How to Tell A Story with Data and Analytics

In a world awash with data, digital marketers and advertising agencies of all shapes and sizes are well supplied with facts and figures on the effectiveness of their campaigns. 

The data isn’t the problem; it’s making sense of it and presenting it to clients that’s become such an intractable issue. 

In this article, we’ll explain why data stories matter to marketers, define traditional and data storytelling frameworks, and then examine a few impactful data visualizations that may inspire your next client report.

Why Data Stories Matter

Picture this; the business and marketing world is overrun by computers. 

Data is available everywhere, on everything, and the computers know more about us, our habits, our behaviors, than we know about ourselves. 

Does this sound familiar?

Well, that was the world-view in 1964, at the ad agency Young and Rubicam, when they put out this iconic magazine ad, “Computers Can’t Cry”

The full page ad prominently features a close-up image of a young, blonde, woman, shedding a single tear. There is a small bit of copy at the bottom, that’s worth re-quoting here.

“A computer can tell you how old she is. It can tell you where she lives. How big her family is. How much money she makes. Or where she shops.

What she buys. How much she spends. And what she reads and when she watches television. 

But a copywriter like Greta Nissen can tell you what makes her cry. Or laugh. Or buy. 

Young & Rubicam likes computers.

Young & Rubicam loves Greta Nissen.”‍

Amazing how familiar, and fresh, a fifty year old advertisement can feel.  

What’s most compelling about this advertisement is Young & Rubicam, an ad agency itself, clearly states its function and its strengths; being strong storytellers and knowing how to take data and analytics, and craft a narrative that makes an impact, in an ad. Brilliant.

The Art of Storytelling 

To learn how to tell better stories with data, let’s first review the structure of a traditional story.

The prototypical storytelling framework starts with an exposition of the facts and figures, places, faces, and settings. 

The exposition is followed by rising action and conflict, perhaps the addition of a few extra characters and twists. 

All of this, comes to a high point, a climax that then resolves through falling action, and unwinds back into a state of relative stability, capped off with an actual ending. 

If we apply the typical storytelling framework to a data story, what would that look like?

A data story framework first integrates and synthesizes data into addressable issues that clients will find interesting. 

Then, through data visualization, you illustrate the impact of these issues, and push towards an insight. But unlike traditional storytelling, now that we’ve reached the climax, we can’t hit the peak and climb down. 

Data stories should inspire inquiry, and end with a set of intentions, leading to the next iteration. A good data story leads to the next chapter of your relationship with your clients. 

Successful data stories don't have storybook endings; they’re Never Ending Stories.

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Data Storytelling Defined

‍Data story is simply; visualization, plus context, plus narrative.

‍Self-service Business Intelligence and analytics platforms have given marketers access to a range of tools and data integrations, helping them create compelling data stories. 

Data visualization can show up in a variety of different forms, ranging from geographic maps, charts and graphs, or more varied examples like candlestick charts or heat maps.

It’s important to remember that there isn’t ‘one correct format’ to data visualization and representation. There will always be contextual, conceptual sequences that visualizations will need to follow, in order to make a compelling case for clients.

How to Build a Data Story

Rather than starting from whatever data is available, begin with the questions you’re trying to answer. 

Of course, this means knowing which questions are important. At a general level, there are three indicators you should concern yourself with, when attempting to tell a good story with marketing performance data.

• Input Indicators - Contextually, what’s different from the last report? How does the activity of the marketplace differ from before; what have the competitors been up to, and how might that impact the data?

• Leading Indicators - What is the reach? Have enough people seen the campaign or brand? How do they feel about it, and is there a difference from previous reports? Different how?

• Lagging Indicators - Has what we’ve done, changed behaviors? Have we sold more, if so, where and to who? Was that expected?

Identifying the questions you’d like to have answered, defines the type and volume of data you need to collect. Before you start telling a story, you have to gather facts. 

Most organizations hoover up so much data, it’s relatively easy to overwhelm a report with data sets.

Knowing what you are measuring and why, instills far more confidence when you get to the how; which is taking all the data and presenting a crystal clear client report, that tells an impactful story.

Examples of Effective Data Storytelling

The key to getting valuable traction out of a data story is to consider the audience. The sales reps might love to focus on competitor details, but the finance team would prefer to discuss predictable outcomes and ROI.

The audience for your data story must be actively, not passively, engaged with the information. And through a series of linked visualizations, you and your audience explore and question the narrative, which inspires intention to continue the conversation, the campaign, and the relationship, in the next client report. 

Here are a few examples of how marketing agencies have used NinjaCat client reports, as effective examples of data storytelling.

Take advantage of NinjaCat’s report builder, where data fields, integrations, and image galleries are all 100% customizable.

Another benefit of customizable dashboards and reports, is the ability to integrate multiple datasets, and track several objectives and key results, OKRs, in one place. In this example, internal KPIs are tracked right alongside point-in-time analytics reporting about the ad campaign, providing a high-level overview of the activity and results of marketing. 

In Conclusion

Effective data storytelling is about communicating insights through persuasive narratives that go beyond the data. A data story is more compelling than raw statistics. A data story takes information and integrates, illustrates, and inspires inquiry with it, and when done well, influences decisions and drives change. 

Interested to learn more about client reporting, data storytelling, or to schedule a demo, Get In Touch!