5 Tips for Better Data Storytelling

What is data storytelling?

Data storytelling is a powerful approach to communicating data points in a form of a narrative that resonates with your audience and inspires the need for action. Data storytelling usually involves a combination of data, visuals, and a compelling story.

Why is data storytelling important for marketers?

While having access to raw data is great, it’s the ability to turn it into influential messages that matters in the end. 

Whether you are communicating with a client, investors, or internal stakeholders, storytelling makes your data meaningful. And if communicated effectively, it can hugely impact your intended audience. 

What makes a good data story?

If you can show the power of the stats, you have a better chance of engaging your audience. And a lot of the time that means making an emotional connection through storytelling with your data.  

Why do people do what they do online? 

Or why do they say what they say or contribute to a conversation?

A data point on its own is not as important; context turns data points into insights. Remember the famous quote by Maya Angelou, "People will forget what you said. People will forget what you did. But people will never forget how you made them feel."

So how do we tell better stories with data?

Here are our best tips for turning data points into stories. 

1. Start with a question

You can approach the process of discovery for your research project in two different ways. First, you may want to start with a general idea. Say, you are looking to explore the broader topic of veganism. Then your general question will be, “How do people talk about veganism online?”

In case you are looking to discover insights specific to a particular brand or brands, you may want to narrow your question down to: “Which vegan makeup brands generate the most conversation online?”

While studying a defined set of brands or topics is great for competitive research, a broader question will often return unexpected, surprising insights.

Also context is important. Whether you are researching a broad conversation or niche topic, ask yourself if any recent events might have had an impact on the social conversation online. And depending on the nature of your research, you may want to include or exclude those keywords from your search query.

Suppose you wanted to research the dairy industry dating back five years, focusing on key products like milk, cheese, and butter. In that case, you’d be confronted with millions of irrelevant mentions of “Butter”, which coincidentally is also the name of the hit song from BTS that broke all charts in 2021.

2. Know your audience

Too often we jump straight to presenting our ideas without ever thinking about the person who is going to be on the receiving end of that. And it could be anything from an exhausting work meeting with no breaks and no clear agenda, DJs switching songs every 20 seconds, or professors running three-hour-long college classes and their effects on students with ADHD.

Here’s real feedback from a subreddit on ADHD:

When thinking about the outcomes of a project, you should always think about your audience first. Who’s going to read your insights, and what are they looking to learn?

Knowing what your intended reader is interested in can help shape your narrative further. 

Some questions you may want to ask yourself:

• What problem is your research solving for your audience? 
• How is your audience going to discover these insights?
• Where are they going to read them? What is the medium and their preferred format?
• What time are they most likely to consume your insights?
• What tone of voice does your audience prefer: edgy, fun, professional? Do they use slang?

In other words, tailoring your data story to your audience can increase the chances of your message being understood and perceived in the way you want it to. 

How do you make sure to keep your audience in mind?

Knowing your audience means you know how they prefer to consume content.

Here are just a few metrics for you to consider and benchmark against:

• As a content format, video is on the rise. How does your audience react to videos?
• According to research, viewers prefer videos between three and six minutes. Do you know the ideal video length for your audience?
• There are currently 462.7 million global podcast listeners, and that number is expected to hit 500 million before the end of 2024. Does your audience listen to podcasts? And is audio a format to consider? 
• There are over 4.3 billion daily email users. How responsive is your audience to emails?
• Tuesdays see the highest email open rates globally. What does this metric look like for your brand or company?
• What questions is your audience asking when looking for information online? Your presentation can be much more effective if you structure your findings around the questions your audience is already asking. Tools like Buzzsumo’s Question Analyzer and AnswerThePublic can help focus your narrative. 

Keeping your audience’s behavior in mind when sharing your insights, will yield in growing the engagement around your story. 

For example, we at Brandwatch produce different types of format to cater to different preferences of our audiences. You may see us telling our stories in the format of short webinars, reports, or quick blog recaps. In fact, multi-format content is one of the biggest digital marketing trends in 2023. 

Keep in mind, you can’t reach your audience or capture their attention without knowing what they need. And knowing what your audience’s goals are enables you to leave them with something valuable.

So before you go any further, ask yourself who is your target audience, and what makes them tick? 

3. Tell data stories that others want to share

If it’s boring to write or create, it’s boring to read or watch. According to recent studies, the average human has an attention span of just 8.25 seconds – 4.25 seconds less than in 2000. And you need to make the time count when delivering your insights.

A good approach is to ask: “What’s in it for the reader?” “What can be done with this finding?” “How will your insights help your audience make smarter [business] decisions?”

Here are five popular data-driven narratives you can use in data storytelling:

• Trends (Here’s a Brandwatch example.)
• Rank order (Here’s a Brandwatch example.)
• Comparisons (Here’s a Brandwatch example.)
• Relationships: correlations and causation (Here’s a Brandwatch example.)
• Surprising or counterintuitive data (Here’s a Brandwatch example.)

The one thing to remember is that a good marketing story needs to encourage action. And nothing inspires readers more than real-life examples that demonstrate the points in your narrative.

Using verbatim social feedback to illustrate your findings

Finding and including verbatim examples into your story is a great way to make an emotional connection with your audience.  

People tend to gravitate towards authenticity, and showing real emotions behind something can make your points highly persuasive.

Ask yourself: How does your story make people feel?

For example, if you are telling a story about vegan products and butter specifically, you may want to highlight a few consumers and their opinions in your presentation. 

In this post, a consumer is sharing concerns over some of the ingredients commonly used in non-dairy butter and gets upvotes from other people who seem to agree with this viewpoint. 

"Verbatim is impactful. Where high level stakeholders are involved, they don’t always have time to read and digest the whole report, but if you’ve got recurring themes with example mentions they add more color and detail. It’s the same story, but with a more human angle." – Peter Fairfax, Data Science Manager, Brandwatch

Detailed conversation adds granularity to the story you are telling. Verbatim quotes will paint a truer picture of consumer needs and wants.

4. Provide the right kind of evidence

Sometimes we have preconceived notions about a topic or area of interest, and while looking to confirm our bias, we might miss on other important insights backed up by data. Keep an open mind when researching a topic, and broaden your search where possible to find unbiased insights.

What do you need to look out for when analyzing subtopics in social conversation?

When building out a narrative, you need to prove or disprove your hypotheses. Asking the following questions can help you navigate the online conversation:

• What is the size of the conversation on social media about your topic? Is it two people or tens of thousands discussing this?
• How has the conversation changed or evolved over time? Has the volume of mentions increased, decreased, or remained the same? Was the shift slight, sharp, or steady?
• Did a short-term event cause a change, or was it gradual? Was there a spike in conversation on a particular day? Are we looking at a short-term fad, or does the topic keep trending upward?
• When did the change occur? What does a month’s worth of data look like compared to a longer date range?
• What drove peaks? Can you identify specific events that might have sparked the conversation?
• Where did the conversation take place? Were consumers talking about the topic based in a specific region? Were some social channels more popular than others? 
• What was the overall sentiment of the conversation about the topic?
• What drove positive/negative sentiment about this topic?

5. Pick the right tool for the job

Finally, automation is your friend. There is just so much data out there, and picking the right tool can make your analysis easier, highlighting the stories that make a bigger impact. 

One of the main benefits of using Consumer Research is that you have many different dashboards and tools at your disposal that enable you to slice and dice your social data further when searching for valuable insights.