Data visualization: a content marketing trend that you can no longer ignore

data visualization content marketing

Data visualization: a content marketing trend that you can no longer ignore

Guest blog by Michael Slender from

The modern online marketer has access to a large amount of unstructured data that creates chaos rather than meaningful insights. For a marketer, data is essential to find out who is buying what, when is being bought and how the target group can best be reached. It is also used as part of the content marketing strategy to rank higher in Google, get more visitors to a website while contributing to the branding of the brand. Data visualization is the visual way in which data is presented that makes it easier for the reader to absorb the information.

What exactly is data visualization?

A graph, table or infographic are examples of data visualization. Data is displayed visually for faster insight. Data visualization is also known as knowledge visualization or scientific visualization. Graphic design and data analysis come together in data visualization. It is originally an interdisciplinary field that also includes epistemology. Today it is a widely used tool for anyone who has a story to tell in which knowledge or data plays a role.


The idea behind data visualization is that it tells a story. The story behind the data is more complex than the numbers in the data themselves. Data visualization should not only show insight into the data, but also bring the insights to the foreground. A simple table with data is no longer enough in 2016. Infographics, moving images, quizzes and videos are the trend. The human brain processes visual information better than text, so that you can make data much more transparent with images, graphs and design elements. With a clear display, the reader can take it in less than a glance. At a time when the average reader's attention span is decreasing, it is important that the reader is absorbed in the story. Data visualization is the solution. It is not only intended to convey the information clearly but also to create more involvement.


The old trusted infographics

Visual representations of data are not new but adapt to the times. An infographic like this one about mobile internet was quite unique years ago, but not anymore. An infographic is “flat” and although it is a structured representation of data, nowadays there are more advanced techniques for displaying data. That doesn't mean an infographic doesn't work anymore. On the contrary, infographics are still three times more liked and shared on social media than other forms of content. Using data visualization, this raw data is transformed into bite-sized information that can be quickly absorbed. This example of the PuffPuffProject does this well showing the relationships between different languages.


Expansion with interactive content

There is a shift towards animated and interactive content as marketers can use more and more techniques to communicate data in an organized way. This has led to an explosion of interactive content. Take this example of that displays data about the vocal use of top artists in a structured and interactive way. With over 78,000 Facebook shares over 700 mentions on other websites, an excellent example of the success of a small amount of data.

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The advantages are therefore great. It leads to more engagement and helps build a brand if used correctly. The best examples of the interactive content are not for conversions. This interactive page of The Washington Post is a good example of this with thousands of shares and likes. With a virtual climb of Mount Everest, data is used to ensure that the reader is completely immersed in the story.


As you can see, data is a powerful marketing tool to use for content marketing but if it is not presented in the right way it is difficult for the users to understand. Using the latest techniques and open source methods, a better form of data visualization is within reach for everyone. Whether you're a content marketer or a search engine expert, it's not a question of whether you should pay attention to data visualization, but how quickly you can prioritize it.


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