Guest post by Astrid Michelsen, Client Relations Specialist at nullmighty
We live in a world of visualisation. There is so much information we share we need to adapt our time schedule, our devices, and our relationships to adequately absorb all this amount of information. Data visualisation is a relatively new solution for this collection of information, or data, which we call a dataset. A modern society is a society suffering of data glut. Businesses need more ways of getting to their clients or to other businesses.
Their need to increase their visibility, which was once a simple problem solved by basic marketing tools, had to transform into to an invasive game of imposing their information on the market. While it may seem that there is not such a thing as bad advertisement, using the same marketing techniques over and over is a big turn off for consumers. The result of intrusive publicity is generating a wave of antipathy from the client-target, and in the best case scenario, they will only watch your content like another ‘terms and conditions’ they will need to scroll down and accept it.
Data visualisation, and particularly interactive data visualisation, is an easy solution of filtering this enormous amount of data by making use of patterns and connections that matter. This means not only showcasing the content but designing the information as it was a visual entity. Data visualisation presents the content as it was telling a story.
The main goal of Data Visualisation is to communicate enormous amount of information in a clear and effective way through graphical means. In order to produce this self-explanatory visualisation, both artistry and functionality need to be addressed. Accessible and beautiful, like we like to call it, this representation of data achieves more insight into the nature of a problem. If the initial problem was an overload of data and intrusive information, a business can rectify that by using (or better, displaying), less amount of content. However, although it may win the precious attention of the consumer for a short while, it may lose its place overall in the marketers competitiveness. The only way to efficiently communicate this content is to make it visually easy to understand, as they will display an image. Let’s take for example Sunny Edinburgh Project (http://private.nullmighty.com/labs/sunny-edinburgh/). This could have been represented by scraping a load of reported figures and statistic and various other information from multiple sources. The way it all worked relied on using a minimum of words and a majority of graphics that were, most importantly, interactive and interconnected.
Sunny Edinburgh Project is a project aiming to present different type of live data in a way that yields clear understanding through graphical means. The enormous amount of information included in this project was divided into a comparison between Edinburgh and Madrid’s forecast, by analysing rainy days, sunny days and windy days. The information was even more categorised, as the user was able to play between the days of the year, seasons and months, discovering the sunniest/ rainiest/ windiest day of the year in both cities, as well as retrospectively, comparing data from 2011 to 2015. There was a temperature info in the middle of the bubble, depicting average, highest and lowest temperature on the specific date selected. The project proved to be a great success of visualising complex data, by transforming otherwise long and boring stats into a clear and effective graphic example. As this was presented at the Data Talent Scotland event in 2016, we can record and quantify the results. This was not only a win for the companies who were interested to acquire this product for showcasing their own data, but also for visitors who needed reminding on how depressing our weather can be. A real conversation starter!
Interactivity is the key in any data visualisation. Users can see straight away the relationship between patterns and numbers, stats and timeframes, graphics and tables. This would otherwise be scattered across multiple paragraphs and numbers and clearly not have the same engagement.
David McCandless stated in his TED talk in 2010 that businesses need relative figures that are connected to other data facts in order to see the fuller picture, and thus to lead them to changing their perspective. His master, Hans Rosling, said ‘Let the dataset change your mindset’. From a psychological point of view, this is likely to change the users’ behaviour as well. If intrusive and aggressive marketing is attracting antipathy from the members of the public, an interactive visualisation would make the user feel like he is controlling the amount of data given by the business. As the visualisation includes patterns and connections between financial and operational activities interconnected in between them as well as between other types of data, the user is given a tool to choose what type of content he wants to visualise and which type of content he wants to see first. This is usually a win-win: businesses get all their content understood with minimum investment, while their service consumers are happy to select and prioritise the content provided as they desire. It is proven that interactive data visualisation is the best way to enable an audience to directly interact with data and further to engage them.
Data visualisation is about variations in shape, colour, pattern. David goes further calling it ‘the language of the eye’- and by combining the language of the eye with the language of the mind, which is basically words and numbers and concepts- the user starts to speak two languages simultaneously, each engaging the other. This is Data Visualisation in the end: a platform for a user who is eager to expand his eye language.