The Different Types of Data Visualization – Which One Is Right for Your Content Marketing Strategy?

The Different Types of Data Visualization – Which One Is Right for Your Content Marketing Strategy?

Data visualization, sometimes referred to as information visualization, is becoming more and more common when it comes to gleaning insights from big data. This is because big data in its raw form isn’t always the most helpful for interpreting and analyzing for new insights. A row of data or a single data point is much less useful than a visual representation of those data points when it comes to data analysis and determining correlations, which is why statistical graphics and scientific visualization are becoming more critical in the field of data visualization. Information graphics and the proper data presentation are also becoming increasingly important in today’s data-driven world if you want to make the most of your business intelligence platform and tools.

Just because you’re using data visualization doesn’t mean that there aren’t some best practices to follow, though. In fact, the various charts and groupings offered by data visualization tools can often mean that you’re having to select between various visuals in order to pick the best graphic representation of data. Spreadsheets aren’t a helpful way of presenting information for comparison, but they’re also less likely to create confusion than the wrong visual or chart representing a set of data. If you’re just venturing out into the world of content marketing and data visualization, here are a few things to know about how these two realms intersect effectively.

What are the Different Types of Data Visualization?

Data visualization is varied, since there are different ways to present statistical graphics as visual information. For example, a pie chart would likely be best if you’re comparing multiple parts of a whole, such as segments of a certain age or other demographic. That sort of information could also be presented in a bar chart or histogram; however, these sorts of visuals are better for comparison between less similar groups than a pie chart. Scatter plots, on the other hand, are help for presenting a smattering of data points on various axes and looking for clusters that could signify certain correlations. A heat map is another great way to show visual information, especially if you’re looking for visual stories about how users are interacting with a specific web page or marketing email. While there are a myriad amount of data visualization options at your fingertips when it comes to visual analytics, below are some of the most common ways to transform raw data into a visual display of quantitative information.

Which Type of Data Visualization is Best for Your Content Marketing Strategy?


It would be great if there was a one-size-fits-all answer to this question, wouldn’t it? Unfortunately, selecting the right form of data visualization for your content marketing strategy ultimately depends on what you’re trying to do. If you want to present data in the most easily understandable way possible, sticking to the line chart, pie chart, or bar graphs that you learned about in elementary school is a good idea. That being said, infographics are becoming more and more popular as a way to offer a visual display of quantitative information, too. Particularly if your content marketing strategy is focused on social media platforms like Facebook, Instagram, and Twitter, infographics may work really well. This is partially due to the way that images and animations already perform well on social media channels, and is also a result of the fact that you can brand or spice up an infographic much more easily than a more simple bar graph of a dataset.

Data visualization sounds much more complex than it actually is. In fact, of the various types of business intelligence software and services, data visualization is one of the most straightforward kinds of ways to interact with data. Remember that the main goal of data visualization is to tell visual stories instead of presenting large amounts of data raw and unfiltered and you’re bound to find success.