Data Storytelling – How to Use Data to Tell a Story That Excites Your Readers?

Data storytelling is the art of crafting compelling stories using data. It’s about taking the often dry and unapproachable, even boring numbers, statistics, and graphs and turning them into an interesting story.

Data storytelling will help you make your data more interesting and relatable. Instead of just showing the numbers, it adds context and meaning to them. It’s about something more than just facts and figures – it’s about telling a story that people can connect with. If you’ve worked with content for some time, you surely know, that this connection is vital to keep people interested and engaged.

 When we do regular data analysis, we usually focus on presenting the piles of data that we managed to collect. As you can probably tell already, it doesn’t sound very interesting, or inviting. That’s why we need data storytelling. It connects the data to real-life situations, explains why the numbers are important and tries to make people feel something.

Source: Forbes

Data Storytelling Example

NGOs are a great example of using stories to present important information. As they often care about niche problems they need compelling narratives to convince people to listen to them and donate money to their cause.

A great example is the Ocean Cleanup project which carries out activities to clean the ocean from plastic waste. They help people not only realize how much plastic is in the ocean but also how our day-to-day activities might affect it.

They use visuals to help people understand and grasp the data they’re presenting. For example, the plastic tracker is a great tool that can help people realize where their waste might end up.

Simply stating that it might travel even 117,000 km is not enough since this number is difficult to imagine. But, creating a map that shows the potential journey of a plastic bottle from Malaysia all the way to South Africa and then into the middle of the Indian Ocean is a great way to help people understand their impact on the environment.

Example of where floating plastic debris from Malaysia might end up. Source: https://theoceancleanup.com/updates/where-does-my-plastic-end-up-in-the-ocean/

Another example of data storytelling is our real-life example series in which Delante’s SEO specialists explain how to achieve certain results and they use their own data to back it up.

Data storytelling example – graph showing visibility increase after sucessful migration. Source: https://delante.co/website-migration-case-study/

So, why should you care about data storytelling? How it can be useful to your business?

Data storytelling helps people and organizations to make better, more informed decisions. When data is presented in the form of a story, it becomes easier to understand the consequences of different choices. This can be particularly crucial in business, where decisions based on data-driven insights can lead to better strategies, cost savings, and competitive advantages.

One of the great advantages of well-done data storytelling is its ability to engage diverse audiences. Unlike raw data or complex reports filled with jargon, data stories are accessible to a broader range of people. It makes it easier for people from different backgrounds and expertise levels to understand the presented information.

Data, on its own, can be abstract and distant. It lacks the emotional appeal that stories naturally possess. Data storytelling bridges this gap by simplifying data and making it more relatable to our day-to-day lives. It helps people relate to the information, understand its relevance, and feel a connection to the insights being shared.

So, next time you want to present some really important data, make sure it’s easy to understand and grasp by using storytelling technics. If you want to convince customers that your product is the best, or your potential business partners that your services are the right solutions for them, don’t just use the technical jargon and piles of data. Integrate them into a story of how you can make their life easier.

Imagine a situation where you want to buy a vacuum cleaner, but you don’t really know anything about it. So, the information about the noise level of 76dB won’t tell you anything. But, if a producer adds a short story of how you can vacuum even around sleeping babies it completely changes how you view it ( I don’t know if such a vacuum exists, but it would be nice, wouldn’t it?)

Data storytelling is more than just presenting numbers and facts, it involves creating an interesting story that catches people’s eye and informs your audience.

To make the most out of it, you need to understand the key elements that make data storytelling effective:

1. Data Visualization

Data storytelling often starts with data visualization. Visuals like charts, graphs, maps, and infographics make complex data more accessible and engaging.

2. Context and Relevance

Context is the glue that holds your data story together. It answers the “why” behind the data and helps your audience understand its importance.

 This way your audience not only will understand the data you’re presenting but also why you’re doing it and how it can affect their life. This is especially important if you want to influence their behavior, for example, convince them to buy your products or services.

3. Audience Understanding

Tailor your data story to your audience. Consider their background, knowledge level, and interests. What do they need to know, and what will resonate with them?

Go back to your user personas and adjust your story, data, and communication style accordingly.

4. Emotional Connection

To make your data story memorable, connect with your audience on an emotional level. Stories that evoke emotions are more likely to be remembered and shared.

 Make sure that in the process of creating a great story, you’re not forgetting about your audience. Write about things your users are interested in and tailor your content to their needs, interests, and preferences.

5. Clarity and Simplicity

Keep your data story clear and straightforward. Avoid jargon and complexity that might confuse your audience.

6. Visual Consistency

Maintain consistency in your data visualizations. It helps your audience focus on the data and the story. It also makes your brand more recognizable and memorable. Your audience will easily recognize your content if they associate it with a certain design.

Choose visualizations that are easy to understand and focus on presenting your message effectively. And if you are wondering whether you even need to provide your audience with visuals, the answer is definite YES. Don’t neglect the power of well-crafted visuals – we all prefer graphics over walls of plain text.

7. Data Integrit

Make sure your data is reliable and accurate. Any errors can undermine the trustworthiness of your story and your brand.

Crafting a compelling data story is not easy. You need to consider many elements and make sure your narrative is easy to follow and engaging.

Let me help you by explaining step-by-step the process of data storytelling:

1. Data Collection and Preparation

Start by gathering relevant data from trustworthy sources. Ensure the data is accurate, up-to-date, and appropriate for your story. You can use external data if you are sure they come from a reliable source or use your own data.

I recommend collecting and preparing your sets of data. This way you’ll be able to give users new, original information instead of copying something already available on the Internet. It will contribute to the quality of your content and help you build your image as an expert in the field.

2. Define Your Story’s Purpose and Audience

Clearly define the purpose of your data story. What message do you want to convey, and what action do you hope to inspire? What is the reason you want your audience to see this data? Make sure you answer these questions before you start creating your story.

Consider your audience’s needs and preferences. What level of detail, tone, and visualizations will be suitable for them? If you’re talking to professionals they’ll probably appreciate formal language, and detailed graphs, but a regular user might prefer a simple infographic and lack of technical jargon.

3. Data Exploration and Analysis

Dive into the data to uncover insights, trends, and patterns.

Look for the most compelling and relevant findings that support your story’s purpose. Remember that just showing the data is not enough. You need to elaborate on it and help your users understand and draw their own conclusions.

4. Choose Effective Data Visualizations

Select the right types of charts, graphs, and visuals to represent your data. Ensure that they align with your story’s narrative and purpose.

Make your visualizations clear and visually appealing. Remember about branding – make sure you use your brand’s colors, fonts, and logo.

5. Craft the Narrative

Write the story that accompanies your data. Start with an engaging introduction that hooks your audience and makes them want to read the rest. Remember that every day, people are flooded with thousands of stories, and news. Why would they care about what you have to say to them? You have only a few seconds to grasp their attention, so make the best out of your introduction.

Next, you need to explain the data’s context, significance, and impact as you present your visualizations. Use a conversational tone when possible to make the story relatable and easy to understand. Show people your data and explain why they need to know it, and how it can impact their lives, and gently push them towards desirable action.

6. Refine and Review

Review your data story for clarity, and accuracy. Ask for feedback from your colleagues to find elements that might need improvement. If you want to reach regular people who are not experts in your field, make sure your story is easy to understand even for outsiders, and doesn’t require a PhD in the subject.

Make any necessary changes to enhance the story’s impact and effectiveness. Remember about your goal, you want people to understand presented data and act in a certain way. It might mean that you need to implement a lot of changes to make your story accessible to wider audiences, but don’t give up – it’s worth your effort.

7. Presentation and Delivery

Decide on the format for presenting your data story. It could be a report, an ebook, an interactive dashboard, or even a blog post.

Consider the platform and medium where your audience is most likely to find your story. It might be your company’s blog, Facebook, Linkedin, or industry’s journal. It depends on your readers and the industry you work in.

Don’t copy your competition or success stories of other companies. You know your users best and you need to think about them while creating your own, original stories.

To create compelling stories you need to right tools that will make your task easier. That’s why I will explore some essential tools and resources that can help you excel in the art of data storytelling:

Data Visualization Tools

You can find many data visualization tools on the market. Some of them might require more or less effort and some graphic skills. If you’re a beginner in this area, or you just want a simple tool to help you present your data, Google Looker Studio (previously Google Data Studio) is a great choice. We use it at Delante for creating visually appealing and clear monthly reports for our clients.

Example of using Google Looker Studio for creating visuals. Delante’s SEO report

Looker Studio provides an easy-to-use platform for creating interactive and visually appealing data visualizations. It offers a range of chart types, customization options, and the ability to connect to various data sources.

Excel and Google Sheets

I don’t think I need to present these tools but it won’t hurt to mention them.

These spreadsheet programs are versatile tools for basic data analysis and visualization that we all know and use daily. They are accessible and widely used in many organizations.

There’s no reason not to use them, especially if you’re just starting, or your data set is not large. Sometimes the simplest solutions are the best.

Data Analysis Software

Software like R and Python (with libraries such as Matplotlib and Seaborn) is essential for in-depth data analysis and advanced visualizations. They provide greater control and customization when crafting complex data stories.

Infographic Design Tools

Infographics can be powerful for conveying data in a visually appealing and digestible format. Tools like Canva and Visme are user-friendly for creating infographics. They offer pre-designed templates and customizable elements.

Example of an infographic. Source: Delante

Data Sources

Access to reliable and diverse data sources is essential. Government agencies, research institutions, and open data platforms like Data.gov provide datasets for various topics. Explore these sources to find data that aligns with your storytelling goals or conduct your research and create original data sets.

By leveraging these tools and resources, you can enhance your data storytelling capabilities and create narratives that are both informative and engaging.

Data storytelling is not a mere presentation of numbers, it’s a craft that breathes life into data, bridging the gap between raw information and human understanding. It has the power to drive change, foster engagement, and make data accessible to all.

Crafting a data story is a process that involves data collection, analysis, narrative creation, visual integration, and thoughtful presentation. Thanks to this process you can ensure effectiveness in delivering messages to your users.

As you master the art of data storytelling, remember the potential it holds to inspire, and influence. Use it creatively and wisely to leave a lasting impact.