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Any great story means great details and strategic use of visuals.
Let’s face it: Numbers bore people to death. And it is this particular reason you need to start storytelling with data. Stories have a profound effect on people. Yes, tell a tale compellingly, and you’ll have the full attention of everyone around you.
People do love stories.
And if you want to take storytelling to a whole new level, try strategically incorporating images.
The human brain processes visual content over 60,000 times faster than texts and numbers. And this creates a strong case for incorporating relevant visuals into your data story.
Storytelling with data can be intimidating, especially if you’re not an expert in data presentation. To create a compelling data story, you need a strategy, a plan, THE BIG IDEA, and most importantly, an easy-to-use visualization tool.
In this blog post, we’ve rounded up thought-provoking tips, how-to, never-heard-before strategies, and other ingredients that will help you make your data story more compelling for audiences. And these tips do work. We use them to create compelling and actionable narratives for our clients, presentations, and meetings. And every time we use them, we get an overwhelming response.
We hope you’ll gain immense value from the blog.
Understanding and translating data into meaningful insights is crucial in any setting. And this is not limited to research, digital marketing, and business management. So if you aren’t connecting that information to your audience, they’ll have little motivation to act on it.
And this is where data storytelling comes in.
Data stories help you communicate critical insights clearly and compellingly—driving change and inspiring action. You’re not alone if telling a story doesn’t come naturally to your analytical mind. And luckily, you don’t have to be an English major to tell a good data story.
So what does it mean to “tell a story with your data?
Keep reading to discover more.
Data stories explain how and why data changes over time—often through visuals. But data storytelling isn’t just about making great charts and data presentations.
It’s about communicating insights that deliver real value. And this should be accompanied by clarity and simplicity.
Compelling data narratives have three main elements, mentioned below:
If you combine these elements strategically using tips you’ll learn in this blog post: you’ll have a compelling data story. And your audience doesn’t matter if you keep the context relevant and communication simple with a call-to-action (CTA) at the end.
There’s a tendency by some of you to use data presentation interchangeably with storytelling with data. The following section will clear the air by highlighting clear and practical distinctions.
Data stories and presentations are connected but distinct. Well, data presentation is simply a visual representation of information.
Visuals play an essential role in telling a story and communicating critical pieces of information. But the data narratives put that information into context and share why it matters and what actions to take. So data stories connect the audience with the data.
On the other hand, data presentations support and enhance data stories, helping you communicate your insights elegantly and in an easy-to-understand way.
Now that you’ve learned the distinction between data storytelling and presentation: Let’s jump to the following equally important section. Why do data stories matter to you?
Data without a story lacks impact for two reasons, namely:
The data seldom comes distilled. This means you don’t necessarily need more data to solve your problems or uncover opportunities. But you do need to identify and communicate value from the data you already have.
And secondly, data doesn’t support a BIG Idea. And this makes it difficult for our audience to grasp the actionable “news” it brings quickly.
We live in a world characterized by a gazillion of information, ads, trend news, etc. And besides, with socioeconomic problems the current Coronavirus global pandemic has come with, such as mass loss of jobs, we’ve turned into a day-dreaming generation.
And it’s not surprising to see people nod as you speak but in reality, they’re very far mentally. So it takes strategic use of emotional triggers, such as captivating narratives, to awaken people, or capture their full attention.
Just picture yourself in an afternoon meeting looking at Bob from the Finance Department presenting company revenue projections with massive tables. And don’t forget to add Bob’s bland demeanor to the mix.
So if you have numbers and want to explain their changes to any form of the audience (including engineers): use stories. And you’ll find your audience taking the action you desire at the end of it all.
Like we said earlier, numbers without stories are pretty much noise. So if you want your audience to rent their ears to you, you need to arouse their emotions. And stories have been tested and proven to do so.
Let’s revisit the audiences with an engineering background. For starters, people in this profession are very analytical. And in other words, they’re the typical ‘show me the numbers’ guys in your office. Engineers are humans capable of feeling emotions, albeit their profession has socialized them to be analytical.
Engineers with a sales background know how powerful stories can be, especially when marketing to fellow engineers.
So you need stories to transform your data into actionable insights to empower data-driven decision-making in your organization.
So let’s agree that numbers without captivating narratives are pretty dry and less attractive to audiences. And this brings us to the other crucial benefit.
One of the core ingredients of a compelling story is simplicity in details. You might have stumbled upon a fascinating insight in your data that either communicates opportunity or impending risks. But your problem is to share these insights with the decision-makers for action-taking.
You use data narrative for change. There’s no doubt that stories can lead your audiences in the direction you want.
Now you have a clue about why data stories matter to you. So let’s delve into its core building blocks.
Data storytelling is not a simple case of charting out the numbers and creating a report on the findings.
A great data story example visualizes the information so that even someone with no background knowledge can look at the chart and understand what’s being displayed.
You want the audience to reach the same conclusions that you do when they view your presentation.
You need the correct chart that expresses the data, the context of that data, and what’s significant about it.
It’s a three-step process.
Before you can begin telling your data story, you must first perform a thorough and accurate analysis.
Data science is the field of expertise that deals with extracting knowledge and insight from raw data and making it accessible. Data scientists collect, clean, and analyze data to find these insights.
In the business world, the need for business professionals to also be data scientists is crucial. This combination means you can extract insights experience and know-how to understand the opportunities hidden in the data.
Once you’ve uncovered opportunities or risks in the data, you need a means to depict those findings visually.
The problem is that tables and spreadsheets are not very engaging or easy to understand. You have to work line-by-line, comparing different values in Excel, to get what’s being shown.
It’s a tedious and challenging process that is far from efficient. Plus, it’s easy to make mistakes when only looking at a data table.
Presentation is the process of transforming your data rows and columns into easy-to-understand charts and other visuals.
This allows you to physically see the data and how it unfolds. This is the beginning of your data story!
Your typical data visualizations have limitations. They only provide an at-glance snapshot of the data, but fail to offer the crucial context needed for audiences to get the big picture.
This is where the narrative part of data storytelling comes into play.
The narrative uses language and other contextual clues to offer the necessary background that viewers need to understand the story.
You can achieve this narrative side in data presentation through titles, labels, colors, and other formatting decisions. Even the types of charts and graphs you choose can be the difference between a good and a bad data story example.
Below are essential tips you need to incorporate into your data narrative to make it more compelling.
Picture a blank page or a blank screen.
And every single element you add to that page or screen takes up cognitive load on the part of your audience. In other words, it takes brainpower to process.
So you want to take a discerning look at the visual elements you allow into your data story. Start by identifying stuff that isn’t adding informative value or adding enough informative value to make up for its presence. And eliminate them without mercy.
Identifying and eliminating such clutter is the focus of this section.
Clutter is the #1 enemy of a compelling data story. And there’s a tendency by a majority of analysts to cram too much information into a single chart. Yet this is a very harmful practice because it distorts the insights you’re trying to communicate.
The design and other irrelevant stuff in your chart should fade away in the background. This will allow your audience to grasp the insights you want.
Let’s agree on this one: keep your charts clutter-free for your audience to grasp insights instantly.
There are many different graphs and other types of visual displays of information. But only a handful will work for the majority of your needs.
Looking back over the number of visuals that we’ve created for workshops, client meetings, and consulting projects in the past years, we’ve only used slightly over a dozen.
Choosing the best chart possible to embody your data story boils down to your goals. Yes, it depends on the BIG IDEA you want to communicate to your audiences.
Let’s admit it. We’ve all been victims of boring, long, and disorganized presentations and meetings. One of the biggest failures in storytelling with data is the random use of charts.
Different charts come with different uses. So your choice of data is influenced by multiple factors, such as audience type, nature of the data, and most importantly, the main goal.
Check out the summary of charts and their relevant application.
Heat maps transform tabular data into an easy-to-read presentation chart. So if your data is in tables, using a heat map is a good idea.
These charts interact without our visual system, which is faster at processing information. There are 4 types of graphs, namely.
We’re sure you get motivated to tell your story more and more if people are listening. Yes, the listening factor matters a lot to the progress of any story.
Just imagine trying to communicate a story to people who aren’t paying attention. It hurts, right? In data storytelling, you can refocus your audience’s attention on particular insights with the strategic use of colors and the size of the chart.
Take a look at the screenshot below: How many 3s are there in the cluster of numbers shown below?
Now, answer the question above using the screenshot below. How many 3s are there in our data?
Of course, it’s easier to spot the answers. And this is because of the strategic highlighting of the details we want you to see. Similarly, you should deploy this strategy of highlighting the insights you want your listeners to take home when storytelling with data.
Rather than let them do all the work, make the findings low-hanging and easier to cherry-pick with strategic use of colors. And this brings us to the other crucial element that can make or break your data story.
Storytelling with data requires context. And this context has two elements:
Most likely, someone has asked you to explain why something has happened, such as why customers are churning. So this question serves as the basis for your hypothesis and the data you’ll use to answer the question.
Ideally, you’ll start by defining the problem. It’s by defining the problem you’re seeking the solution for; that you’ll get precise traction of your data story.
The second important part of the context is the audience. Yes, the audience type influences the type of data presentation and storytelling language you use. For instance, the charts you would use for non-technical audiences need to be straightforward at best. This means you have to balance between not cluttering your chart with details and being informative at the same time.
The big idea is more of the theme of your presentation. Essentially, this is the part that answers the famous ‘So what?’ question.
For instance, if you’ve just discovered that sales in December and January have taken a slump, the reason why would be a BIG idea.
“During December and January, our sales took a nosedive by 45%, thereby erasing all the gains we made in the third quarter. And this is because of an increase in the number of product returns and refunds. So my recommendation is: there’s a need to investigate further into the product development process to know the cause of the money-draining problem”.
For you to create a compelling big idea, you’ve got to know your presentation very well. And I mean inside-out. The section can boil down into a sentence or a paragraph.
And this brings us to the critical part of your data story: the action you want your audience to take.
Insights have little value if you don’t recommend action, such as whether to invest or divest.
Imagine you’ve already explained what your data story is about and why it matters in some detail. But what should your audience do with this information?
Suppose Internet customers are churning because their connections are dropping too often. Should the company invest in the latest fiber optic cables or focus its marketing efforts only on specific areas?
The alternative is providing decision-makers with a set of choices or recommendations for them to make data-driven and informed decisions.
Providing actionable information is, after all, the goal of good data presentation and storytelling. And it’s thinking through the layers and making sure there’s continuity between where your story starts and its ending.
After doing all this, how do you make your story compelling? This other section provides you with the fundamental building blocks of a story.
So what makes a good story?
When you see a great play, watch a captivating movie, or read a fantastic book, you’ve experienced the magic of the story.
A compelling story grabs your attention and takes you on a journey, evoking an emotional response. And in the middle of it, you find yourself not wanting to turn away or put it down. After finishing it—a day, a week, or even a month later—you could easily describe it to a friend.
Wouldn’t it be great if you could ignite such energy and emotion in your audiences?
The story is a time‐tested structure; humans have been communicating with stories throughout history. Aristotle recognized the impact of stories centuries ago. And he went ahead and provided the building blocks of a captivating story. They include:
The first section sets up the story. And it introduces the protagonist, their relationships, and the world in which they live. After this setup, the main character is confronted with an incident.
The attempt to deal with this incident typically leads to a more dramatic situation. And this is known as the first turning point. The first turning point ensures that life will never be the same for the main character. It raises the dramatic question—framed in terms of the main character’s call to action—to be answered in the climax of the story.
The second section makes up the bulk of the story. And it depicts the main character’s attempt to resolve the problem created through the first turning point.
Often, the main character lacks the skills to deal with the problem he faces and, as a result, finds himself encountering increasingly worsening situations. This is known as the character arc, where the main character goes through significant changes in life due to what is happening.
The protagonist may have to learn new skills or reach a higher sense of awareness of who he is. And what he is capable of to deal with his situation.
The third section resolves the story and its subplots. It includes a climax, where the tensions of the story reach the highest point of intensity. And finally, the dramatic question introduced in the first act is answered, leaving the protagonist and other characters with a new sense of life.
So there’s no need to reinvent the wheel in storytelling. Just use the centuries-old template to create a compelling data story for your audience.
Data storytelling is a powerful tool for engaging stakeholders and inspiring action. However, when done incorrectly, it can lead to incomplete or misleading information and conclusions. And besides, it’s not a tool for propagating unethical persuasion or distributing propaganda with ill motives.
So storytelling with data should never lie, mislead, or misrepresent data. As you develop your data stories and visualize your data, don’t:
And besides, it’s difficult for your audience to follow the story and understand the data accurately.
Data-driven storytelling is a powerful way to:
By combining best practices in presentation, data analysis, and storytelling, you can create compelling data stories that inspire change.
To summarize this section: ensure you’re telling the whole story. Always use good data from credible sources to inform your interpretations and conclusions, and always provide context.
So, how do you tell it effectively?
Use the steps below to get started.
The first step to telling a good data story is to uncover a story worth telling. You can start by asking a question or forming a hypothesis, then compiling and digging into relevant data to find answers.
As you consider your data story, ask:
There are several ways to approach data to uncover a story—and the story you set out to tell may not end up being the story you find. As you analyze your data, consider using the following approaches to help you identify a theme and develop a structure for your story:
What connections do you see between data? And are there interesting or surprising correlations?
These relationships can provide a compelling foundation for a story.
Trends indicate the direction of change. And it can go either upwards or downwards. For example, is there growth in a particular product or service your business offers? Or maybe you want to know your website traffic patterns over time—you may discover that certain days or times tend to be higher or lower volume.
Identifying new or evolving trends in your data is crucial.
Comparisons can help you uncover interesting correlations and understand how data relate to one another and why.
For example, you might compare open rates for two different email subject lines to see which subject line was more effective.
Outliers are one-off occurrences that you may spot in your data. And data that doesn’t fit in with the rest of your data settings can be just as valuable for you.
Look for outliers and ask questions.
Why is the data behaving that way? And what is the cause? You’ll uncover more interesting (and valuable) insights.
Pay attention to any data that is counterintuitive or surprises you.
Are there any results that you didn’t expect?
What might cause those results? Some of the most compelling stories are those that are unexpected.
Always be aware of your audience when developing and sharing your data narratives. And if the story you want to tell isn’t relevant or interesting to your intended audience, it won’t have the impact you want.
As you build your data narrative, ask yourself:
Your audience’s age, demographics, job, and subject matter expertise influence how they understand and respond to your stories (and should inform how you tell your narrative).
So if you are speaking to a room full of engineers, you may want to provide more technical details and dig into the data sets more thoroughly as you tell a story. However, an audience of executives will likely be looking for simplified data with clear insights.
Develop a habit of customizing your story and approach it from different angles depending on your audience.
With your data in hand and your audience in mind, you can start developing a story.
Consider:
A compelling story isn’t just an explanation of your data. So it should take your audience on a journey. To do this, you need to follow this basic formula mentioned earlier:
And lastly, a good data story needs visuals. Visuals are a powerful way to engage your audience and improve retention—especially when communicating with non-technical audiences.
Visualizing your data story enhances understanding at every level. So storytelling with data presentation helps you:
There are many ways to visualize your data, including:
Choosing relevant and easy-to-interpret charts makes it easy for your audience to understand and engage with the data.
This brings us to the meaty part of the blog: the best tool to use to create compelling charts that complement your story.
Please pay attention because this is one of the essential parts of the blog.
Congratulations if you’ve reached this section. Keep in mind this section can single-handedly decide whether your story is captivating to the audience or not.
Remember, our brains process visual data over 60,000 times faster than texts and numbers.
So your choice of the visual chart to be used matters a lot. To emphasize this point: you don’t want to use visuals that barely support your data narrative due to their complexity. You want to choose a presentation chart that’s easy to understand and straightforward irrespective of the audience.
And this is because you don’t want to take chances with your audiences. Simplicity sells. So keep it stupid simple (KISS).
Your audience will not only appreciate your presentation but will also take the action you intend them to. In other words, you’ll have sold your idea, suggestion, solution, or recommendation successfully to your audience.
So you need a tool that can help you create easy-to-read and understandable charts. Besides, you need a presentation tool that grants you the freedom to highlight the insights you want your audience to take home. And most importantly, you want a tool that’s considerate to your budget.
I already use Google Sheets for my presentation needs.
If the above statement is what is already running in your mind, it’s very understandable.
Yes, you can use Google Sheets to take care of your presentation needs at NO cost. And besides, this tool comes with a friendly and familiar user interface (UI).
However, it also comes with WEAKNESSES that can break your data story.
We have a way of eliminating all these weaknesses to make your Google Sheets a powerful presentation tool. The next section will address this fully. Keep reading.
So this highly affordable data presentation tool comes with over 50 chart templates to grant you a broader choice of visuals to select. With ChartExpo, you don’t need to know programming or coding. Yes, it’s that easy peasy to use.
So when you are creating a data story, know you have a reliable data presentation buddy on your side. ChartExpo provides you unlimited freedom to customize your charts. So you can highlight the key insights you want your audience to take in with ease. A few mouse clicks and BOOM…And you have a chart that fits seamlessly within your data narrative.
To Get Started with ChartExpo for Google Sheets Add-on, follow the Simple and Easy Steps Below.
Comparison Sentiment and Stacked Grid Charts are among the 80-plus chart templates you’ll find in ChartExpo. So, we’ll use these chart templates for demonstration purposes.
We want your data storytelling skills to improve significantly with the new tips and tools you’ve learned in this blog.
As the name suggests, Comparison Sentiment Charts are used to compare sentiments, which may be positive or negative. You can use this chart to visualize feedback data provided by customers.
Imagine you run a restaurant. And you want to know how your customers rate your services. And you’re doing this with a view of improving your overall service delivery to outdo the competition and grow your customer base. So you survey to collect the voice of the customer (VOC) data.
Let’s imagine you’ve been conducting surveys for three years running. And you want to know how each financial year compares to the other about service delivery.
The table has the data that embodies our imagination (mentioned above).
| Year | Topic | Positive | Negative |
| 2016 | Quality of food | 11 | 12 |
| 2016 | Ease of ordering | 29 | 50 |
| 2016 | Services | 20 | 33 |
| 2016 | Parking | 2 | 4 |
| 2016 | Cleanness | 55 | 12 |
| 2016 | Ease of reading the menu | 12 | 7 |
| 2016 | wait time to be seated | 16 | 11 |
| 2016 | Seating space in the waiting area | 8 | 8 |
| 2016 | menu and drink choices | 4 | 3 |
| 2016 | Attitude of Waiter | 3 | 5 |
| 2016 | Payment method | 12 | 15 |
| 2017 | Quality of food | 15 | 12 |
| 2017 | Ease of ordering | 51 | 1 |
| 2017 | Services | 28 | 12 |
| 2017 | Parking | 4 | 2 |
| 2017 | Cleanness | 45 | 11 |
| 2017 | Ease of reading the menu | 12 | 8 |
| 2017 | wait time to be seated | 16 | 18 |
| 2017 | Seating space in the waiting area | 13 | 18 |
| 2017 | menu and drink choices | 4 | 1 |
| 2017 | Attitude of Waiter | 3 | 8 |
| 2017 | Payment method | 17 | 16 |
| 2018 | Quality of food | 18 | 12 |
| 2018 | Ease of ordering | 59 | 20 |
| 2018 | Services | 30 | 10 |
| 2018 | Parking | 2 | 0 |
| 2018 | Cleanness | 55 | 7 |
| 2018 | Ease of reading the menu | 18 | 10 |
| 2018 | wait time to be seated | 22 | 14 |
| 2018 | Seating space in the waiting area | 13 | 16 |
| 2018 | menu and drink choices | 4 | 1 |
| 2018 | Attitude of Waiter | 2 | 4 |
| 2018 | Payment method | 13 | 14 |
How easy was this?
Each survey question is ranked according to the sentiments gathered (both positive and negative). The question with the highest number of positive sentiments ranks higher. And on the other hand, questions with a vast number of negative sentiments rank lower.
In the last three financial years, the ease of ordering food and cleanliness have been interchanging in the top spot. And it seems customers love the hygiene level and convenience of making an order in the restaurant.
On the other hand, the quality of food and ease of reading the menu seem to form the bulk of customers’ issues about the restaurant. And this means you need to address these issues if you want to scale to another level.
And this brings us to the second example.
We hope you’ve enjoyed what you’ve read so far.
You can use this chart to visualize comparisons between categories of variables in your data.
Imagine you’re running a PPC campaign on behalf of a client. You create a compelling visual chart that shows the performance of keywords across metrics, namely impressions, clicks, conversion, and cost per acquisition.
A Stacked Grid Chart can complement the data story you’ll be creating. Assume your end goal is to persuade the client in question to increase his marketing budget.
The data in the table below embodies our example above.
| Category | SubCategory | Period | Measure |
| Mobile | Impressions | Current | 2470 |
| Mobile | Clicks | Current | 109 |
| Mobile | Conversions | Current | 3 |
| Mobile | Cost | Current | 2030.9 |
| Smartphone | Impressions | Current | 2459 |
| Smartphone | Clicks | Current | 35 |
| Smartphone | Conversions | Current | 1 |
| Smartphone | Cost | Current | 803.1 |
| Phone | Impressions | Current | 2256 |
| Phone | Clicks | Current | 112 |
| Phone | Conversions | Current | 4 |
| Phone | Cost | Current | 2160 |
| Mobile Phones | Impressions | Current | 1802 |
| Mobile Phones | Clicks | Current | 87 |
| Mobile Phones | Conversions | Current | 1 |
| Mobile Phones | Cost | Current | 1469.9 |
| Cellphones | Impressions | Current | 750 |
| Cellphones | Clicks | Current | 56 |
| Cellphones | Conversions | Current | 0 |
| Cellphones | Cost | Current | 531.1 |
| Mobile shop | Impressions | Current | 637 |
| Mobile shop | Clicks | Current | 58 |
| Mobile shop | Conversions | Current | 0 |
| Mobile shop | Cost | Current | 1559.6 |
| Free phones | Impressions | Current | 627 |
| Free phones | Clicks | Current | 38 |
| Free phones | Conversions | Current | 0 |
| Free phones | Cost | Current | 377.6 |
| Prepaid Phones | Impressions | Current | 626 |
| Prepaid Phones | Clicks | Current | 21 |
| Prepaid Phones | Conversions | Current | 2 |
| Prepaid Phones | Cost | Current | 488.4 |
| Cheap Phones | Impressions | Current | 619 |
| Cheap Phones | Clicks | Current | 47 |
| Cheap Phones | Conversions | Current | 0 |
| Cheap Phones | Cost | Current | 4024.3 |
| New Phones | Impressions | Current | 587 |
| New Phones | Clicks | Current | 21 |
| New Phones | Conversions | Current | 0 |
| New Phones | Cost | Current | 477 |
| Latest Mobile Phones | Impressions | Current | 474 |
| Latest Mobile Phones | Clicks | Current | 31 |
| Latest Mobile Phones | Conversions | Current | 2 |
| Latest Mobile Phones | Cost | Current | 586.6 |
| Best Phone | Impressions | Current | 445 |
| Best Phone | Clicks | Current | 23 |
| Best Phone | Conversions | Current | 0 |
| Best Phone | Cost | Current | 487.3 |
| Mobile Price | Impressions | Current | 440 |
| Mobile Price | Clicks | Current | 28 |
| Mobile Price | Conversions | Current | 4 |
| Mobile Price | Cost | Current | 565.4 |
Let’s export this data into our Google Sheets for presentation using the ChartExpo Add-on. Then, let’s unleash the ChartExpo add-on to visualize this data using a Stacked Grid Chart, as shown below.
Find a Stacked Grid Chart template by pressing a tab called General Analysis Chart.
After clicking the General Analysis Chart, you’ll come across multiple charts. Just browse through to find a Stacked Grid Chart template, as shown by the screenshot below.
Input the relevant metrics and dimensions. In our case, the Measure will be our metric. And our dimensions will be:
Fill in the respective metrics and dimensions, as shown below:
Complete the process by clicking the Create Chart button.
Congratulations if you’ve followed the steps and created your first Stack Grid Chart. The trick lies in practice. Practice more, and you’ll be an expert sooner than you know.
After clicking Create Chart, your resulting chart should look like this:
Note: the length of the bars represents performance. So the more significant the bars, the more amazing the performance is. And vice versa is also true.
The first rule of storytelling with data is to “know your audience.” Understanding the background, interests, and information needs of your audience is crucial. Tailoring your data story to resonate with the specific audience helps in creating a more impactful and relevant narrative. By considering the audience’s familiarity with the subject, technical expertise, and the level of detail they require, you can present data in a way that is engaging, accessible, and meaningful to your target audience.
The three steps of data storytelling are:
Frame the Context: Define the purpose and context.
Present the Data: Display data using visuals.
Interpret and Conclude: Analyze and draw conclusions, emphasizing key insights.
Understanding and translating data into meaningful insights is crucial in any setting. Storytelling is one of the tested and proven media for passing actionable insights to your audiences.
And this is because stories have an emotionally appealing effect on our minds. We all have a story to tell about something that matters to us. Data storytelling can be done efficiently with ChartExpo Library.
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