How to Tell an Effective Data Story

Using data to tell a story

Each company values sound decision making, which in turn is dependent on accurate and complete information.

That's why it's so important to learn how to interpret data and use it to make informed decisions. People may hear what you have to say, but they won't be moved to take action unless you show them how it applies to them. Data-driven narratives are perfect for this purpose.

The ability to effectively and persuasively convey key insights through data stories is a powerful tool for fostering innovation and motivating people to take action in business. Those of us who think more analytically than creatively often struggle with the art of storytelling. Thankfully, compelling storytelling can be accomplished by anyone.

Use the advice and guidelines provided here to create data stories that will engage, inform, and inspire your audience.

What are "data stories"?

The purpose of data stories is to provide context for the evolution of data, typically through visualizations. The art of data storytelling, however, extends beyond the creation of eye-catching charts and presentations. The key is to share insights that have practical application.

There are three main components to compelling data stories:

• Data
• Visuals
• Narrative

All of these pieces work together to give your data meaning and highlight what's most crucial to those who will be making decisions based on it.

Data stories vs. data visualizations

Data visualization, which is merely the visual representation of information, and data stories are related but separate concepts.

An effective visual can help tell a story and convey crucial details. But a data story is what explains the data's significance and suggests next steps in response to it. Data stories, then, serve to bridge the gap between the data and the audience. When combined with data stories, data visualizations help you present your findings in a clear and compelling manner.

Why it's crucial to tell stories with data

The goal of any data-driven narrative should be to shed light on the surrounding circumstances and motivate the audience to take some sort of action. Data analysts can better convey complicated ideas to stakeholders and speed up the decision-making process by presenting their findings in the form of a story.

Stories help us make sense of the world around us and understand its complexities. It provides the background, understanding, and interpretation that are essential to the value of data and the appeal of analytics.

In other words, using a story will make your information more compelling, interesting, and memorable.

Storytelling with Analytics and Data

Now the question is, how do you know when you've found a good story, and more importantly, how do you tell it so that your audience stays engaged?

Just follow these simple instructions to get going.

The first step is to determine your narrative

Finding a story in the data to tell is the first step in creating a compelling data story. Starting with a query or working hypothesis, data can be gathered and investigated in depth to reveal insights.

Think about the following questions as you consider various narratives:

• What exactly are you attempting to explain?
• What are you trying to accomplish?
• Are you attempting to gain support for a proposal?

The story you set out to tell may not be the story you find when you explore data using different methods. Take into account the following methods as you collect and analyse your data in order to establish a theme and build a framework for your story:

Make an effort to find connections

When you look at the data, what patterns do you notice? Which correlations stand out as particularly intriguing or unexpected, if any? These connections have the potential to serve as a story's riveting backbone.

Identify trends

The direction in which a trend is moving is an indication of the rate of change or the rate of development.

Have you noticed any increases in demand for any of your company's products or services, for instance? Perhaps you're interested in learning how visitors to your website fluctuate over time, finding out whether or not traffic is heavier at certain times of the day.

Your business needs to be aware of any new or shifting industry trends in order to respond and prepare effectively.

Analyse the similarities and differences

It is often through the use of rankings and comparisons that new insights into the relationships between data can be found and understood.

The effectiveness of an email subject line can be gauged, for instance, by comparing the percentage of recipients who clicked on the link. From there, it's possible to delve into the specifics of what made a given data set more productive.

Analyse the data for any unusual patterns

You can still benefit from data even if it doesn't make sense in the context of the reInformation that deviates significantly from the norm is said to be an outlier. Seek out the extremes and probe their causes. What could possibly cause this peculiarity in the data? What is the cause? There's a chance you'll learn something more interesting (and practical).

Pay close attention to information that seems to go against common sense

Data that goes against your expectations or surprises you should be treated with the same level of scrutiny as outliers. When you look at the big picture and make comparisons, do you find anything surprising? What could have brought about those effects? In fact, unexpected stories often make for the most interesting reading.

Be conscious of your audience

It's important to keep your target audience in mind whenever you're creating or delivering data stories. The impact of your story will be severely diminished if it is not engaging or relevant to your target audience.

When constructing your narrative, ask yourself:

• Who is my audience?
• Does this story solve a problem my audience cares about or offer necessary insight?
• Have they previously heard this story?

Consider your audience's age, gender, education level, occupation, and level of familiarity with the topic at hand when crafting your narrative (and let that knowledge guide your storytelling).

If you're telling a story to a group of engineers, for instance, you might want to include more technical details and delve deeper into the data sets. When speaking to a group of executives, however, it's important to remember that they have a wider range of professional experience than the average person and thus require data that has been simplified with clear takeaways.

Adapt your story and your approach to it for the various readers you intend to share it with.

Construct your story

Now that you have your data and know who you're writing for, you can begin crafting your story.

• Who are you talking to?
• What do you want your audience to learn or do?
• Can you give me some examples of how you plan to use this data to support your argument?

A story is more than just a summary of your findings. A compelling data narrative should take the audience on a journey. A data story that accomplishes this goal will adhere to the following guidelines:

Narrative:

Ask yourself, "What's going on? Why am I telling this story?" and "What's the hook?" to get people interested.

People:

Which individuals play pivotal roles, if any?

Problems:

What exactly is the conflict?

Solutions:

What are some potential approaches to fixing this issue? Or what key insights or actionable steps should we take? Focus on what is truly important. Make it personal and engaging. Can you explain the benefits?

TIP: Use a chronological order when telling your story. If you want to make something, you have to put it in context, so start at the beginning. The results shouldn't come first; they're the most interesting part of the story. The big reveal should come at the end.

Make use of visual aids in your presentation and writing to better convey your message

Finally, a data story isn't complete without accompanying images. The use of visuals is proven to increase comprehension and retention, especially when addressing non-technical audiences.

Data visualization is an effective tool for communicating complex information. By combining narrative with data visualization, you can condense complex data into easily digestible chunks and convey your message with clarity and brevity.

There are many ways to visualize your data including, find out some of the most popular methods below:

8 Popular Chart Types and When to Use Them

Struggling to know which chart type to use? We’ve made it easy for you. Here are the most common chart types and when to use them!

Data-VizDaniel Cox

Use the appropriate visualizations that are easily explainable to your audience to enable them to engage with the data and act upon it.

Data storytelling bad practice

The ability to tell a compelling story with data can motivate stakeholders to take acHowever, if not executed properly, it can result in inaccurate or misleading data and conclusions. Storytelling based on data should never omit relevant information or give the wrong impression. Avoid these bad practices:

• It's important to be careful when choosing a scale and units of measurement for your data visualizations. Be sure that your visuals capture the full story.
• Don't just show the data that supports your ideas, show the whole picture instead of cherry-picking.
• Don't alter the visual conventions already established by utilising consistent colours, labels, and layouts. A jumbled presentation, with images and text that don't match up, makes it hard for the viewer to keep up with the plot and get a clear grasp of the information.

See to it that you're not leaving out any crucial details. Make sure your interpretations and conclusions are based on solid evidence from reliable sources, and always give some background information.

Leaders at all levels can benefit from the persuasive power of data-driven narratives because of their ability to explain complicated concepts, gain support for their ideas, and provide more accurate information upon which to base decisions. Data stories can be powerful agents of change if they combine the best of data visualization, analysis, and storytelling.