Visual Storytelling with Data

With the exponential rise in data being used across every department of a company, the ability to translate data into sensible, bite-sized takeaways and actionable steps is more critical than ever before. And for digital marketers, this means becoming adept at communicating with two distinctly different audiences: Your target customers, of course, and also your co-workers. This post covers how to tell your co-workers a story with visualized data, and not just splash a pie chart on the screen while you talk numbers at them.

But so much data analysis went into making this plan, where do I begin?

All advertising is storytelling, all good data-based presentations should tell a story, and all great stories start with the same plot device: a problem.

If you’re recommending an actionable solution, then that means you’ve identified a problem. Present the data that infers what the problem is in a single diagram or chart, and rather than spending time reiterating the numbers on the screen, talk about what this problem means for the whole company’s bottom line.

For example, no executive cares about an 80% shopping cart abandonment rate amongst mobile users. But if you put that stat up against the 36% abandonment rate amongst desktop users, and tell them that they’re missing out on X amount of potential sales that are already at the last step in the purchasing funnel, that “missing out” number will make perfect sense.

Ok, I’ve told them we’ve got a problem. They’re agitated. Now what?

The beginning of your story has been set: we’ve got a problem. Now everyone in the room is on tenterhooks waiting for your solution. Now it’s time to connect the dots – which is covered in great detail in a post in Big (but not so bad) Data – and move on to the part of your data visualization story that will make you the hero.

Following the example above, you can now move on to presenting potential reasons why there is a significantly higher drop-off rate amongst mobile users. If you have access to heat mapping tools like Crazy Egg, you can identify where users are backing out or having second thoughts, and present screen captures that show exactly that. Otherwise, using Google Analytics, you can show the pages that users are leaving to. Are they going to the user log-in page? Force the user to log in earlier in the purchase funnel. Are they abandoning the site entirely? The user might have been turned off by the taxes and shipping costs, and maybe those costs should be put upfront or, if possible, minimized. Is your site just generally not mobile-friendly yet? Then shame on you, and that’s an entirely different conversation.

Knowing why you’re experiencing issues, although not a solution, is comforting. And it’s also the point in the presentation when you’re seen as the hero. So it’s time to deliver.

We all know we have a problem, we all know what the problem is, so how do we fix it?

If you have access to past digital development costs, summarize a few in charts, including the problem that needed fixing and the end result. Try to select ones that were aesthetic or minor in consequence, but relatively exorbitant in cost.

Now put your proposed solution up with the accompanying cost analysis. Visualize for your audience the potential bottom line gains the company can expect to see if these fixes are made. Alongside most other development costs, this one will seem like a no-brainer to your audience – this will directly increase revenue, or prevent a trend of decreasing revenue.

Final takeaways

The most important aspect of data visualization in a presentation is to keep each visual concise:

·      There is a problem.

·      This is why the problem exists.

·      This is how we fix the problem.

·      This is what we can expect in returns for fixing this problem.

If you try to include anything more in your data story, the important points will be lost on the audience. All of those supporting data points and trends you know by heart? Keep them in mind and off of paper. If someone in the audience is savvy enough to ask you about them, you’ll be ready. But never presume the analytical intelligence of your audience.