Never before has the size and scope of the data we collect and hold been so important to businesses.

Just look at the looming changes to GDPR (a story for a future blog), and the role of Cambridge Analytica in the US Presidential Election and Brexit referendum (also worthy of a few thousand words). People are starting to understand the implications of clicking ‘yes, please store my details for future use’.

Further, our ability to interrogate and interpret such data has never been more sophisticated, thanks to BI tools such as Tableau and QlikView and charting libraries like Plotly and Highcharts.

The New York Times is leading the way with highly interactive and bespoke data visualisations. No election coverage is complete without a hexagonally-binned cartogram, and #dataviz is being tweeted 500 times a day.

The biggest challenge? Our clients have higher expectations for consuming data. Data should be easily understood, yet have the breadth and depth to be actionable.

It should be live, yet thoroughly quality-assured; on-brand, but bespoke; interactive, and also mobile friendly.

As a data-driven agency, we need to deliver all of these things in our insights (where possible!). We’ve worked hard to make our charts clean and clear, while informative. So here are a few tips you can use to present your data better.

1. Cut the crap

Edward Tufte (1983) introduced the concept of data-ink ratio. How much ink on each chart is vital to understanding the core message?

Here’s a chart with a low data-ink ratio. All those gridlines, labels and bold text are superfluous and make this chart more difficult to understand than it needs to be.

Here’s the same chart, but with all the fluff removed. Sure, you can’t trace your finger along the gridlines to find out exactly how much was spent on Radio advertising, but if you wanted your readers to do that, then why not use a table? Or popups?

Now, the story is even stronger with less visual complications.

2. Tell a story

In marketing, it’s rarely enlightening to say simply how something is. We can add a huge amount of insight by describing how something used to be, or how something will be.

The below chart comes from the same dataset (from this Marketing Week article), but instead we focus on how the spending has changed since 2015. This paints a very different picture to the previous chart — the two would work very well in series.

3. Use grey

Grey is your friend. Rather, the absence of grey is your friend. Using a bright colour to highlight the main story in your data is much more powerful when the comparisons are dulled. Here, I’ve used green and pink to highlight those channels which rose (or fell) by 10% or more.

Using grey with a limited palette is also really handy when you’re trying to keep your charts to a tight brand colour scheme.

4. Annotate

Annotations provide contextual information. They help your reader to better understand the data and the reasons why something is as it is.

This chart highlights that all print channels have seen a decline year-on-year. Although this reduces the data-ink ratio of the chart, it serves to highlight a trend that may not have been obvious to all readers.

5. Make it interactive

We live in the digital age. We interact every day with our colleagues and friends, our phones, and even QR codes on bus stops. We should provide the same level of interactivity to help our readers understand and engage with our data.

Here, I’ve coloured the largest positive and negative changes in green and red respectively, but more importantly I’ve added some interactivity to the chart (click to open). The popups show contextual information for some of the categories, as well as providing the % change. The dropdown menu allows the user to choose where to see the historic change, or look ahead to the future.

These are all techniques that I’ve used to enhance the charts that I create. I don’t use all of them all the time, but the core principle remains the same. Simplify, then add complexity where and when you choose.

Now, your charts are ready to engage and excite. Enjoy!

If you want to learn how to make interactive charts like the last example, head over to my Udemy course — Data Visualisation with Plotly and Python and sign up for only £10.