Surveys storytelling: Turning data into meaningful narratives

While data scientists may take delight in the increasing ease of accessing numbers (along with the tools that transform them into valuable insights), numbers possess an inherent limitation for one fundamental reason: although they can unveil what is happening, they fail to explain why it holds significance.

Certainly, you can present numbers and assume they will speak for themselves. However, this presents a major risk when managing a business—particularly when those numbers could be transformed into an engaging narrative instead.

This brings us to data storytelling.

Instead of depending solely on numbers, data storytelling leverages their power to enhance communication, strengthen relationships, generate insights, and drive results.

In this blog, we will closely examine what market research storytelling entails and why it is essential. You will also discover what makes a strong data story, tips for crafting narratives using data, and various tools, services, and resources to help achieve your organizational objectives.

What is data storytelling?

Storytelling with data integrates data, visuals, and narrative components to captivate audiences and clarify concepts. Numbers hold great power. However, they can also feel overwhelming and inaccessible. This is where data-driven storytelling plays a crucial role. As a natural extension of the big data revolution, data storytelling shapes numbers into a clear and structured narrative tailored to resonate with a particular audience.

Data stories vs. data visualizations

Curious about what sets data storytelling apart from data visualization? Data visualizations are merely one component of a broader data story, serving as aids in communicating a more extensive narrative. While data visualizations help illustrate specific points, data storytelling also incorporates industry or subject expertise and communication skills to transform data analysis and visual elements into a narrative that explains the who, what, why, and how of a larger story.

For instance, a set of data visualizations may depict how sales trends have shifted for a particular product line over time. While these data presentation may clearly indicate a change, a data story would provide context by relating these trends to factors such as marketing efforts or supply chain issues that have affected inventory levels.

Identifying the Right Story in Your Data

The initial step is to determine the story you want to tell. This requires an understanding of your data, identifying patterns, insights, and relationships within it. Once you grasp your dataset, you can start identifying trends and patterns. Analytical techniques can also help uncover hidden insights. Additionally, consider the context of the data—who generated it and for what purpose. This understanding will help shape the narratives you can construct from it. Two key analytical techniques can reveal data insights:

Exploratory vs. Explanatory Data Analysis

Exploratory analysis utilizes visual methods to uncover patterns and relationships within data. It involves tasks such as data cleaning, generating graphs and charts, conducting basic statistical tests, and identifying correlations. This type of analysis helps surface potential questions for further examination. It almost feels like cracking a code in a thrilling detective novel—embrace it if you aspire to be the Sherlock Holmes of data analysis!

Explanatory analysis delves deeper into the data to clarify or predict specific outcomes. It relies heavily on statistical models such as linear regression, logistic regression, or time series analysis. Unlike exploratory analysis, explanatory analysis begins with a clearly defined research question or hypothesis. This approach helps assess the strength of relationships between variables, offering an understandable data interpretation of findings. Unlike traditional storytelling, your audience will appreciate gaining clarity through survey analysis on what you are trying to communicate.

Why Is Data Storytelling Important?

Humans have been telling stories for over 30,000 years, not merely for entertainment but also to share knowledge. Effective storytelling aids in comprehension and retention. It also makes data-driven conclusions more persuasive and impactful, ensuring that their implications are clear to a wider audience. Furthermore, storytelling enhances collaboration, teamwork, and decision-making by ensuring that everyone is aligned and engaged.

The same advantages apply to research storytelling. Rather than overwhelming your customers with an excess of numbers, data storytelling provides survey insights that directly address their questions, needs, and objectives. Combining numbers with narrative elements also creates a symbiotic effect. Numbers reinforce claims, enhance credibility, and foster trust. In addition to helping your brand stand out with consumers, data storytelling can increase awareness and capture the attention of media, influencers, and new audiences.

Moreover, data storytelling is a versatile tool for businesses aiming to maximize impact with minimal resources. It can be adapted for various formats and communication channels—including case studies, brochures, white papers, pitch decks, social media content, and website pages.

How to tell a good data story

While having relevant and interesting information to share is important, it’s far from the only factor that determines whether a story is “good” or “bad.” Other aspects of good stories include having a beginning, middle, and end (i.e., they’re not merely anecdotal); they have meaning; they’re thoughtfully structured and have a good ending. Here are a few storytelling techniques you can take:

1. Find the stories within your data

Two of Michelangelo's most famous quotes are, “I saw the angel in the marble and carved until I set him free,” and “Every block of stone has a statue inside it, and it is the task of the sculpture to discover it.”

With the right metrics and analytics, the stories worth telling already exist within your data. It’s your job to find them. The importance of knowing your audience cannot be overstated. The more you know about your audience, the better you’ll be able to identify the most meaningful data and “carve” it into the most compelling narrative.

The following questions can help you uncover a narrative within your data:

• Who is your target audience?

• What are your goals?

• What is the data telling you?

Sometimes, a compelling story will emerge from the data because of its obvious potential. In other cases, you must dig deeper into meaningful relationships, patterns, and themes.

2. Create and structure your narrative

How you structure the narrative is instrumental to making your data meaningful. After you’ve honed in on the story you want to tell and the data sets you’ll use to tell it, it’s time to work on your narrative research.

Traditional story plot lines contain exposition, rising action, climax, falling action, and resolution. Compelling data stories also have “plots” crafted to support a satisfying audience journey. Typical elements include an introduction with a hook, background and context, a conflict or pain point, and resolution.

In other words, it’s not enough to provide useful data. You must also strategically organize that data in a way that keeps the audience engaged and the story moving forward to an actionable conclusion.

3. Leverage visuals

Earlier, we touched on the difference between data storytelling and data visualization. When integrated into data storytelling, visuals like line charts, bar charts, tables, maps, infographics, and animations can amplify your message's impact. Not sure which data points will best translate to visualizing data? Common data-driven visualizations focus on trends, comparisons, rankings, and statistical relationships. Counterintuitive data can help create stories that are especially evocative.

4. Use high-quality, relevant data

While high-quality, relevant data adds value, low-quality and irrelevant data can have the opposite impact. Not only will it add up to an ineffective data story, but it also jeopardizes your relationship with your target audience. After all, if you waste their time with outdated, inaccurate data or content that doesn't apply to them, you’ll lose their trust.

5. Be human

While data can be dense, scientific, and technical, the information you convey should be understandable and accessible. This is heavily reliant on your audience. After all, a target audience made up of rocket science experts will have a different baseline level of comprehension than one made up of middle schoolers. This brings us back to your audience, which should dictate what you say and how you say it.

That said, your audience is human, presumably. Regardless of the specifics of your target audience, emotions play a pivotal role in all data-driven storytelling. When turning numbers into a narrative, be sure to put yourself in the shoes of your audience: what will speak to their hearts and minds?

There’s no single-best way to deliver information or visualize data. Experimenting with different and unique visuals can help you better understand how your data looks from different viewpoints.

Spotify Wrapped is a masterclass in data storytelling

One of the most well-known and successful examples of data storytelling is Spotify Wrapped. Every year, Spotify curates personalized listening insights for its users, transforming raw data into an engaging, shareable experience.

Spotify uses listening data to craft a unique story for each user, highlighting their top songs, artists, genres, and total minutes streamed. This personal connection makes the data more meaningful. The experience is presented as a journey through the year, breaking data into digestible moments like "Your Top Artist of the Year" or "Your Musical Personality." This structured storytelling approach keeps users engaged. Wrapped features colorful graphics, animations, and interactive slides, making data visually engaging and easy to consume.

Spotify taps into nostalgia and personal memories, creating a sense of excitement as users relive their musical year. The Wrapped campaign is designed to be highly shareable on social media. Custom graphics and social integration encourage users to post their results, turning them into brand ambassadors. Wrapped boosts user engagement, retention, and brand affinity while attracting new users who want to be part of the experience. It also provides Spotify with valuable behavioral insights.

Spotify Wrapped transforms user data into a fun, engaging, and viral campaign that strengthens customer relationships while reinforcing Spotify’s brand identity.

Use your data to build meaningful stories

One of the most exciting things about data-driven storytelling in marketing is that anyone can tell a great narrative as long as they have high-quality information. With the right business intelligence tools as offered by Xcel Global Panel, you can craft an engaging story that drives your organization to success.