When done right, visual data should tell a story. Unlike plain text, data visualization takes complex information and boils it down to a simple, attention-grabbing image that conveys your message without scaring your reader away with long, blocky “walls” of text.
Data visualization can make all the difference between a conversion and a lost sale. After all, visual data transcends some of the most common obstacles in communication, including:
- Language barriers
- Time limitations
- Ability to engage
Of course, to do this effectively requires going beyond the basic PowerPoint presentations of old by designing intuitive and aesthetic visuals that speak to your readers and convey a message.
But first, we need to understand what data visualization is and what it means for your business.
Visual Thinking 101
The human brain can latch onto the meaning of images and pictures at a rate many times faster than text. More than any other kind of data, visual sensory information is how we as humans perceive and make sense of the world around us. As marketers and designers, we operate much the same way.
On an attentional level, we’re simple creatures. Rather than text or numbers, pictures provide our short attention spans with the highest return-on-investment (ROI).
With data visualization, the mind can take otherwise highly complex information and retain its message 60,000 times faster than they would with the equivalent amount of text.
What Makes a Good Data Visualization?
Visualized data should grab and capture an audience’s attention at first glance. Data visualization should never leave ambiguities or questions in your reader’s mind.
For instance, if your reader is unsure about which marketing solution they should invest in for the upcoming quarter, a simple bar graph or line graphic should be able to delineate their best options quickly.
When creating content, visual data needs to stand out from the rest. While large amounts of text may be necessary for adding context, visualized data should be able to tell the larger story for you. Using infographics and geospatial data, your content can be rendered shareable, simple, engaging, and, most importantly, useful. Not only should you be creating something engaging, but you should be creating something that appropriately conveys the message of your data. Take our guide to charts and graphs infographic for example:
How Can Data Tell a Story?
If you have ever studied economics, you might notice that intersecting supply and demand charts are found on every page. Why? Because supply and demand curves offer a simple, bite-sized formula for displaying dense, quantitative data. In other words, they tell the whole story in a convenient, consumer-friendly package.
Where economists have supply and demand curves, marketers and SEO specialists have the power of arc diagrams, area graphs, bubble maps, and much more to showcase their data. There are also “click-through” graphs that allow for seamless data presentation at the touch of your readers’ fingertips.
Data visualization is the key to compelling storytelling. When done right, your clients and readers can easily find the essential information on the page without having to scroll or launch a search query. To save your readership the most time possible, leverage the power of data visualization.
How to Build a Balanced Data Diet
It’s no secret that images and infographics are the bite-sized “snack foods” of the marketing world. They are great to munch on if you are in a rush out the door, or if you do not have time to prepare a hearty meal. Exercise caution, as these tools can be misleading without proper utilization.
It is vital for marketers to maintain a healthy mix of text and varied visual data to mitigate the risks involved with data visualization. Far too often, we find that even the best marketing teams over-saturate their reports with the same old bar graphs of pie charts. Important details tend to go missing this way.
Your clients deserve to hear the full story, without any details or omissions in their SEO or marketing reports. That’s why it is critical that your reports include plenty of visually-appealing data that your readers can snack on if they are short on time.
What Are the Different Types of Data Visualizations?
When discussing data visualization, among the most common questions we are asked are “What are the different types of charts” and “What are the different kinds of graphs” that can best articulate their message. To help you get a sense of which graphs and charts are best suited for your audience, review the list of visualization categories below. We’ve also collected some of the best visualization examples of 2018 in a recent post, if you’d like something to inspire your own visualization efforts, or if you need to see why visuals are powerful.
Data visualizations fall under the “temporal” category if they satisfy two conditions: (1) that they are linear, and (2) that they are one-dimensional. In other words, they usually feature lines which can either stand alone or intersect or overlap with each other.
The benefit of choosing temporal data visualization types such as scatter plots, polar area diagrams, time series sequences, timelines, and line graphs, is that they are familiar. Most of us have been exposed to these charts in school and the workplace, which means they instantly “click” when we read them.
Hierarchical data visualizations are those that order groups within larger groups. The classic “tree diagram” is one of the most popular types of visual hierarchical data because its simple, linear path makes it a breeze to follow along. These figures can be arranged to flow from left to right or top to bottom.
Other forms of hierarchical data plots are ring charts, treemap charts, sunburst diagram graphs, circle packing, and dendrogram charts. These data visualization formats are best suited for those looking to display clusters of information, especially that which emanates from a single origin point.
The downside, however, is that these graphs tend to be more complicated than most.
Data does not exist in a vacuum. Instead, many datasets connect deeply with others, and the ability to demonstrate these relationships using visual network data gives you an edge over long-winded explanatory text. This data type allows users to communicate the intricate networks that link one data set to another.
A few of the most common network data visualization types are alluvial diagram charts, node-link diagrams, network diagram charts, word cloud plots, non-ribbon chord diagram plots, parallel coordinates plot, and matrix charts.
If you want to show relationships between data sets, these are the visualizations that you should lean on.
Image courtesy of Tufte
Multidimensional data have multiple dimensions, which implies that there are always at least two variables at play. Often, multidimensional data makes for the most eye-catching visuals because of the many coinciding layers and datasets.
When it comes to multidimensional visual data, the most common varieties are:
- Pie charts
- Scatter plots
- Timetable charts
- Venn diagrams
- Steam graphs
- Stacked area graphs
- Stacked bar graphs
- Parallel sets
- Multi-set bar charts
These chart types are among the most useful because they can take big data and boil them down to their fundamental takeaways.
Image Courtesy of The Atlantic
Last, geospatial and spatial data relays information related to real-life physical locations. A personal favorite of many, geospatial maps overlay familiar territorial maps with data points. These maps are commonly used to showcase sales or acquisitions made over time. Plus, they’re visually appealing if properly color coordinated.
Some of the most popular geospatial visual data types are the cartogram, choropleth, dot distribution map, flow map, density plot, heat map, and connection map.
Most viewers recognize these maps for their widespread use in political campaigns and by multinational corporations that want to visualize their market penetration.
How Do You Know Which Graph to Use?
There are countless graphs and charts to choose from when converting raw data into a visual format. For many, it can be difficult to decide whether to rely on a straightforward pie chart or bar graph or to opt for a more spatially complex chart type.
Two common questions we often hear are: “How do you know which graph to use?” and “How do you know which chart to use?” The answer, as always, depends on the nuances of your readership, including their experience level and familiarity with big data analytics.
Know Your Audience
The first step in creating an effective data visualization strategy is to identify your audience with precision. If your audience consists of experienced, executive-level marketers, chances are they have already been exposed to hundreds of bar charts, graphs, and other visualizers.
Audience familiarity is a key factor when deciding which types of data visualization you should include in your content. For those who are well-versed in visual data, such as senior marketers or C-suite executives, you can employ a variety of visualization methods to help break the mold and introduce new, stimulating insights.
For less experienced general audiences who aren’t as familiar with data analytics, we recommend the following types of data visualizations:
- Dot map
- Pie graph
- Linear line graph
- Multi-set bar graph
- Word map
On the other hand, there are several more sophisticated kinds of visual data that can communicate more information than those listed above. If you are preparing a report for an experienced industry client or readership, we recommend the following:
- Stacked bar graph
- Spiral plot
- Stacked area graph
- Point and figure chart
- Choropleth map
- Candlestick chart
Know Your Colors and Branding
For decades, marketers have understood that there is a clear link between color and conversions when it comes to establishing a brand identity. But what is less understood, however, is that data is part of one’s brand too.
When visualizing data, it is equally important to keep brand color schemes and aesthetic patterns in check. Bar and pie charts, as well as geospatial data types, are excellent opportunities to include plenty of color in your visualization designs.
By keeping colors on-brand, the reader can better retain both the information and your brand identity.
What are the Benefits of Data Visualization?
If you haven’t already started incorporating visualized data into your reports and marketing campaigns, you are missing out on providing a wealth of untapped value for your clients or readers. Listed below are a few of the best reasons to start visualizing your data.
Data Visualization with Purpose
When you visualize data, you unlock the potential to communicate otherwise complex ideas in a short and sweet format. For instance, bar graphs provide a simple means to visualize the back-link profile of your top SEO competitors and draw conclusions with ease.
One-look analytical insight is a rare commodity in marketing, so it is important to harness it whenever the opportunity presents itself. Visual data techniques do precisely that by displaying key bite-sized information, such as the driving factors behind your competitors’ ranks.
Harness Big Data Trends
Today, machine learning and big data analytics are driving marketing and SEO insights. On the other hand, presenting data alone is not enough to sell your message or generate conversions. Instead, you need to make sense of the data and transform it into useful information. For this, data visualization is your most indispensable tool.
When you leverage this tools power, you can capitalize on a growing trend within the marketing industry: distilling information and presenting it in the simplest way possible. In a complex world, sometimes telling a simple story is your greatest advantage.
An abundance of visual data shaves down your time to insight (TTI). In today’s world, an excess amount of data has left many readers wary of reading lengthy blocks of text without skimming. By switching to visual-based data, you can save your readers the chore by offering them all the takeaway information on a platter.
Data doesn’t have to be boring. When used with your audience’s interests in mind, visualized data can transform an otherwise stale and heavy “meal” into a lightweight, snack-sized dose of useful information. By providing your readers with fresh insights driven by visual data, you can tell meaningful stories that drive conversions. TapClicks is built around the idea that visual data is necessary for agencies. We don’t think that our ultimate guide is the end all be all for convincing the marketers of the need for visualized analytics, but we hope that our companies success and the obsession over our product will demonstrate just how valuable visual analytics can be for agencies and businesses of all kinds.