Data Storytelling: Telling a Great Story with Data
Data Storytelling: Telling a Great Story with Data
What is data storytelling?
Why data storytelling matters
Data stories vs data visualizations
Key elements of effective data storytelling
How to craft a story with data
Best practices for data storytelling
Real-world examples and use cases of data storytelling
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Data Storytelling: Telling a Great Story with Data
Businesses rely on data to make informed decisions, but the complexity of large data sets can make it challenging for anyone to access and interpret the data. This is where data storytelling techniques become valuable. By crafting a narrative around your data and using visual representations, this approach translates raw data into easily digestible presentations for your entire team, no matter their background.
Data storytelling goes beyond just sharing your data; it places information within the broader context of your business to derive greater meaning and value so you can generate more effective insights and take action.
For CTOs and CIOs, it helps your organization use data for smart decisions and encourages teamwork between technical and non-technical teams. For data analysts, it’s a way to increase your influence—making sure your work is not only understood but also essential for shaping business strategy.
What is data storytelling?
Data storytelling is the process of developing and sharing a written or verbal narrative about your complex business data using analytics and visualization. It enables you and others to better understand your data, offering more context than traditional data analysis and presenting data in a more approachable and compelling format.
Why data storytelling matters
The storytelling of data pairs familiar communication techniques with raw data and visual aids to make data more accessible to all individuals, regardless of their professional background. It enables you to consider your audience and the context of your data to develop deeper, more meaningful insights your audience can understand and implement.
Data storytelling also makes your raw data more “human” by appealing to your audience’s feelings, values, and senses. Instead of a traditional one-sided report, storytelling data is a shared interactive experience. The storytelling elements and visualizations make it more engaging for your audience. They can see the data supporting your story as it’s shared through easy-to-comprehend tables, graphs, and charts. Not only does this help hold their interest, but it also allows them to generate their own insights and conclusions based on the data presented.
Benefits of telling a story with data
With data storytelling, you can view your data in its broader business context, uncovering relevant and meaningful insights that raw data or simple analysis might miss. By focusing on the most relevant data points and presenting them in an engaging format, your audience can easily understand and act on the information while not being overwhelmed with too much data. With data storytelling, you’ll see benefits like:
- People without technical or analytical backgrounds can interpret and find meaning from complex data.
- Greater value from data by adding narrative and visual context, increasing the relevance for your specific audience and industry.
- Growth of a data-driven work culture since more people are comfortable using data in their roles.
- Recognizing new trends or patterns from your data, allowing you to take advantage of new opportunities.
- Improved decision-making due to increased understanding of complex data and data-supported solutions.
Data stories vs data visualizations
Data stories and data visualizations are two different ways to understand and share raw data. Data visualizations show information in easy-to-understand graphical formats, like charts or graphs, while storytelling adds context and a narrative that give raw numbers meaning that people can act on.
Visualizations make it easier to identify relationships within the data, such as the correlation between different metrics or the hierarchical or organizational relationships of your data. You can create data visualizations for specific purposes, such as monitoring marketing campaign ROI over time. But on their own, visualizations don’t provide the broader story necessary to explain the why behind the numbers.
Data storytelling combines visualizations to support the data with narrative to provide greater context and explain a larger message. With data storytelling, your audience can learn not only why something is happening but also why it matters, and what actions they can take to achieve their desired results. By adding storytelling, you add another layer of value to the data, which creates a comprehensive picture and an emotional connection that encourages your audience to take action.
Key elements of effective data storytelling
A data story has three main elements: your data, narrative, and visuals.
Choosing the right data for your story
The data you choose for your story should support the point you want to make or the questions you want to answer. For example, if you’re investigating factors that affect customer experience, data from satisfaction surveys and customer support metrics would be relevant, while sales data would not. Since data is the foundation of data storytelling, think about which sources will provide key information and the type of analysis best suited for your needs (such as recommending actions, understanding past events, or predicting future trends).
Crafting a compelling narrative with data
Your narrative is how you will share the story of your data with others. You can present data storytelling verbally, through informal meetings or larger presentations, or through written reports to share. Regardless of your method of communication, you need to share your findings, provide context for the data, and recommend next steps through a narrative that captures your audience’s attention and motivates them to act.
Using visuals and data visualization techniques
Charts, infographics, tables, and other visual elements allow you to share your data story more easily. Not only is a bar graph easier to interpret than raw numbers, but it’s also more memorable and gets your point across more clearly and effectively.
How to craft a story with data
To create a successful and valuable data story, follow these five steps.
1. Define your objective and audience
Before you can craft your story, you need to know what you want to show with the data. For instance, you might want to study how sales related to different age groups affects your product lines and adjust your marketing efforts accordingly.
You also need to identify your data story’s audience. Are you delivering it to data scientists, a marketing team, HR managers, C-suite executives, or other stakeholders? Think about their roles, their experience with data interpretation, and their overall expectations, as this will help you choose the type of language and the data points to use.
2. Collect your data
Once you know your goals and audience expectations, you can collect the relevant data for your story. For example, if you want to improve the user experience on your company’s website, you’ll want to collect data on page load speeds, task success rates, and time-on-task, to name a few. Sticking to the most relevant key performance indicators will keep your data storytelling clear and focused.
3. Analyze and interpret the data
After selecting your data, you need to analyze it to develop actionable insights. Data analytics and BI platforms simplify this step and can help you identify patterns or opportunities from your data that people may not see on their own. In this step, ask yourself what the data shows and explore the relationships between data points. Are the results what you expected, and do they reflect the story you’re trying to tell? Compare the results to ensure you’re using the most relevant findings in your data storytelling.
4. Create visualizations
Data visualizations and data storytelling go hand-in-hand. Visuals are an effective way to translate complex information into a more accessible format to share with your audience. However, it’s important to choose the right visuals for your data. Think about the type of visualization that works best with your data points. Would a bar or pie chart tell your data story most effectively or is a table or heatmap more appropriate?
Here’s one example: If you’re telling a data story about product sales trends over time, you might use a line chart that shows both time information and total sales. This will help you see how sales of different products changed over months or quarters. And pay attention to the colors and labels you use in your visualizations. You want to make sure data is easy to differentiate from a distance if you’re making a presentation.
You might also want to use interactive visuals for your data storytelling, such as real-time dashboards or other data exploration tools, to help your audience understand and engage better. Dashboards let you customize, drill down, and filter your data visualizations so you can focus on the most relevant details for your audience.
5. Develop the narrative
Finally, you need to develop your data storytelling narrative. Start by providing your audience with context. Share relevant information about your customers and business, along with trends in your industry or any economic or market conditions that they may not be familiar with. This context can help them better understand the data. Then, describe the problem you’re facing and wat your data analysis has revealed before proposing your solution.
To tell effective data stories, you may need to first build the data literacy skills of your team or organization. This means learning to understand and interpret statistical data and visualizations, as well as being able to clearly communicate about what the data shows. Data literacy helps avoid misinterpreting data and maintaining data privacy. You might also consider investing in specialized data storytelling courses or training online to help you master how to tell a compelling story with data.
Best practices for data storytelling
To get the most out of your storytelling data, follow these tips:
Structuring your data story for maximum impact
Your data story should be structured with a clear beginning, middle, and end. Think about who the key players are and the setting of your data. Then, describe the conflict or root problem you’re addressing — or, in cases where there is no conflict, how you can maintain your current performance. Finally, share your solution and the insights your data provides. Creating relevant visualizations for each stage of your narrative can help enhance your story’s impact.
It’s also important to use timely data. With an estimated 402.74 million terabytes of data generated each day, customer information, search intent, and trends can quickly change. If your data is outdated, you could miss key correlations and base decisions on the wrong information. Using a platform that supports real-time data analytics prevents this problem.
Engaging your audience through storytelling techniques
People don’t connect with numbers or statistics as easily as they do with stories, which is why storytelling techniques are essential for emotionally connecting with your audience. Common storytelling frameworks, such as the hero’s journey or the problem-solution-impact structure, can help you create an effective and emotionally compelling story with your data that has a lasting impact.
Like with any other type of story, you may want to edit your data story for clarity and length before presenting it to your audience. This step ensures your data is concise and focuses only on the most relevant and critical data points your audience needs to know. Doing so also helps keep your audience engaged and prevents data overload.
Measuring the success of your data storytelling efforts
Similar to other business operations, you can measure the effectiveness of your data storytelling. Here are a few ways:
- Audience engagement: Collect open-ended feedback or audience surveys about how clear or informative the story was. Also, ask them how relevant and helpful the data or presentation was and what insights they learned.
- Knowledge gain tests: Ask your audience how much they know about the topic before and after you share the data story and measure the difference.
- Insight implementation: Track if your data story’s insights and recommendations are being acted upon. See if there are operational or behavioral changes after your presentation.
Using data responsibly
Be sure to follow ethical data storytelling practices, such as avoiding bias in your data and ensuring data accuracy. You can accomplish this by using diverse data sets and well-trained algorithms, which can reduce bias or adjust data to more accurately reflect underrepresented groups. It’s also key to present data truthfully and without manipulating it to better fit your data story. You’ll also want to be transparent about any shortcomings in your findings and prioritize data privacy.
Real-world examples and use cases of data storytelling
To see how you can use data storytelling in your role, here are a few real-world examples:
Marketing and lead tracking
Use data storytelling to help understand your customers’ behaviors and make the most out of your marketing campaigns. With a data storytelling process, your marketing team can quickly learn what drives people to your website or company through data points like search intent and ads or email campaigns. Data storytelling can help you learn who your leads are and which ones are more likely to become customers, so you can adjust your marketing efforts for higher ROI.
Investment trends for finance companies
With data storytelling, you’ll go a step beyond identifying investment trends and tracking performance to sharing why the investments behave in certain ways and what you can continue to expect. This technique is especially helpful for client relationships because investors want to know the “why” behind their investments’ performance and feel confident about their decisions. Plus, you can easily adjust your data story to reflect the specific needs of your clients, so they’re receiving the most relevant information.
Energy usage and outage data
Data storytelling helps energy companies understand how much energy is being consumed, which groups of customers account for the highest levels, and when demand for energy is at its highest. You can share the story of your energy data through data dashboards, which enable you to track customer consumption, manage energy production, and monitor outages through real-time visualizations. Insights from this data can help you optimize production and delivery, benefiting customers and your bottom line.
HR management
Your internal HR team can also benefit from data storytelling. Understanding employee sentiment and satisfaction is key to reducing attrition and improving workplace productivity. Your HR data story can share findings from employee surveys and data such as your company’s turnover rate, on-time project completion rates, and other relevant metrics. From there, you can suggest data-backed solutions to increase employee engagement and satisfaction or improve performance.
Data storytelling allows you to translate complex data into easily understood narratives, making data more accessible and helping grow a data-driven culture. By pairing storytelling with data analytics, you can develop more relevant insights and take meaningful action to improve your business operations. Want to learn more? Domo helps businesses empower data storytellers through our self-service cloud BI.