Storytelling is one of the most powerful tools you can use to connect with people or persuade them to take action. You can never go wrong with it whether you’re a startup founder pitching to investors or a content marketer helping businesses build trust with their customers. And that’s because great stories are persuasive.
What makes storytelling even more persuasive is when you pair it with data. It becomes irresistible.
Spotify is one company that gets data storytelling right with “Wrapped”, a summary of the music their users listened to throughout the year.
When they released 2020 “Wrapped”, their mobile app download increased by 21% in the first week. What made the content work so well was that it merged beautiful storytelling with numbers in a way that’s exciting.
Let me show you how to find the sweet spot between storytelling and data.
What is Data Storytelling?
Data storytelling is the process of making sense of numbers in a way that’s relatable to your audience.
It combines data and storytelling to make your narrative more compelling and give your audience clear and valuable insights to help them improve the quality of decisions.
For example, say you have the analytics from a marketing campaign you just finished.
Data stories can help you compare the results with a previous one and give you an idea of how to optimize a future campaign and get better results.
Benefits of data storytelling
I saw this poll from Animalz on LinkedIn where they asked about the best hook people have ever written. 52% of the people that took the poll picked data as the go-to hook strategy.
Data makes your work credible and an authority in your field. That’s why B2B companies race to publish reports at the end of the year.
For instance, take a look at this 2021 Content Marketing Benchmarking.
The entire report compared the stats from 2019/2020 with 2020/2021.
In the industry growth rates section, the writer started by listing the growth rate in 2021 and then compared it with the numbers in 2020. Afterwards, they concluded that the numbers had dropped and finally reinforced their conclusion by calculating the mean growth rate for each industry.
Looking through the thoroughness of their data story, the context, and the visuals, readers can conclude that they are an authority in their industry.
Major Data Storytelling Skills that Anyone Needs
Data storytelling goes beyond presenting raw numbers and charts. It involves crafting a compelling narrative that engages the audience and conveys the key messages hidden within the data. Here are some major data storytelling skills:
Data Interpretation: You need the ability to understand and analyze data, identify patterns, trends, and outliers, and extract valuable insights. It’s important to go beyond the surface-level analysis and dive deep into the data to uncover its underlying story.
Storytelling Structure: A well-structured data story follows a logical flow and engages the audience from beginning to end. It typically consists of an introduction that sets the context, a clear narrative arc with a beginning, middle, and end, and a conclusion that highlights the main insights or recommendations. Understanding the principles of storytelling, such as creating suspense, building tension, and providing resolution, can greatly enhance the impact of a data story.
Audience Understanding: Tailoring the data story to the intended audience is crucial for effective communication. It’s important to understand the audience’s level of data literacy, their background knowledge, and their specific interests and needs. This understanding allows you to present the data in a way that resonates with the audience and makes it relatable and relevant to their context.
Visual Communication: This skill includes selecting the most appropriate chart types, using color and design principles effectively, and presenting data in a visually intuitive manner. Visuals should support and enhance the narrative, making complex information more accessible and engaging.
Simplification and Focus: Data storytelling involves distilling complex data and insights into simple, digestible messages. It requires the skill of simplification, removing unnecessary details and jargon, and focusing on the most relevant and impactful findings. Keeping the story concise and focused helps to maintain the audience’s attention and ensures that the key takeaways are effectively communicated.
Now let me show you how you can create your own data story.
4 Steps to Tell an Effective Data Story
Creating a data story can look really intimidating, especially if you don’t have a process. But these 4 steps will guide you.
1. Know your audience
The first step is to find out who your audience is and their needs. Ask questions like: What are their pain points? What are they looking for? Is the data you’re collecting relevant to their needs?
After figuring this out, you have to discover the best way to present this data to them without confusing them. Consider their psychographics and their level of understanding of the subject matter.
Let’s say your target audience is C-level executives in the B2B space. Consider that specific group of people oversee several major projects and spread their attention across multiple teams. So, any data story or visualization you share needs to get straight to the point. Therefore, you should show them the bottom line up front aka BLUF.
2. Find a story narrative
Next, find a story worth telling.
The narrative depends on your goal for the data story. Is it an informative piece? Do you want to create top of mind awareness, or position your company or product in a certain way? Is it to nudge your audience down the funnel and then turn them into customers?
After finding the end goal for your data story, now you can craft the narrative around that goal. The narrative is the structure that guides your audience to the end goal.
Compare two things
This concept usually works well if you’re trying to show your audience why one thing is better than the other. This type of narrative shows your audience the possible outcomes of choosing between two things.
It could be a comparison of two tools, strategies, or even two email subject lines. A typical example is this blog post by Backlinko, which compares Ahrefs and Semrush.
Tell a story about trends
Telling a trend story shows your audience the flow or the direction of something. This narrative gives your audience the likely outcomes based on past results or the present situation.
For example, you could show your audience the effect of video marketing on the overall marketing strategy of a startup in the past 3 years. You can then make a prediction for the future based on the data.
An example is this post by HubSpot talking about marketing trends of 2022.
Start from audience’s pain point then expand
This type of narrative helps you tell a story that links your audience’s pain point to something bigger. The story uses their pain point as the starting point and then shows how it’s connected to other scenarios.
Let’s say you want to tell a story of how email marketing contributes to the revenue. Then, you use email marketing as the reference point to show how it influences other acquisition channels like social media, organic search, or paid ads to contribute to the revenue.
This post about the effect of SEO on other marketing channels by Moz is an example of this method. If you’re a SaaS company, you can show a customer who pays for a singular feature the benefit of paying for other features. You can also reverse this story narrative and start with a broad scenario and then narrow it down to that audience’s pain point.
Show the interaction between two scenarios
This tactic involves showing the connection between two scenarios. The goal is to show how one thing influences another. A typical example is to show the effect of your SEO strategy on a PPC campaign.
There are tons of story narratives to pick from and you can always come up with any story narrative as long as it helps you tell your data story. You can also combine these different story narratives to tell your data story as long as it connects with your audience.
3. Find accurate data
The accuracy of the data and its relevance to the story are important. You can get accurate data from trusted sources, like SMEs, industry leaders, PrimoStats, or your proprietary data.
Due to tight deadlines and inadequate resources, storytellers and marketers often resort to random data. Fact checking is one way to ensure you’re quoting correct data. Sometimes that process could mean hours of google searching or using a fact checking tool. But it’s better to do that than misrepresenting data to your audience.
Data relevance involves connecting with the reader. You want to be intentional with your data. It speaks to how close your data matches the audience’s interests.
For example, say you’re writing a story for the prospects in the marketing funnel of a product.
Data relevance changes at the different stages of the funnel. While they are all leads in the marketing funnel, the data has to match their pain point at every step of the way.
4. Create visuals to enhance your story
Staring at spreadsheets or tables with numbers alone is exhausting. And in cases where you have a large amount of data, your audience can get lost in figuring out the important parts.
That’s why you need to use visuals to present your data story. Visuals bring your story to life. Take the content marketing agency Foundation, for example. They always design unique visuals to aid their data storytelling.
If you create unique visuals for your data story, it will make your story come to life. Also, creating visuals helps skimmers get the gist of the story if they are short on time.
There are different types of visual formats, including:
- Bar graphs
- Pie charts
- Road maps
There’s no need to learn how to use a complex data visualization tool when you’re just starting out. A few clicks on Google Sheets will get the job done. Check out the steps below.
Step 1: Highlight the set of data you want to visualize.
Step 2: Click ‘Insert’ on the upper menu bar.
Step 3: Select your desired format.
Step 4: Customize.
Data Storytelling Trends: Unveiling the Narrative Power of Data
As we step into the future, several trends are shaping data storytelling and revolutionizing how businesses communicate their insights. Let’s see the trends that are defining the narrative power of data.
Interactive Data Experiences
Traditional data presentations are evolving into interactive experiences. Audiences now crave engagement and participation. Data visualizations that allow users to explore and manipulate information firsthand are gaining traction. Interactive dashboards, immersive charts, and dynamic graphs create an environment where the audience becomes an active part of the data story.
Artificial Intelligence Integration
The integration of artificial intelligence is taking data storytelling to new heights. AI algorithms can analyze vast datasets, identify patterns, and generate insights automatically. This trend is not just about automating processes but also about enhancing the depth and speed of storytelling. AI-driven data narratives can provide real-time updates and personalized content tailored to individual preferences.
Augmented Reality in Data Visualization
Imagine being able to walk through your data. Augmented reality is bringing this concept to life. AR in data visualization allows users to physically interact with data in three-dimensional space. This immersive experience adds a layer of engagement, making data storytelling more memorable and impactful.
Ethical Data Storytelling
With increased awareness of data privacy and ethics, there is a growing demand for transparent and ethical data storytelling. Brands are focusing on building trust by clearly communicating how data is collected, used, and protected. Ethical considerations are becoming integral to the narrative, ensuring that the story aligns with values and respects user privacy.
Mobile-First Data Storytelling
As mobile devices continue to dominate online interactions, data storytelling is adapting to a mobile-first approach. Content must be optimized for smaller screens, and the narrative should be concise yet compelling. Mobile-friendly data visualizations and storytelling formats are becoming crucial for reaching and engaging diverse audiences.
Data Storytelling Example: Transforming Numbers into Narratives
To grasp the impact of data storytelling, let’s explore a real-world example that showcases how numbers can be transformed into compelling narratives.
Case Study: “Healthier Habits, Healthier Lives”
Background: A health and wellness company aimed to encourage healthier lifestyle choices among its users. They collected data on user habits, exercise routines, and dietary preferences.
Data Visualization: Instead of presenting raw data, the company created an interactive dashboard. Users could input their habits, and the dashboard dynamically generated personalized recommendations based on the aggregated data.
Narrative Elements: The data story unfolded through a series of success stories, illustrating how individuals transformed their lives by adopting healthier habits. Each success story was backed by data, showcasing improvements in physical health, mood, and overall well-being.
Impact: The personalized and narrative-driven approach led to a significant increase in user engagement. Users felt a connection to the stories and were motivated to make positive changes in their lives. The company not only improved its user retention but also positioned itself as a brand that cares about its users’ holistic well-being.
Enhance Your Story With Data
Stories are powerful. They can help you engage, entertain, and connect with your audience. With the right data, your stories can help you meet your brand’s goals.
About the Author
Moyo Oluwatuyi is a content marketer focused on helping SaaS and tech brands grow and achieve their marketing and revenue goals. You can follow me on Twitter or check out my website to know more about my services.