data visualization

Learn everything about data visualization

Data visualization has been around for ages, from times when humans used drawings in caves as a form of communication until nowadays, when marketers use it for decision-making. Visualizing shapes and forms and coming to conclusions is how we operate when we look at something; thus, data visualization is a very natural process.

Nevertheless, there is a long path to track if we want to understand how we got from drawings to dashboards. In the meantime, we can reflect on why data visualization is so important and how it actually works.

By doing that, we get the importance of visuals, as well as switching from static and tiresome methods of messaging to dynamic communication that is impossible to ignore.

Data visualization has become a central idea in current marketing practices, so keep tuned if you want to know more about it!

 

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What is data visualization?

Data visualization consists of representing data graphically. Think about a set of stats, such as the results of extensive research. If you choose to publish it in a written form, it would surely be readable. However, understanding the whole information would consume a lot of time and effort from readers.

Also, a lot of words distributed in long paragraphs could be overwhelming and confusing to read. People may have a hard time trying to figure out what’s the main message, and the researchers would have trouble getting the point across all those words.

Instead, if you choose a graphic representation, you would use images to express those trends. Charts and graphs, for instance. That’s data visualization, and it works because it allows people to see data differently, catching not just the information, but precise details and new patterns in between.

When we address this topic, we are actually talking about visual literacy. The process that involves our interpretation of an image is fascinating, so we take advantage of that to improve the understanding of data.

First, we start analyzing shapes and objects, establishing the limits between forms in our minds. Then, we think of something we’ve seen before. Later on, those random shapes get a name in our mind, which means the analysis is complete. Looking at charts requires pretty much the same processing.

 

Visual metaphor

It all works based on something called visual metaphor. Just like a regular metaphor, those tools allow us to internalize the concepts of something by comparing it to some shape we’ve already seen. A pie chart, for example, alludes to the idea of a pie to represent a part-to-whole relationship. It’s not a real pie, but a representation of one.

We already know what a pie is and that slices are independent and can be of any particular size. So, we instantly recognize a chart and understand what it means. It tells the story effortlessly, in a way that feels as natural as possible.

Enterprises can use data visualization to summarize a database in dashboards. By using that tool, managers are able to see trends, patterns, and insights to make better decisions. Marketers can employ that to study campaigns and customer data, in order to improve their work.

 

What is the history of data visualization?

As we know, data visualization has been around for a very long time. So, let’s go through that. Back in the 18th century, a statistician named William Playfair had invented the forms we are using so frequently today. He’s the creator of the line chart, the bar chart, the already mentioned pie chart, as well as the circle chart.

During the 19th century, one of the best examples that pop up is Jonh Snow’s chart. He mapped the cholera outbreak back in 1854. But before that, in 1812, Charles Joseph Minard mapped the Napoleon’s March to Russia, representing his journey on a graph, with different features such as temperature and number of soldiers remaining in each place.

Everything started to change when the industrial revolution happened, and people began using stats for commercial reasons as well. Later on, computers came into the picture. Then, statisticians could finally access tons of information quickly. Also, they discovered the power to process large datasets and create stats based on that.

That’s what brought us here. Nowadays, we have intuitive and interactive dashboards. Charts are telling stories everywhere and, without any doubt, stand as the most effective mean to represent the massive amount of data we deal with.

 

What are the benefits of good data visualization?

Now, let’s look at some benefits of data visualization.

 

More attention to detail

As already implied, when we use visuals, we are able to pay a lot more attention to detail than in the traditional way. After all, there are images, trends, shapes, and patterns — a whole universe in front of our eyes. To learn more, all you need is to zoom in to drill down into more insights. Therefore, you’re able to see information from a different perspective.

 

Emotional response

Images are emotionally attractive. People are more likely to provide a passionate reaction to a picture than to a set of words. Charts and visual storytelling talk to us in a way that nothing else can, because they make us go through our memory and remember what we’ve learned before.

 

More shareable

Another critical aspect is: data charts are very shareable. If you look at an article full of stats with no organization, you probably won’t share it with anybody else.

But an image is easy to digest and understand, so the reader is more likely to show it to someone and get their response right away. That means it’s an excellent method to improve communication.

If you look on the internet right now, you’ll find a lot of data charts floating around. In this pandemic scenario, we’re passing through, we see a lot of graphs explaining how COVID-19 works and its growth rates. People usually share those graphs in order to inform each other.

 

Easy comparisons

When we work with visual information, it becomes much easier to compare two trends. You can even put both of them together in the same image as you’re trying to get a sense of how they differ. It’s not difficult to interpret, because differences stand out to eyes quickly.

If you had to do that using text, your job would be to compare every piece of information from one result to the other. It would certainly be time-consuming, and it might involve a lot of mistakes that are just difficult to avoid, not to say impossible.

 

Quick predictions

How can we predict the future with graphs? Well, it’s as simple as it can be. The team just has to look at those trends and patterns, which are instantly visible as they get their eyes on the charts. Then, they can draw conclusions based on what they’ve seen by imagining the repetition of that specific behavior. You don’t even process information and numbers. It’s pretty much looking at the way the graph changes in order to foresee what’s to come.

Let’s look at a real example to clarify things: if your team discovers that a line graph changes every month of March. They don’t even need to process numbers and make calculations. After considering the trend, it’s just natural to expect that the chart for this year will present the same behavior.

 

More impact

It’s way easier to remember images with a lot of patterns than raw data. Charts are a simple form of expression that remains in our memory because it doesn’t require much of our intellectual effort. So, it generates more impact on the viewer, which makes it an effective way to tell a story and to get it to pass on.

 

How does data visualization work?

Nowadays, people use charts in a dashboard, which allows users to manipulate and manage graphical representations. There, you can just add a source and then the application turns raw data into intuitive images.

Plotting graphics is possible if you use Microsoft Excel, but users sometimes prefer more elaborate software, such as platforms based on Business Intelligence (BI). This concept has brought a whole new philosophy with it: data analysis should be democratic, made in a self-service way, available to anyone. By doing that, BI totally smashed the barriers between data scientists and regular users.

Now, with just a drag-and-drop tool, any user can get the graphs they need to take a closer look at the company’s results. Instead of analyzing tables with numbers, marketers can just log in and have a collection of diagrams produced in a few seconds.

 

What methods are useful to visualize data?

Since William Playfair first introduced us to the line graph and bar graph, a lot of visual representations have been used to express concepts and study variables. Let’s go on a quick tour then!

Firstly, we need to look at the general groups. There are at least four of them out there: temporal, hierarchical, network and geospatial. The temporal group refers to time and investigation of changes over a specified period. Hierarchical represents a relationship among different data points.

The network type is about relations, which are indicated by lines connecting points. Lastly, geospatial is a category that describes geographical areas and try to convey a sense of space.

Inside these categories, there are many examples of how to reproduce something visually. The line chart is perhaps the most popular one because it shows us a line and communicates the idea of continuity. See below a description of each type of representation:

  • bar chart: it uses a set of bars to categorize different data points;
  • area chart: it contains a variety of layers that form an area under the line;
  • pie chart: it defines parts of a whole using the metaphor of slices of a pie;
  • heat map: it’s a map with different colors on it to represent different levels of intensity.

You can also use the bullet graph, scatter plot, histogram and bubble chart. It all depends on what you’re trying to express and which variables you will examine.

 

How can interactive content be useful to make data visualization more interesting?

Interactive content is the type of content that requires users’ input. It’s similar to a dialogue between the content producer and reader. Users interact and participate in a conversation, selecting options and giving away some insights about their preferences and needs.

So, how can we mix the two concepts? If a marketing specialist uses interactive content to expose information in a visual form, they increase even more the level of attention and chances for this content to be shared. That leads to more conversions and impact.

For instance, let’s get back to the first example: you want to publish a research on some topics. With interactive content, you can go even more in-depth and get your readers not just to read passively but also to answer questions throughout their reading. Then, you go for a creative, interactive piece. It may be an infographic or a dynamic e-book.

Users, then, can make choices and decide where to go and which stats to see. The content gets more personalized every time they choose a path. Readers can also zoom in and investigate specific details of the diagrams. They can filter the data and look at it from any perspective, learning a lot in a non-tiresome way.

The knowledge users will gain is essential for them and their life, but it’s also relevant to help them move forward in the buyer’s journey. They will know more about the subject they’re interested in, which leads them to build more trust in your brand and make the right purchase decision.

By doing that, your company will stand out in the mind of prospects. After all, the experience with interactive content is fascinating, very much like a game. But, beyond that, your team can collect some info on them that will help to improve segmentation and produce new pieces of content later. The company will contact them again with more value and the proper solution to their needs.

Data visualization is an effective strategy to turn raw data into dynamic, intuitive, and shareable images. You can tell a complicated story and teach people about intricate concepts in a way they will grasp clearly. Today, those methods have been broadly used in Business Intelligence. The goal is to make data simple in order to inspire decisions.

Feel like you need to know more about interactive and dynamic ways of expressing ideas? Check out complete information about interactive content development.

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