’s a third audience, and the reason that that product is going to look very different for that third audience is I need to design it for data and non-data people alike, and assume they don’t know Tableau, and they don’t know how to interact with it. But point is, these three products that I build for each of these three different audiences is going to look very different, so I want to know the answer to this question going into the project.
Yes, there can be overlap. Yes, I might need to create multiple views to accommodate these different audiences, but I want to know that instead of creating something for a power user, for example, only to have the CEO say, OK, I don’t know how to use this. What’s going on? Just tell me the answer and what I should do. I’d rather skip that and know who the audience is going into it.
Another topic related to audiences is, you’re going to find that your audience has some combination of four personality types. Whether we like to think about it like this or not, I think of the practice of analytics as a sales process. We’re trying to sell our insights and our analytics capability so that the audience believes in what we’re telling them and hopefully takes an action on it.
Because it is a sales process, I like to consider personality types, which I learned in sales class. These comes– these come in slightly different terminology, but I learned the four personality types as analytical, amiable, expressive, and competitive. And if you can tap in or figure out which of the four personality types your audience leans, because you can have multiple personality types, but usually, people have a dominant personality type.
And if you can figure out what that is, there’s often a tactic or two that you can use to help your dashboards resonate with them, and once again, it’s all about improving the chance of them taking an action. So let’s cover those personality types. So I’m going to give you a few tips on how to identify what the personality type is and then a tactic or two on how I might try to connect with that personality type.
So the first personality type is probably really familiar to us, because you very likely have– at least some of this in you if you’re watching these videos, and that’s an analytical personality type. These people are into the numbers, and they very often want to do their own analysis on those numbers. So my biggest tactic– if you identify your audience as a analytical personality type– is to provide some means for them to get to the raw data. Perhaps you allow them to export raw text tables of data from your dashboard.
That could be one tactic, because they very likely want to do their own analysis in either Tableau, Excel, or some relevant tool. Another tactic that might not be quite as obvious with this group is I like to provide the methodology of certain things in the dashboard. So for example, if there is a certain calculated field that’s not well-defined in the business, I like to put that on the dashboard somewhere, and I like to say, we made this calculation, our KPI is Profit Ratio, and it’s defined as sum of Profit divided by sum of Sales.
That puts the analytical personality type at ease. They know exactly what they’re looking at, and in my opinion, it also adds a lot of credibility to what you’re doing. It shows you put some thought into this, and you’re trying to be consistent, and that’s going to go a long way with an analytical personality type.
Another personality type is amiable. These are really friendly folks, and they’re more interested in connecting with you on a personal level versus the raw data, so almost the opposite of the analytical. You need to build rapport with them on a personal level so they trust you. If they trust you, they’ll have a better chance of trusting the data you’re showing them, hopefully take an action.
With this group, because they’re so friendly, they’re often telling you what you want to hear. They’ll just nod their head and play along and act like they know you’re talking about, so my tactic with this group– if you identify your audience to have some of this personality type– is to ask follow up questions and just make sure they’re understanding what you’re showing them.
Yeah, that’s great. You’re nodding your head making me feel good and confident that I did a good job on this, but really, I’m trying to cause an action. So I want to follow up. Make sure they are understanding, so hopefully they’ll do something.
The next personality type is called expressive. I always link this expressive personality type with creatives or artists if that helps you identify who these folks are. My tactic with this group is to focus on the outcomes. This is another audience that’s not going to get bogged down with the raw detail of the data. They don’t want to know the math, the calculations, the methodology. They want to know what’s going to happen if we implement these changes.
Because they are creative personality types, I will probably lean more towards the design aspect of my visualizations as well to make them more engaging, help it resonate with them so that they want to look at it, but yeah. We’re focusing on the outcomes, and I might be– try to implement some storytelling tactics to convey that outcome to them. The last personality type is a competitive personality type.
You very likely have some overlap between your C-level executives– seen on the last slide– and competitive personality types. Interestingly, competitives and expressives are similar in that you want to focus on the outcomes. They don’t want to get bogged down in the detail of the data. Well, sometimes they do, but typically, it’s more about, OK, what’s the insight, and what am I supposed to do about it?
They’re not going to look at every single million rows of your Excel spreadsheet, at least they shouldn’t be doing that. They probably have bigger fish to fry. But what’s interesting and why these are parallel personality types is we’re just focusing on what’s going to happen as a result of these changes. The difference between expressive and competitive is the way that I would position those outcomes.
With competitive personality types, it’s more about, what’s in it for me. What are they going to get out of this? How is it going to make them look good if we implement this change? Something like, if we implement this change, we’re going to be able to take 1% of market share from our biggest competitor, or if we implement this change, we’ll be able to increase staff by 5% or whatever the case might be, but it’s all about positioning those outcomes in a way that shows us how we’re getting a head start on the competition.
These tips will be relevant for you as you move forward on both the Strategy and the Storytelling tracks here at Playfair Data TV, but I just wanted to ground us in some ideas on understanding who our audience is, and we’ll come back to this and implement it through the rest of these tracks.
This has been Ryan with Playfair Data TV – thanks for watching!