Storytelling with Data: How to Communicate with Data

Written by Coursera Staff • Updated on

Storytelling with data is an effective way to engage an audience using creative and insightful content. Explore data storytelling and the steps necessary to make a presentation that works.

[Featured Image] A data analyst reviews various data insights in preparation for a presentation using storytelling with data to communicate critical metrics to company leadership.

Key takeaways

Storytelling with data utilizes narratives and visuals to present your data in an engaging way, enabling your audience to gain valuable insights.

  • Presenting data with a story rather than solely delivering numbers makes it easier for your audience to retain key information. 

  • Use graphs, charts, and maps to help visually tell a story using data.

Discover how you can use data to tell compelling and informative stories. If you’re ready to get started, earn a Google Data Analytics Professional Certificate, where you can build in-demand skills, including how to prep data, analyze and visualize it, and use AI-powered tools for informative visualizations.

Why is storytelling with data important?

Data storytelling is important because it provides meaning and context to data sets. It’s an effective way to explain the “why” behind the data’s “how,” and it gives people the chance to interact with the data meaningfully.

Businesses use two critical types of data: quantitative and qualitative data.

Quantitative data refers to the raw numbers of social media interactions and website traffic, for instance. It’s collected year over year to identify patterns, trends, and other data insights a business can use to create high-level plans and campaigns.

Qualitative data, on the other hand, involves the context around the quantitative data. For example, you might see a spike in interaction due to one of your marketing ads going viral. Those numbers are quantitative. The reason for the spike is the qualitative data: is it positive or negative feedback? Why did this ad have the response it did? Can you leverage this information for future campaigns?

Data storytelling blends these two data types into a compelling narrative that provides context and purpose to the raw numbers. Humans already use stories to communicate ideas. Data storytelling is similar in nature, turning data sets into an actionable source of information that connects meaningfully with an audience. That audience can be internal, such as stakeholders, or external, such as potential new customers.

Data storytelling gives a voice to the data sets your company collects. Without context around the data, it’s tough to parse out why the numbers matter or determine the most effective course of action. A spike in website traffic can give you helpful insight if you can tell what caused it or how to repeat it. Data storytelling gives meaning to numbers in a way that makes it much easier to use as part of a business’s strategic plan.

Data storytelling examples

You can apply data storytelling techniques across industries and different contexts to help humanize data. For example, a human resources director can use data storytelling to present a narrative surrounding the importance of successful employee onboarding and the various steps involved, and use insights presented in data visualizations to support the details in the story. Or, a senior staff member at a health care organization could use data storytelling to craft a story regarding successful patient outcomes pertaining to a new treatment strategy, with a bar chart that compares treatment methods.

Data storytelling steps

To use data storytelling effectively, consider the following steps:

1. Identify your audience.

Data storytelling works when you tailor the narrative to the audience you’re presenting to. For example, a marketing team wouldn’t be interested in a narrative that interprets data through an IT support lens. Ask yourself: Who is this story for? What do they care about? What are their pain points? Why should they care? Consider taking the time to understand the people in your target audience, find out what technical information matters to them, and use that information to create a narrative highlighting what they care about.

2. Create a narrative.

Even though this type of narrative centers on data, the elements are the same as any other story. You need a setting, conflict, resolution, and the “characters” involved. For purposes of data storytelling, your characters are your target audience. Next, outline the setting. Let’s say you’re creating a story about the viral marketing ad referenced earlier. The setting might be the two weeks before and after the ad is published. The conflict, then, is how the ad went viral and why. Finally, the resolution would be what you recommend happens next based on the data you pulled. 

For example, if the ad went viral for negative reasons, you’ll want to highlight what your audience didn’t like and recommend how your business can repair and do better next time. If the response was actually positive, you’ll want to outline what was good about the ad and how you can leverage it into tremendous success. 

3. Organize your visualizations.

Visualizations are a key part of a data storytelling presentation. You can use graphs, images, or charts, but they need to be visually engaging, easy to read, and focused on the critical pieces of your data set. Use them to emphasize and highlight the significant moments of your presentation. For example, you might make a line chart to show the spike in interaction around the viral marketing ad and then follow that up with a collage of people’s comments to highlight the positive or negative aspects of the interaction. Stats are a great option to reinforce what you want to highlight, such as why virality matters and how it’s affected other businesses’ growth. 

4. Test out your presentation.

Once you’ve created your narrative and built visualizations to support it, it’s time to create a draft presentation. Practice in front of someone who understands the topic. This run-through allows you to note any parts of your story that might be unclear and prep for any questions that come up. Plus, the chance to deliver your presentation out loud might give you insight into pieces you missed or want to highlight.

5. Make changes and finalize.

Take the feedback you received and change your presentation as desired. Once you feel confident in the presentation, you’re ready to finalize it. Remember, the goal is to craft a story illustrating why the data matters and how to take action with the information. Once you have all of those pieces, you’ll have an effective data storytelling presentation.

Read more: 5 Types of Data Visualization

Explore our free resources for data analysts

Interested in learning more about storytelling with data and other valuable data analyst skills? Explore some of our free resources, like our LinkedIn newsletter, Career Chat.

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