How data visualisation can be a marketer’s secret weapon

Marketers and journalists alike love using data visualisation techniques in the content they create, but all too often they fail to adopt the same engaging storytelling techniques when they report on data internally.

In 2013 the most popular story on the New York Times was a piece of interactive data visualisation. The piece, entitled “How Y’all, Youse and You Guys Talk” was created by in-house developers, based on a University of North Carolina study about dialect.

In just 11 days it was visited more than any other piece for the entire year, including breaking news stories about the Boston Marathon bombings.

A cynic might attribute the story’s popularity to narcissism — the piece asked readers to reflect on the way they spoke and then told them something about their dialect. But five years later our rapture with dynamic, visually interesting content has continued to grow. The graphics on website Information is Beautiful have generated such a sizeable following that it recently hosted an exhibition featuring 3m-high interactive data visualisations. Most major media outlets, including The Wall Street Journal, New York Times and BBC, all have Twitter handles devoted exclusively to data visualisations. The Guardian has two.

Many marketers have capitalised on the ability of data visualisation to simplify the complex in the content they create, but still aren’t using it to shine a light on their teams’ achievements  when they report content or campaign results to the c-suite. This can mean that the value of the marketing team’s efforts isn’t always clear.

The big picture

The best way to approach data visualisation is often to use storytelling techniques so that your data is accessible, but also engaging.

As with any kind of storytelling, it is first important to set the scene. Numbers are, by their very nature, specific, so it pays to be to be explicit about how your data relates to the broader goals of the organisation.

To that end, it’s always a good idea to contextualise your data visualisations using some brief accompanying text, and explain why they reflect a success or failure and how this will inform the content strategy moving forward.

Keep this copy succinct and to the point, giving recommendations that are simple and relate directly to insights from the data.

Visualisation versus data

In 1964 Marshall McLuhan can’t have known that his adage, “the medium is the message” would be used to describe story clicks and digital audience engagement, but the maxim holds true for data visualisation. Before you can think about more sophisticated storytelling techniques you need to know your line graphs from your bar graphs and your pie graphs from your scatter plots, so you can easily decide which will best illustrate your numbers.

For the data visuals themselves, there is no shortage of inspiration — particularly for the design savvy. The New York Times, for example, is increasingly making its data-heavy stories more interactive. Its summary of the Obama years asked users to draw their own line graphs, based on their assumptions about growth and decline in various areas during his presidency. The program would then generate the real data, encouraging readers to challenge their assumptions about the administration. Similarly, NYT’s infamous ‘election calculator’ synthesises the complex US voting system and updates in real time on election day, with incoming vote counts and projections.

These kinds of visualisations can be difficult to create, but the end product is simple to use and understand, making convoluted data easily digestible and highly engaging. While the ends of marketers are different to those of journalists, the storytelling principles remain the same – put in the hard work so your readers can easily understand your story.

If you don’t have an animation department at your disposal, Google Data Studio produces graphs that are highly customisable and, better still, interactive, meaning that your audience can adjust the variables, such as date range or time of day, and can more easily understand the nuances of the data.

There are other tools as well, including Plotly, Datawrapper, Quadringam and Tableau, and as demand grows, there are more being developed all the time. Data is Beautiful will soon be launching VIZsweet, which it describes as “a high-end tool for creating beautiful, interactive data-visualisations and stories”. Time will tell.

The future

Scott Berinato, the Senior Editor of the Harvard Business Review and author of Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations, thinks that visualisations will soon become even more dynamic and interactive, and encourages savvy marketers to lean into this trend.

“I can imagine a presentation getting more interactive in the future. For example, a budget update becomes: ‘Here’s some numbers. Let’s workshop it right there. What would happen if we changed these assumptions?’ That’s really exciting to think about,” he told the Content Marketing Institute.