Data is central to many business decisions and operations. Whether you’re communicating with an internal team or a customer, data can help you tell a compelling story that supports your position and highlights the value of your products or services.
However, raw data can’t do the job on its own. You can’t simply give the audience a handful of spreadsheets with rows of numbers and hope that they’ll figure out your key message or take action. To get the point though and achieve your objectives, you need to present the information in a compelling way to engage your audience.
This is where data-driven storytelling comes in to turn data into an effective, engaging and convincing communication tool. Let’s look at what data-driven storytelling is, the benefits of using this method, how you can use data to tell a story effectively and some data visualization examples.
Data storytelling is the practice of blending hard data with human communication to craft an engaging narrative that’s anchored by facts. It uses data visualization techniques (e.g., charts and images) to help convey the meaning of the data in a way that’s compelling and relevant to the audience.
Data-driven stories are created through the process of analyzing and filtering large datasets to uncover insights and reveal new or different ways to understand the information. They’re tailored to a specific audience and the context in which they’re consumed. This can help communicate information or a point-of-view most effectively while generating the least cognitive load, which affects the mental energy the audience needs to spend on grasping your message and therefore, impact how well it’s received.
In today’s environment in which we’re besieged by data and struggle to make sense of them, data-driven storytelling offers a valuable tool that not only presents the data, but adds context, meaning, relevance and clarity to help the audience interpret the information and extract value from it.
Here are some benefits of using data storytelling as a communication tool:
Data visualization is central to crafting a data story that triggers emotions, engages the audience and inspires action. Here are 9 top techniques to augment data-driven storytelling with effective visualization:
First, you need to define the purpose of your data story. Doing so will help you identify specific trends, focus on a subset of data, categorize the information to support a thesis, illustrate the effectiveness of a strategy or highlight the value of your products.
Also, you may need to tell different stories from the same set of data depending on the audience and their priorities. For example, what’s important to board members probably isn’t the same as what the floor staff cares about. What appeals to the marketing team is likely to be different from what the finance department finds useful.
You also should consider what your audience already knows about the topic and frame your data visualization around their current understanding of the subject matter so you can meet them where they’re at. Then adapt your narrative and visual elements to highlight the key message that’s relevant to the audience and elicit the desired actions.
Good stories have strong plotlines — and that’s no different when it comes to telling a data story with visualization techniques. For example, you may start with a hook (e.g., a question or a conundrum,) then take the audience through a journey that builds momentum and ends with arriving at a solution.
Here are 5 main data-driven narratives and associated data storytelling examples:
To craft a convincing data story, incorporate these key elements:
Your data visualization should present the facts in an unbiased manner, even if you’re using the data to support a specific point-of-view. Any untruthful manipulation, whether intentional or unintentional, can create inconsistency, diminish your credibility and reduce the audience’s trust in your information.
To present your data objectively, use proper labeling to avoid ambiguity, match graphic dimensions with data dimensions and ensure that the design elements aren’t compromising the data.
In addition, take an unbiased approach when selecting information for your data story. For example, don’t use discrete values when data is continuous, be clear about how you treat missing, outlier or out-of-range values and be transparent when you’re using arbitrary temporal ranges, capped values, volumes or intervals.
Using a visualization method appropriate for your data can help display the information effectively to get your point through. Here are some common types of data visualization:
Regardless of the visualization method you choose, simplicity and clarity are key to focusing your message. You should help your audience achieve maximum understanding at a glance by reducing the friction involved in reading and interpreting the graphic elements.
Use white space strategically to guide the readers’ attention, eliminate visual elements that don’t add value to the story and use bold colors to highlight data central to your thesis. Plan for visual hierarchy when deciding on the placement of the information. Most people in Western culture read in a Z-pattern. By incorporating this behavior into your design, you can help the audience better follow the information.
You also can use design elements to reduce the cognitive load so it’s easier for the audience to engage with your content and absorb the information. For example, by staying consistent throughout the presentation, using familiar visualization methods, paring the information down to the essential and priming the audience with the appropriate context or background information.
Using the appropriate software can help you effectively visualize information for your data stories.
Here are some of our favorite free data visualization tools:
Good stories are relatable. By acknowledging your audience’s needs and emotions, you can effectively engage them with the right level of detail and elicit the desired actions. For instance, you can illustrate abstract numbers and insights with real-life scenarios or a personal story to make an idea more concrete.
Good stories are also insightful. As most people struggle with information overload, delivering high-value content can help you cut through the clutter. For example, after reading your data story, will the audience be able to get the answer to their questions, make an informed decision or improve an outcome?
To capture your audience’s attention and keep them engaged, your data story should focus on a single concept and deliver unique insights that are useful and valuable to your audience. Remember, it isn’t just about the data, but how the insights can create an impact on your audience’s lives.
Data analysis storytelling is a great complement to many types of content because it supports your ideas with facts while increasing audience engagement with visual elements. You can incorporate data visualization into articles, white papers, reports, ebooks, videos, presentations, infographics, social media posts and more to increase the credibility of the content and position your brand as an authority.
Your data visualization graphics should be self-explanatory so they can either be embedded in a content piece or used as a standalone image (e.g., on social media.) The design should align with your brand image to deliver a consistent user experience. In addition, you can use interactive data visualization, such as animation, maps or word cloud, to add interest and increase engagement.
Also, tap into the power of social sharing to reach a larger audience and drive traffic to your content. You can ask your readers to share the data visualization on social media and make it easy for them to do so by including social share buttons on your website and a call-to-action in your posts.
Data visualization and storytelling with data is an indispensable tool for augmenting internal and external communications. It can support your ideas with facts and add credibility to your content while engaging your audience to increase information retention and inspire action.
If you’re wondering where to begin, the good news is that data can be found everywhere you look thanks to the many technologies we have at our disposal to collect information from various sources.
You can tap into internal sources such as website analytics, customer research, insights from different departments (e.g., sales, product development, human resources) or get inspiration from external sources including industry forums, Google Trends, studies published by think tanks, reports from research organizations and more.
By combining trusted data sources with a compelling narrative, unique insights, an understanding of your audience’s needs and effective data visualization techniques, you can craft engaging data stories to support your idea and enhance your content.