Everyone in the SaaS industry is discussing the value of data. “Data-driven insights,” “the importance of data storytelling principles,” “use data for forecasting,” etc., are some trending topics. Moreover, it appears that companies know the need to take advantage of the information at hand.
So why do 40 percent of businesses still not use data analytics?
The fact that data can be ambiguous is one of the main causes. The availability of a plethora of measurements and data does not simplify analysis. One can facilitate seamless communication using data storytelling principles, an age-old, dependable, and simple form of communication.
This article explores the best data storytelling principles that can help businesses make the most of data to convey their messages clearly.
Data Storytelling Principles To Know About
The main goal of data visualization is to narrate your message and connect with business decision-makers. Also, it does so by using a clear narrative that connects data, insights, images, and models. As a result, the storyteller must concentrate on a few key ideas in the narrative:
Create Your Story
Once your information is gathered and your intended audience is identified, you can start developing a story. Think about:
- With whom are you conversing?
- What do you want the people watching you to learn or accomplish?
- How will you use the evidence to support your argument?
There is more to a tale than merely summarizing your statistics. An engaging data story should take the viewer on a journey. The following essential formula should be followed in your data narrative:
- Context: What situation is this in? What justifies the dissemination of this narrative? To grab the attention of the audience, find a hook.
- Characters: Which ones are the primary ones?
- Issue: Where is the issue coming from?
- Solutions: What steps can be taken to fix the problem? Alternatively, what crucial realizations or practical actions ought we to undertake? What benefits will you receive?
Tell your story in the order that it happened. Proceed by starting with the background information. Your findings should be the most captivating part of your story, so start there. Put it off until the very end.
Data Visualization
An engaging data narrative needs an appealing chart design. When speaking with non-technical audiences, in particular, visual aids are a highly efficient way to capture and hold your audience’s attention. Putting your data story into visual form enhances understanding in every way.
With data visualization storytelling, you can quickly clarify key concepts, highlight the significance of the data, and simplify large amounts of information. Choose chart layout options that will facilitate the understanding and interaction of your audience with the facts.
Add Design Thinking
You have your information, your tale, and your graphics. However, you cannot prepare for an audience without practicing your presentation and placing yourself in their position. The three-step method known as “chart design thinking,” which designers use to envision and communicate information, consists of these two parts.
These three values—empathy, broad thinking, and experimentation—are also called the “3 E’s.” Considering your audience’s knowledge and lack thereof is necessary for empathy. For example, you should generally avoid using excessive technical lingo when speaking with executives as an IT specialist. Considering things from several angles is known as expansive thinking.
You can test your tale in front of a different audience for feedback by doing this. And finally, experimenting. Be receptive to criticism and adjustments; don’t assume your story is flawless.
Tips For Effective Data Storytelling: Best Practices
Now that you know the situations in which we can utilize storytelling to make our case, let’s look at some useful tips for when you attempt this on your own.
- Make sure to always label your axes with the plot heading.
- When needed, employ legends.
- Make use of proportionate and lighter-than-black color schemes.
- Refrain from incorporating extraneous details into your visualization, such as themes or backgrounds that hinder legible reading.
- The simultaneous encoding of two quantitative values based on a horizontal and vertical location is limited to using a point.
- When encoding time series, never use points for visualization.
Ending Note
Data storytelling principles have been embraced by companies worldwide to enhance reporting and decision-making procedures. Data-driven storytelling may surely assist businesses in making the most of their data, regardless of the methods by which they choose to apply it.
So, if you want to become a data storytelling pro in no time, check out the expert tips from Storytelling With Charts!