Share More

How To Tell Stories With Data For Businesses

tell a story with data

How To Tell A Story With Data

  • Definition Of Data Stories

  • Elements Of Data Stories

  • Data Stories Vs Data Visualizations

  • Why Data Storytelling Is Important

  • Ways To Tell A Data Story

  • Ascertain Your Story

  • Be Aware Of Your Audience

  • Create Your Story

  • Clarify Your Message Using Visuals.

Every single business desires to make good choices, and good choices depend on decent information. 


Still, how you connect that information matters. That is why understanding and interpreting data into eloquent insights are vital. 


Even with linking that information to your listeners, they will have little enthusiasm to act on it. 


That’s where data storytelling arises. 


Data stories aid you in communicating significant insights evidently and grippingly, motivating alteration and inspiring action in business. 


You’re not alone if telling a story doesn’t arise naturally to your logical cognizance.


Fortunately, you don’t need to be an English chief to tell a story. 


Use the tips below to create compelling data stories that motivate, encourage, and stimulate your teams and organization.



Data stories are narratives that clarify in what way and why data fluctuate over time, often through visuals.

However, data storytelling is about more than just creating great plans and presentations. It’s about communicating perceptions that supply actual value. 



There are three elements to data stories, which comprise:





Together, these elements place your data into a milieu and jerk vital information into the application for key decision-makers.



Data stories and visualizations are linked but discrete. Data visualization is merely a visual depiction of information. 

Visuals can play a significant part in telling a story and communicating key information.

On the other hand, a data story sets that information into context and communicates why it matters and what steps to take. 

In other words, data stories link the audience with the data. 

Data visualizations sustain and improve data stories, aiding you to communicate your findings elegantly and effectively. 



Data storytelling is finally about understanding context and emotional changes or actions. 

When data analysts check and submit their data, a story can assist them in communicating their multifaceted thoughts,  simplifying and hastening the decision-making procedure for stakeholders.

 In other words, a story ensures your data is memorable, persuasive, and engaging.  


So, how do you determine and recognize a good story?

And more notably, how do you tell it effectively

Use the steps below to get started;

Ascertain your story

Be aware of your audience

Create your story

Clarify your message using visuals.


The first stage to telling a good data story is discovering a story worth telling. 

You can start by asking questions or establishing assumptions, then collecting and excavating pertinent data to find responses. 


As you consider diverse stories, question yourself:


What are you trying to elaborate on? 

What are your aims? 

Are you trying to get buy-in on an offer?


There are diverse ways to approach data to unveil a story, and the story you set out to tell might not be the story you discover. 

As you assemble and scrutinize your data, ponder on using the following methods to help you recognize a theme and develop a structure for your story:

Look for connections

What connections do you understand among data points? 

Are there any stimulating or shocking correlations? 

These connections can deliver a convincing foundation basis for a story.  

Identify trends

Trends specify the route in which something is fluctuating or evolving. 

For example, is there any advancement in a certain product or service your business bids? 

Or you may want to distinguish your website traffic arrays over time; you may notice that some days or times are likely higher or lower volume. 

Recognizing new or developing trends in your business is important for accepting how the company should respond and organize.  


Draw comparisons

Comparisons and levels can help you discover stimulating links and understand how data relates to one another and why. 

For example, you might associate open rates for two diverse email subject lines to see which topic line was more current.

From there, you can dig into what made one data set more efficacious and provide understanding.  


Look for outliers

Data that doesn’t fit properly with the rest of your data remain just as advantageous to you. 

Outliers are any data that perform unusually or outside the norm. 

Look for outliers and inquire why. Why is the data acting in that manner? What is the reason? 

You may reveal a more exciting (and beneficial) story. 


Pay devotion to data that are counterintuitive

Comparable to your outliers, consider any counterintuitive data that astonishes you.

When you gauge trends or equate data, are there any results you didn’t presume? 

What might cause those outcomes? Unexpected stories can be some of the most captivating



Always be aware of your audience when increasing and distributing your data stories. 

If the story you want to tell isn’t pertinent or exciting to your envisioned audience, it will have a different impression than you want. 


As you build your story, ask yourself: 


Who is my audience?

Is this story important to my audience? 

Does it resolve a problem or difficulty they care about or deliver needed awareness?

Have they heard this story beforehand?

Your audience’s occupation, age, demographics, and focus matter proficiency will disturb how they apprehend and reply to your stories (and must notify how you express and tell your stories).


For instance, if you are talking to a room full of doctors, arrange for more clinical details and dig into the data sets more methodically as you tell a story. 

Yet, an audience of managers will likely have a wider range of professional experience and will be looking for shortened data with clear take-out. 

Customize your story and line it from diverse angles, contingent on the audiences you plan to share it with. 



You can start creating a narrative with your data under control and your audience’s cognizance. 



Who are you speaking to?

What do you want your audience to discern or do?

How can you use your data to make your idea?

A narrative isn’t just an enlightenment of your data. A good data story ought to take your audience on a voyage.

To do this, your data story should keep an eye on these intricate principles: 


Context: What is the condition? Why are you telling this story? Look for a peg to engross the audience. 

Characters: Who are the main players?

Problem: What is the skirmish?

Answers: How can the difficulty be resolved? Or what key visions or actionable strides should we take?


Place prominence on value. Make it significant. What will be gained?

Pro tip:

  1. Tell your story linearly.

  2. Start from the foundation (context) and construct from there.

  3. Don’t start with your discoveries—those would be the most thrilling part of your story.

  4. Save that for the climax at the conclusion. 


A good data story requires visuals. 

Visuals are a prevailing way to engross your audience and expand retention, particularly when communicating with non-technical audiences.  


Visualizing your data story improves understanding at every level. 

Storytelling with data visualization helps you shorten the information, highlight the most important data, and connect key points rapidly. 

There are many ways to visualize your data, including: 

Pie charts




Bar graphs

Road maps

Choose visuals that will make it easier for your audience to recognize and engross with the data. 


Show off your data with a precise visual.

Learn the best performance for actual data visualization.


Data storytelling is an influential tool for likeable stakeholders and inspirational action. 

However, when done erroneously, it can lead to imperfect or deceptive information and assumptions.

Data storytelling should never lie, deceive, or twist data. As you progress your data stories and visualize your data, don’t:


Manipulate scale: Don’t pick random values to base your gauge and units when visualizing data. Make sure you are representing the full context visually.  

Cherry-pick data. Make sure to display the data that best supports your ideas and the entire picture. 

Be inconsistent. Don’t alter colours, labels, and conventions between visuals. 

Inconsistencies between visuals and verbal information can be confusing, making it difficult for your audience to follow the story and correctly recognize the data.

Make sure you are telling the full story. Use good data from reliable sources for your clarifications, and assumptions, and always provide context. 


Final Thoughts

Data-driven storytelling is a powerful way to interconnect multifaceted ideas, produce buy-in, and notify improved decision-making for leaders at each level. 

You can craft compelling data stories that drive change by uniting the best visualization, data scrutiny, and storytelling performance. 

If you found this content valuable, please share it with your friends.

Also, share your thoughts on this post in the comment section below.

Keep winning. Cheers.



Hire the best of African creative, writing and tech experts where experience is our forte.

4 thoughts on “How To Tell Stories With Data For Businesses”

  1. Pingback: 7 Steps To Becoming An Instagram Influencer in 2023 - Expaat

  2. I have read your article carefully and I agree with you very much. This has provided a great help for my thesis writing, and I will seriously improve it. However, I don’t know much about a certain place. Can you help me?

Leave a Comment

Your email address will not be published. Required fields are marked *