Crafting Powerful Data Visualizations
The topic of Data Visualizations is one that occurs frequently with Product Designers and their partners on the Product Design journey. This type of data representation trickles through everything that inhabits the Product Design Ecosystem. It may surface across different flows and aspects of the Product itself, and then it disseminates itself across various additional products in the ecosystem, which includes Digital Web Products, Newsletters, White Papers, Press Releases, Presentational materials, all of which require this coherent representation of data to make their messaging that much clearer to their audiences. Data Visualizations are indeed challenging, since they combine factual data with richly conceived business metaphors and brand positioning, all of which married with effective storytelling, positions that visualization at the forefront of being rapidly perceived and understood by its audience. Some Data Visualizations can take static approaches in showcasing their narrative while others can be interactive. Whatever their scope may be, the common denominator invariably is: its universal outreach, its seemingly approachable perspective in representing various layers of content, and the ability for its narrative to be consumed by various audiences (even if for some it will be immediately more comprehensible than for others). This article is a succinct view on some considerations to address when building these, based on extensive work I’ve done in the past with both Interactive and Static Data Visualizations, leveraging both out of the box visualization engines, and also custom ones.
Data and Messaging. Independently if a Data Visualization exists within an application or within a Power Point presentation (just two notable examples), the goal should always be for this artifact to ingeniously represent a complex set of data with enough context for the user to rapidly understand what is being conveyed in it. Which means the team crafting the Product Solution, and Designers in particular need to clarify what story they’re wanting to narrate with that particular visualization. Is it a showcase of the evolution of a particular Product throughout a certain period of time, or the representation of how consumers interest in mobile devices has evolved since 2007 or the fluctuations of credibility and usage of Web 3.0 and Blockchain. Independently of the topic, the goal should always be: make the visualization clear while showcasing it with substance, specificity and credibility. Also and in the case of being an interactive visualization, the users should have a clear understanding of what is expected of them, and how they can consume that artifact. Another very important topic to keep in mind: the Data sources and how this data is meant to be represented. Making sure the data available and the visual concept that is defined marry seamlessly, is something that Designers should always keep in mind, researching aspects such as the users who will consume the artifact, the industry pertaining to the topic, trends, and of course in the case of interactive visualizations, engines or technology languages which can successfully bring these to life.
Storytelling and Users. Data Visualizations are that much more effective when they have a successful marriage of data with a storyline they want to convey to their audiences. They should adapt the typical flow of a story, one that includes an introduction (hopefully a succinct and substantial one), a development phase (or showcase of content) and an epilogue (summarizing what occurred, but more importantly hinting at what comes next). Adding nuance to this structure is also the aspect of humanizing it with the users/characters who are associated with the visualization on some level. The most successful visualizations are the ones where there’s a sense of journey combined with the illustration of how a user is either impacted by it or is part of the visualization itself (any layer that impacts the user), something that ties the topic being showcased with a human presence in the ecosystem. Something that allows for the consumer of the visualization to create a bridge with that representation of data and with the journey that is being showcased to them. Understanding the users in the ecosystem, including those who have been represented in the data, and also those who will consume it, is fundamental for Designers and their co-pilots to effectively build Visualizations that not only resonate, but that also have a large parsing footprint. There are of course visualizations that due to their sheer nature, won’t have an opportunity to bring forth the user component in certain parts of the journey, but a story is shaped by the whole narrative, and not just some chapters. It’s up to the Designers and their co-pilots to best discuss the theme/metaphor of the visualization and how to best tell a story from it (example, if a data visualization pertains to financial assets, create a visual language and path that is associated with that specific industry, and what players are affected by the specific visualization being created).
Branding and Aesthetics. Branding is inescapable and it is also fundamental when building a Visualization. Ultimately the visualization should be part of the narrative that is being told by the brand itself. Which from a pragmatic standing, the visualization should be consistent and seamless with the principles of the Brand, when it comes to DNA-like elements such as fonts, colors, iconography, illustration, stock photography, tone of the writing. It should feel like a continuation of the Brand Narrative, and not be an alien showcase of an episodical occurrence. Chances are the consumers of this visualization will be users and clients already associated with the brand, or others that are being sought after. Either way, the data visualization and its representation should at all times feel like an integrated and orchestrated part of the brand strategy. Aesthetically (which is one of the principles of Design), visualizations should find a balance of presenting the data clearly with an engaging, clearly perceptible and polished stance when it comes to the graphical elements which comprise it (which typically means, there’s a fine line between making sure the metaphor comes across from the illustration, without over saturating the visualization with too much information, which makes that much more difficult to parse through and understand). One of the projects I worked through which focused on Interactive Data Visualizations to be consumed in a worldwide scale had to be tested multiple times and iterated upon as well. Not all audiences consume information in similar ways, since there’s nuances to different cultures, demographics, social-economic statuses, which manifests itself in how users/consumers perceive colors, typography, motion, content tone, and eventually expected outcomes. All this to say, aesthetically and functionally, the data visualization has to maintain a balance where they co-exist without toppling one another. If the aesthetic is privileged over the data, you may find yourself with a shallow exercise in visual components that are opaque for the user/consumer (some of the dashboards that are built for feature films for instance, where there are an array of modules with data, and the character apparently knows what all those mean, and simply touches one single element to make the hatch open, a la Joseph Kosinski’s “Oblivion” for instance). If the data topples the aesthetics chances are you’ll end up with a series of tinted tables, which makes the process for the user that much more cumbersome to parse through, and to be glossed over. A balance between those two components is the goal, something that Designers and their teams should test and iterate for.
Deliverability and Engagement. Delivering these visualizations will typically depend on the channel in which they will be consumed. Either as part of an application, or an interactive showcase, or even a static presentation. Either way, they should appear as part of a narrative being told on a certain topic. They should make sense with the flow the user is going through, or in the case of an article or a presentation, be sensical with the flow of the content that is being showcased. As the previous points alluded to, it should be part of the storyline and be consistent with the brand. It should enhance the storyline, and not take the user/consumer out of it. Its engagement will be that much more successful, the clearer that message and content comes across. It should invite investigation and support the journey of engagement.
Reality Check. Data Visualizations have become essential for almost any engagement that occurs with any user. Users/consumers are faced with a constant deluge of information, which means that for them it is essential they can parse through it in a meaningful and compelling manner (if you think about, even utility bills have a data visualization which showcases for instance the rate of consumption of power or water). That also means, the more clearly data intensive reports or parts of an application are presented, the more successful they are or become (which is why so many Designers have literally thousands of concepts on Dashboards, which one can easily consume simply by going to Behance). Again the goal is to balance pertinence with clarity, assuring in the process that the brand and product experience resonates and engages the user/consumer in order to assure the longevity of the relationship that is either happening or has been happening.
I’ll conclude with a quote from Friedrich Nietzsche:
“Those who know that they are profound strive for clarity. Those who would like to seem profound to the crowd strive for obscurity. For the crowd believes that if it cannot see to the bottom of something it must be profound.”
