Data visualization: numbers and images

We have all faced the difficulties in explaining complex data sets. We’ve all wanted to pull our hair out in front of incomprehensible Excel tables. It is often difficult to understand a problem correctly when there is an overload of information and it is difficult to present it. So, what is data visualization? How can dataviz help us?

 

Data visualization for marketing is the art of visually representing data to facilitate analysis and decision making.

 

“Do you want me to draw you a picture?” This sentence in everyday language carries meaning. Datavisualization is not a new term… It simply refers to the transformation of a set of data or more or less abstract terms into a visual, readable and understandable representation.
In marketing departments, data visualization is an asset for
making good decisions. When you need to analyze and compare the effectiveness of thousands of digital media files, consulting tables full of figures can be counterproductive. It can take more than a full day to read and understand a document that contains data on the use or distribution of thousands of assets. The purpose of data visualization is to highlight all the essential information on one or more easy-to-read visuals. Applied to content, it facilitates content scoring. But above all, data visualization is an excellent way to communicate with your customers. By presenting clear graphics rather than long speeches, you can capture attention more easily.

 

How to perform dataviz?

 

Data visualization is not just about creating beautiful graphics. It is also the art of choosing the right data representation. The pie chart, for example, is very practical and very pleasant to the eye, but can quickly become indigestible if the amount of data represented is too high. If you are not sure of your creativity, do not try to invent complicated representations yourself. Always favour the clarity of your diagrams.

 

In data visualization, the form counts, especially the colors. For example, red will often be associated with something negative, “dangerous”, while green has a more positive value. A good variety of colours makes reading the graphics more enjoyable. For example, avoid using only cold colors or colors that are too close to each other. You must always keep in mind that you must give priority to the readability of your graph. Be careful not to lose the clarity of your graphic by focusing too much on aesthetics. The key is to keep it simple, with as little text and numbers as possible.

 

The purpose of data visualization is not only practicality: it is also about telling a story with your data. Only 5% of readers retain data while 63% retain the stories. Telling a story through your data visualization makes it easier for your audiences to understand the challenges.

 

From data visualization to data storytelling

 

Storytelling is a process that is reflected in the advertisements of major brands. When Louis Vuitton insists on its long tradition as a craftsman or when Quézac presents an advertisement in 1995 making its water a product with “sacred origins”, we are in the field of storytelling.

 

The same approach must be followed in your data visualization project. Your main objectives should be to attract and inspire.

One marketing campaign that used its data to create huge billboards is  Spotify’s end-of-year campaign, which humorously reveals the sometimes strange listening habits of its users.

Discover how our customers use the Wedia solution to measure media performance

You can also use humorous or unusual graphs and statistics to illustrate your offers in a fun way while relying on your data. Take a look at this article from BBC which uses an original and humorous approach to depict the number of avocado toasts it takes to afford a deposit on a house in 10 cities around the world. This article is an excellent example of successful data visualization because it is simple, engaging and educational.

Finally, here are two recommendations:

First, this book by Andy Kirk on “Data Visualisation: A Handbook For Data Driven Design”.

And second, a site with a catalogue of very useful graphic resources: https://datavizcatalogue.com

Category
Glossary Wedia Solutions EN
Tags
complexity, Data, Data visualization, Dataviz, Measurement, representation, Statistics, visualization
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