Dataviz: A Critical Skill for Modern Marketers

Dataviz: A Critical Skill for Modern Marketers

What’s data visualization? In an interview with CCO magazine, Scott explains that in today’s data-abundant world, finding ways to extract human insights from data is a key challenge (and critical skill): “The amount of information coming at us is insane. Others analyze third-party data (such as public datasets or licensed data) to uncover new ideas or create interesting infographics. The chart from Udemy uses multiple colors, but it uses them to distinguish among generations – a good use case. ‘Black Panther’ has become one of the most successful movies ever in a near-record amount of time, completely dominating the winter box office in the process https://t.co/l4MQtMOgSu pic.twitter.com/aCu1I2xyZx — WSJ Graphics (@WSJGraphics) April 1, 2018 Choose chart types carefully The pie chart is a popular choice to visualize percentages that add up to 100%, but it’s often not the optimal choice. Of course, tools need data to make the magic. To understand what’s available, scan through communities like Kaggle, Google Public Data, and Github Data. For beginners who don’t expect to go far beyond updating presentation decks, I highly recommend The Wall Street Journal’s Guide to Information Graphics. For those with more than a passing interest, Scott’s Good Charts is an excellent guide, as is Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic. If you’re interested in visualizing public data sources, Niel Malhotra from Growista wrote an online guide to research and his chapter about accessing and analyzing existing data is informative.

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A decade ago a friend bought me a copy of Edward Tufte’s iconic book Beautiful Evidence.

The professor emeritus of political science, statistics, and computer science at Yale University has spent his career teaching others how to turn information and data into elegantly crafted drawings and graphics – and even more, doing so in a way that illuminates in interesting and unexpected ways.

Inspired by him, I set out to learn more about visualizing data, and how to use it in everyday life. The subject area is massive and at times overwhelming, but data visualization (sometimes called “dataviz”) is among the most critical skills for marketers to understand at least at the basic level, if not to study in more depth. Let’s walk through the what, how, and why of data visualization for marketing.

What’s data visualization?

Put simply, dataviz is the art and science of displaying information (data) in visual form. While bar charts are a form of dataviz, the term is more often used to describe the translation of complex or nuanced data into summarizing, artful images. One of the most highly rated sessions at Content Marketing World was from Scott Berinato, senior editor at the Harvard Business Review and author of Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations. In an interview with CCO magazine, Scott explains that in today’s data-abundant world, finding ways to extract human insights from data is a key challenge (and critical skill):

“The amount of information coming at us is insane. It’s overwhelming. So visualization serves two purposes. First, it serves a prosaic purpose. It gets people’s attention … When you’re fighting for attention, whether in a Twitter feed or even in a presentation, visuals work …

“Second, it solves the problem of relaying complex information. Consider something as simple as trying to understand the gun debate in America. There are so many people saying so many things about guns. Visualization is a way of making sense of all the data, ideas, and information.”

What’s the application for marketers?

Let’s explore two practical and easy-to-understand ways marketers use dataviz as well as real-world cases showing how it’s applied.

Dataviz as marketing insight

The scenario Scott explains – living at a time of data abundance – is particularly true for marketers. Whether we are reviewing our analytics platforms, mining user data for insights, or reviewing sales performance to understand what variables are driving (or dampening) growth, visualizing this information is critical to make sense of what can be overwhelming detail.

Among the most interesting examples I’ve read of late is a case study published by Tableau (the data visualization software company) about its work with outdoor retailer REI. (You can read the full case here.) Managers across REI visualize owned data – online and in-store transactions, operations information, buyer demographics, etc. – to extract insights and improve customer experience.

What used to be done inelegantly with Excel is now visualized instantly using Tableau dashboards. And because Tableau lets you interrogate the data and visualize findings – sorting, slicing, and filtering in real time – it is more likely to surface interesting and unexpected findings. (No more static decks with a single view chosen by the presenter.)

Dataviz as content

Maybe you’re curious about using marketing data, but deep marketing analytics is a step beyond what you’re interested in? The use case nearest to my heart is publishing data as content marketing. Research can take many forms. Some companies host surveys to gather insights about their industries (salary guides and “state of” reports come to mind). Others analyze third-party data (such as public datasets or licensed data) to uncover new ideas or create interesting infographics. And still others find that their internal data can generate interesting lessons to share.

My favorite examples take their original research and make it sing using strong data visualizations to present findings. Among my recent favorites:

spotlight-data-visualization-example

Salesforce does a nice job with its research efforts in large part because of the strict information design that underlies each publication. Charts and graphs are clean and easy to understand. Rather than simply restating research findings, Salesforce explains its point of view on key issues affecting the industry. Salesforce’s AI Revolution report is a great example of its design ethic.

Not every viz needs to be a serious exercise in thought leadership. The avocado toast index is a great example of using existing data in a new and hilarious way.

avocado-toast-index-example

Most helpful tips for dataviz

Let’s be frank. Learning how to visualize data is a massive subject that you could spend years refining and finessing. Rather than trying to sum up a complex discipline, I’ll give the basics that will be most helpful:

Clarity not cleverness

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