Data visualisation – the tool for easy and quick knowledge acquisition

Our first article concerning digital analysis revealed the challenges faced by companies in today’s world of data. Companies often have enormous quantities of data at their disposal but fail to take advantage of them. This is because many entities focus on gathering and storing data, while the aim of digital analysis – which is to enable deriving data-supported recommendations and optimisations of actions – is frequently not pursued consistently. Data should support the decision-making process, and to this end there must be a possibility to analyse and interpret them comprehensively.

Data visualisation is the preparation and presentation of non-graphic data contained in databases and Excel tables. By this means information derived from such data can be presented and communicated in a visually understandable form. The area of data visualisation combines the principles of many disciplines, such as statistics, information design and psychology, which is precisely why it constitutes a complex, yet very valuable instrument.

Visualisations tell stories, engage the user and can present complex facts in an understandable manner. Visualisations can also be interactive and fun, and in the best scenario might even trigger a “wow” effect in the user. Thanks to visualisations it is easier for marketing managers, decision makers, but also non-technical users who come into contact with data in any way, looking for answers to their questions, to extract information from data, interpret it and derive recommendations for action. Visualisations influence human perception and the visual system. As a sensory organ, the eye carries information to the brain and enables people to analyse complex relations and draw conclusions on their basis. Data visualisation helps users apply their cognitive capabilities and analyse complex facts and relations. Data journalist and information designer David McCandless points in his blog (1) that the attractive appearance of visualisations is important. Beautiful and creative presentations appeal to users and motivate them to learn more from the graphics and make use of them.

But why do companies need data visualisation? In order to be competitive, it is more and more important for companies to be able to develop their marketing activities in a targeted and customer-oriented way. Data-supported decisions are essential for good performance, and an understanding of data is indispensable for this purpose. Data visualisation has the following advantages:

  • Structured and organised data presentation and communication
  • High information quality and good, understandable presentation of information
  • Information is processed and visible, complex relations are presented in a simple manner
  • Visual exploration of data and interactivity
  • Cost savings through standardised visualisations and provision of information
  • Time savings through simple and quick data analysis and insight acquisition
  • Transparent and meaningful reporting and provision of information
  • Potential for action is recognised and optimisations are derived
  • Basis for data-supported decision making

There is no limit to the number of graphical forms of presentation for the purpose of data and information visualisation. The greatest difficulty consists in choosing the right form from among circle diagrams, bar charts, histograms or box plots. The suitable graphic should be selected on a case-by-case basis: the key role is played by the context and the information to be communicated. There are important principles that have been developed in the area of information design, business communication and statistics, which should serve as guidelines here (3):

  • Pay attention to information density: not too little and not too much information in one graphic
  • Highlight important and relevant information, omit unimportant information
  • Avoid redundancy
  • Direct contents to addressees
  • Present the same contents in a uniform manner

In addition, the effect of graphics can be manipulated and thereby customised by applying a suitable font, scale, axial section and layout, so that the information to be communicated is presented in an appropriate manner. It follows that selecting the form of presentation is the crucial factor when it comes to making the information included in the data reach the readers. This is illustrated by the following examples.

Figure 1 shows an example of the effect of various types of charts containing the same information. Although the pie chart provides a good overview of the shares of the groups, it is difficult to compare the values if they are close to each other, and the human eye cannot interpret the area straight away. Therefore, the rule of thumb is to avoid circle diagrams and pie charts when various figures are to be compared. Column or bar charts are recommended instead.
 
Figure 1: Circle diagrams vs. bar charts
[Source (3): http://www.ibcs-a.org/standards/144]

Another common mistake in data visualisation can be seen in figure 2: the left illustration uses the size or surface area of a car in order to represent a certain figure. The problem here consists in two-dimensional representation, which is misleading. The third value is not even twice as high as the first one, although the car symbol gives such an impression. Therefore, two-dimensional presentations should be employed only when the size of the symbol represents the underlying value. Linear bar charts make more sense also here because they facilitate comparisons.
 
Figure 2: Linear charts instead of two-dimensional forms of presentation
[Source (3): http://www.ibcs-a.org/Standards/163]

Effective data visualisation can be useful for a variety of tasks in the company, for instance business reporting or regular standard reports to stakeholders. Regular or ad hoc analyses and insights can be shared quickly and without large expenses, and interactive dashboards can be made available for the purpose of continuous monitoring of the company’s KPIs.

Use data visualisation in your company as an insight acquisition instrument. We are keen to support you in this task.

Sources:
(1) http://www.informationisbeautiful.net/ (David McCandless, data journalist and information designer)
(2) https://www.solit-finance.de/datenvisualisierung
(3) http://www.ibcs-a.org


Digital analysis: Why more is not always better, or 3 strategies to get more out of your data

Using data-based marketing to become more customer-oriented, to organise marketing activities more purposefully: that is the vision. Many decision-makers, however, face a huge amount of web analytics data and are not able to process it systematically so that the collected information could support marketing decisions. This article shows where the challenges lie and what strategies you can use to get more out of web analytics data.