Data is the language of business. Used most often as a reference point, addressing performance metrics, or making projections, many marketers struggle to make ‘talking data’ appealing enough to get their salient points across. But that doesn’t have to be the case, with data visualizations to the rescue!
Data visualizations are essential because they make it easy to pass on information without compromising on meaning. It’s like a perfect translation of a foreign language. Through shapes and colors, you can connect with your audience and keep them interested in what you have to say.
Whether you are talking to a group of executives, a department, or consumers on the internet, data visualization is a great way to ensure that your message is not only heard but also understood and remembered.
What is Data Visualization?
Data visualization uses graphics to communicate information gathered from both structured and unstructured data sources. And it’s goal is to make the insight more palatable for humans, as the use of graphics capitalizes on the brain’s propensity for visual information.
The strengths of data visualization are seen in many business scenarios such as communicating trends, reporting statistical facts, and revealing the interconnectivity of large datasets.
Easy and straightforward as it sounds, data visualization is a delicate process. However, when done well using proper tools, it works to improve attention, comprehension, and memory.
For marketers, researchers, data analysts, and others whose job involves communicating through visual media, it is worthwhile to learn how to perform data visualization.
Let’s start with the types available.
Types of Data Visualization
There is a broad range of methods used to present data in interesting and effective ways. What you choose may be limited by the type of information you want to communicate or your audience, but it is largely a matter of creativity. Let us look at some of the most popular types of data visualization:
The table is one of the most common types of data visualization. It displays information in rows and columns making it easy to read and understand. While it focuses less on visual appeal and more on easy reading, there are ways to make it interesting e.g. color-coding and font formatting.
2. Pie chart
The pie chart presents information in a circular graph. The variables are represented as slices of the pie to show their numerical interrelationship and proportion to the whole. The pie chart is used when there are few variables, where the size of the arc can easily be compared to the rest.
3. Bar chart
The bar chart displays information on a graph as bars running along the y- or x-axis. The height/length of the bar represents the magnitude of the variable. On the graph, the bars can be vertical (vertical bar chart), horizontal (horizontal bar chart), or each made up of related bars (stacked bar chart).
The histogram is similar in look to the bar chart but not alike. While the data is presented in bars with the height/length corresponding to the magnitude, the histogram shows data in ranges. It is best used to present continuous data while the bar chart shows data in distinct categories.
5. Box-and-whisker plot
The box-and-whisker plot displays data distribution through the quartiles. It displays a variety of information in a simple yet striking way. The boxes represent the main data with the median denoted inside the box. Then there are lines – known as whiskers – extending from the boxes to show variability outside the upper and lower quartiles, and dots in line with the whiskers to indicate outliers.
6. Heat map
The heat map uses color to represent individual values in a dataset. The distinctness of color as well as its density are useful to show variability in the dataset. It is best used to display a general view of data rather than specific values.
The treemap gives a hierarchical display of information in a dataset. Data values are assigned a rectangle of a size corresponding to the proportion of that value to the whole. It is great for showing large datasets.
8. Scatter plot
The scatter plot represents data points as a series of dots along the y and x axes on a graph. It is best used to represent two variables and how they interrelate.
9. Line graph
The line graph represents information that changes over a period of time. Data points are plotted at various points on the graph and linked by a line to show the continuous change. Why don’t we just show you…
Data Visualization Tools
Data visualization is best done with a digital tool or platform. Some data platforms such as NetBase Quid® and Rival IQ are designed with the additional capability to create highly effective visuals for the data collected. Others such as Google Charts are built for the sole purpose of turning your text into visual data.
Let’s look at some of these tools in more detail.
1. NetBase Quid®
NetBase Quid® uses AI technology to collect a vast amount of deep level consumer and market intelligence. In addition to that, the Intelligence Connector facilitates integration and analyses with third party apps on a company’s own business intelligence platform. And through Opus Uploads, it allows organizations to upload internal documents onto the platform for direct analysis there!
To ensure that this information is easily available, visible, and useful to the organization, NetBase Quid® has a powerful dashboard to complement the busy backend.
After analysis, data can be presented in a wide variety of data visualizations including bar graphs, line graphs, histograms, scatter plots, heat maps, pie charts, and many more.
There are also newer ways of data visualization that are more creative and informative. One of these is the word cloud which is used to visualize data in free-form text. This is useful for presenting information such as keywords identified through natural language processing. It can help shine a spotlight on trending topics.
Another of the new innovative ways to represent information is the use of scores where a dataset is analyzed to rank the brand performance along particular lines. This has been most applicable to sentiment analysis helping brands understand the attitude of the audience.
2. Rival IQ
Rival IQ performs competitive social media analytics leaving you to take charge of how the information is displayed through powerful customizable dashboards and reports. Through machine learning technology, the platform allows you to quickly see changes in the posts, accounts, or platforms you are tracking, whether they are your own or that of the competition’s.
The platform offers a range of data visualization options letting you create and customize any charts, tables, and graphics to export or share with other users.
It also offers pre-built dashboard templates that make it easier and faster to create and share data visualizations with your team or audience. Of course, you are able to brand your exports so that the presentations have the feel of the unique brand they represent.
Integrating with Google Analytics, Rival IQ makes both your social media and website data a part of the display on the dashboard. This allows you to see the minutest technical changes in your competitors’ websites including SEO elements like meta data and title tags.
You can take advantage of this to study how such variables relate to other data points. Further, with segmented Google Analytics reporting, you are able to view and generate clean, organized, and exportable reports.
Tableau is among the most popular data visualization platforms. It is trusted by almost 60,000 companies to offer interactive data solutions. The platform allows integration with a host of data collection tools, taking in the raw data and displaying information in highly responsive visuals.
With Tableau, you can import data from advanced databases such as MySQL, Amazon AWS, SAP, Teradata, and Hadoop. Tableau also integrates neatly with NetBase Quid®.
4. Zoho Analytics
Zoho Analytics is a self-service business intelligence and analytics platform that helps businesses create customized dashboards and analyze their data. The tool helps up to two million users across 14,000 companies transform their data into insights.
You can connect Zoho Analytics to a range of data sources including files, feeds, business apps, cloud accounts, and internal databases. The easy drag-and-drop interface makes it easy to apply the many types of data visualization and generate reports.
5. Google Charts
Google Charts is a free data visualization tool that offers a premium level ecosystem for data presentation. It’s coded on HTML5 and SVG, meaning that it is compatible with a range of popular browsers and supports mobile devices on both iOS and Android.
Google Charts offers a rich gallery of customizable data visualization charts that you can modify to match your brand.
Advantages of Data Visualization
There are many advantages to using data visualization tools:
- Better understanding of data: Great tools use cutting edge technology to add elements to visualized data that improve the understanding of the information by the audience.
- Faster recognition of data patterns: Data visualization tools display information in a way that makes data patterns conspicuous to the eye.
- Clearer communication of data relations: Additionally, the viewer can easily discern the relationship between different datasets in a display.
- Easier sharing of data: Visualized data can more easily be shared with other people as diagrams within the ecosystem of the data visualization platform or as image clippings.
Reach out for a demo to see how NetBase Quid® displays data in simple, yet detailed views so you can share your ideas with the rest of the team.