"Our brains are insanely greedy for stories," explains Fast Company's Rachel Gillette. That's because stories trigger the human biology of cooperation, activating our will to solve problems and collectively survive and thrive.
Researcher Paul J. Zak tells business people to begin every presentation with a compelling, human-scale story." Stories motivate people to engage, and improve understanding and recall even weeks later, blowing "the standard PowerPoint presentation to bits," he says.
Zak discovered that emotionally engaging stories raise oxytocin levels in the blood. This neurochemical signals the "all clear" that the humans involved are safe. Furthermore, people attuned the dramatic tension of a story are more likely to want to help, feel empathy -- and even mimic -- the behavior of the character in the tale.
Good storytelling relies heavily on visuals. As humans, we have a hard-wired bias for visual information. The eyes contain 70% of the human body's sensory receptors. In content marketing "articles with relevant images get 94% more total views, than articles without images, on average." reported marketing influencer Jeff Bullas.
Your organization almost certainly relies on data visualizations to understand your customers' experience and describe your brand's impact. So, we have researched these 5 top tips from storytelling and data visualization experts for good storytelling with data.
1. Understand your Data
While it sounds obvious, the first step to effective data visualization is to understand the data you're working with. That means, before you look for what stories might be hiding in the numbers, consider the backstory behind the data itself. Questions to get at the nature of your data (with credit to Search Engine Journal) include:
- Who collected the data?
- Why was this information collected?
- Who does it represent?
- What audience is this data intended for?
- What is the best way to present the information to the audience?
Understanding the data, and reflecting this knowledge in your visuals, fosters credibility. By knowing what your audience cares about, the better your story can relate to their experiences.
2. Find the Compelling Story Angle
There's good reason why effective storytelling is important in business. Not only do stories spark life into the brain's language processing parts, says neuroscience. Stories activate "any other area in our brain that we would use when experiencing the events of the story." From the time of cave paintings of 27,000 years ago, we've used images to turn important experiences into stories, and back into experiences for audiences for generations.
If you want your story to be interesting, "don’t be boring," says Jim Stikeleather in the Harvard Business Review. See if "the narrative has a hook, momentum, or a captivating purpose. Finding the narrative structure will help you decide whether you actually have a story to tell," he tells the visual designer.
Your data describe facts. But without meaning, the facts aren't persuasive or interesting. Knowing what story your data conveys allows your visualizations to have impact in your viewer's experience.
Telling a story helps bring listeners in sync with an experience. Your narrative -- your brand's take on a given story -- helps you decide how to lay out the information and how to structure your visuals. You want to help viewers to grasp the meaning in terms of their own experience.
3. Simplify the Design to Convey Information
Simplicity is a big factor in data visuals that engage viewers. Cole Nussbaumer Knaflic, blogger and author of a book on storytelling with data says, "an absence of clutter" is among the top four things she looks for in a great visualization.
Decide exactly what you want the reader to take away at a glance. Simplifying the visual design of your graphics make them clear, precise and efficient. The purpose is to make the story clear, not to draw attention to the design.
4. Include the Right Metrics Inspire the Needed Action
Businesses need their customers' stories; it gives brands a clearer view of their customers' lives. They create dashboards to automate the visualization of customer data. Employees rely on them to help track trends and improve their performance based on real numbers. An expert on dashboard design, Laura Tyson of Geckoboard writes about designing data visuals so they drive needed action.
Her advice is to put the viewer's needs first: "a well designed dashboard drives action by displaying only directly relevant metrics for a single audience."
She reminds us that dashboard design should show only the key performance indicators (KPIs) for the intended user. Her examples show how the metrics selected for a sales dashboard and a support dashboard will differ completely, though they have similar visual design.
The driving question is, "will this prompt action?" If the primary metric does not mean something on its own, you may need to include a supporting metric, such as percent change from last time. Design visuals to include just the metrics that your users need to take action.
5. Follow Good Design Principles
Know the relevant design principles and follow them. The goal is to draw the eye to the important information, to communicate. Attention to sound design practices helps your visuals communicate successfully on their own.
Data visualization educator Bill Shandler offers these basic principles to help communicate with data:
- Align elements: "The eye likes things to line up, " Shandler notes. Make the edges of charts line up with each other. Look at text labels. Whether you left-align them or locate them near the end of a bar, for example, and align them consistently.
- Embrace white space: Use as few gridlines and tic marks as necessary. When using axis lines and tic marks, make them gray, Shandler suggests. Put space around charts to help the reader focus clearly on the information.
- Use colors sparingly and with their associated meanings: Shandler warns, "Don't try to come up with your own colors." Steer clear of the default colors in your charting or graphics program. If you're working with a brand, get the organization's design team to help you come up with a good color scheme for easy reading and to make the meaning clear.
- Use only the necessary words: Use just the words viewers need to understand your data. "Don't label everything," Shandler recommends. But, failing to label the axes, or cropping the axes are two of the most common data visualization mistakes to avoid, says Nishith Sharma on The Next Web.
Good Storytelling With Data Meets Several Business Needs
Because data-driven stories have such power to attract notice and stimulate engagement, organizations want to know how best to leverage them.
Effective storytelling with data meets several critical needs. They help people make sense of information that is otherwise overwhelming and abstract.
Stories backed up with data can transform hard cold facts into part of a story that viewers humanly relate to. And done well, employees can see where they need to take action to improve results for the organization.