At Digital Third Coast, we love original research. By incorporating original research into the content we create, we establish our clients as industry leaders while garnering media attention and brand recognition. It’s an effective digital PR and marketing strategy when you’re looking to secure media coverage.
Whether we’re analyzing search trends, poring through databases, or conducting surveys, we use data to tell a story. By doing so, we create a strong, clear, trustworthy narrative for our clients that also works for journalists.
Storytelling has the power to connect with us on an emotional level, make information memorable, and inspire action. But what happens when you combine the captivating nature of narratives with the facts of data? You get data-driven storytelling, a powerful tool for transforming numbers into content.
Data-driven storytelling uses data in different ways, like analysis, visualization, and informative narratives, to tell compelling stories that are backed by evidence and insights. Data, both qualitative and quantitative, can be mined and presented in much more engaging and approachable ways, like maps, surveys, social media scrapes, and search trend analyses.
There are two types of data: qualitative and quantitative. Qualitative data describes (e.g. “the dog is brown”) while quantitative data focuses on numbers (e.g. “9 in 10 dentists recommend this toothpaste”).
|Non-statistical data that is descriptive and conceptual; allows for datapoints to be categorized based on traits and characteristics
|Statistical data that is descriptive and conceptual; allows for data points to be categorized based on traits and characteristics
If you’ve never combined data and content before, start simple. To get a feel for navigating datasets, we at Digital Third Coast recommend easily accessible tools such as Google Trends to look at search volume trends across the country, as well as Google Analytics (for B2B marketers) for added insights. Government agencies also offer great resources, including Data.gov, the U.S. Census Bureau, and the Bureau of Labor Statistics.
At the core of data-driven storytelling is data analysis. This is where you dive deep into your data, asking questions, looking for patterns or trends, and discovering insights hidden within the numbers.
It’s the detective work that uncovers the “why” behind the “what”.
Data visualization is how you present the data analysis. Visualization takes datasets and turns them into digestible and engaging visuals. Charts, graphs, infographics, and maps bring your data to life, making them easier to understand and remember.
Once you have your data and the visuals, it’s time to tell the story, and this is the narrative. Craft a compelling story around your insights, using facts and visuals to support your message and engage your audience. A good narrative brings data to life and resonates with your audience.
Data-driven storytelling has many strengths, especially its ability to inform, inspire, and influence audiences in an increasingly data-driven world. Data-driven storytelling can increase credibility, provide clarity, engage audiences, and drive decision-making processes.
While data-driven storytelling has benefits, there are also several challenges, including data privacy concerns, the risk of misinterpretation, and the need for specialized skills and resources.
So, what are the main components of data storytelling? To make the most out of data-driven storytelling, there are some additional tips to consider.
Now that you have your data, it’s time to figure out how it relates to the story that you’re looking to tell. Whatever story that is, it should be newsworthy – timely with a human interest angle that makes an impact on readers.
When we say hard data, we mean data that comes from vetted, third-party and authoritative data sources and exists on the internet in its raw, unadulterated form.
Typically, the data stems from existing databases, such as the ones mentioned above (e.g. Data.gov, U.S. Census Bureau). Hard data can also be found in scholarly reports and studies about specific topics.
Oftentimes, hard data is released on an annual basis, so using it to your advantage opens the door to plenty of content opportunities, including yearly comparisons and year-specific pieces.
The best way to get this data to enhance your story is to use the filters to your advantage.
First, identify the scope of the audience you want to focus your data narrative on. Does it represent a specific sector of the population like millennial homeowners or retirees? Once you identify the scope, you can filter the dataset by that demographic information to really customize your narrative.
We recently analyzed cities with the most deeply rooted homeowners in America for a client specializing in active adult communities. We knew that to tell the story, we’d have to know where to look, and the U.S. Census Bureau would have all the insight we needed.
By filtering specifically for owner-occupied homes, we were able to determine areas in which owners not only stayed put the longest (owner-occupied for 30+ years), but also where they were newest (owner-occupied for ten years or less).
Another way to turn existing data into content is to manipulate it. By comparing different elements of pre-existing datasets you can shape a data narrative.
For instance, when we ranked the best cities for newlyweds, we didn’t just look at the percentage of newlyweds in 300+ cities across the country, we also incorporated household income, home cost, affordability score, and dining options.
When we dive even deeper into a dataset and take advantage of things like filters or take the time to weigh elements against each other, we’re able to confidently establish rankings. This system works so well because everybody loves to see where they, or their city or state, fall, rankings tend to perform very well with the media.
Don’t be afraid to use Google Trends or Google Ads to your advantage; these give a reliable look at what any given population is thinking about at that moment.
Before you just throw in a handful of keywords, though, think carefully. What’s the story you’re telling, and which audience are you trying to reach?
Let’s say that I wanted to create a search trends piece about the most popular Christmas movie in each state.
First, I’ll come up with a handful of terms relevant to my story, then put them into Google Ads’ Keyword Planner.
Now that I have my list of keywords, I’ll download them, and then enter them into Google Ads again to determine historical metrics. At face value, these will provide me a look at the number of monthly searches each term has gotten across the country.
But I want to tell a story more interesting and relevant than that. So, I’ll drill down and target each state, adjust the time period, and then find the uniquely popular search term – the one that sees the most traffic – in a separate .csv file.
There you go, I have an authoritative list of the most popular Christmas movies in each state.
Bonus tip: Journalists and readers alike love to see stories about their region or audience. Localizing your data gathered from search trends or hard data sources is a great way to garner local coverage, especially if your story includes a ranking or map. The more local a story, the greater the chance of catching a journalist’s eye.
Surveys are far less regionally specific, but they can tell great stories that point to nationwide trends and are great for evergreen content. This type of research allows you a look into the preferences, attitudes, and behaviors of Americans on a wide variety of topics.
We conduct a number of surveys each month, and they range from the serious (Mental Health at Work) to the silly (Biggest Complainers in the NFL). There’s absolutely no limit on what survey topics – but as you create them, be sure you’re sticking closely to your narrative.
It’s not just small businesses or agencies using data-driven storytelling, major organizations are also using this type of storytelling to connect with their audiences, raise awareness, and drive engagement. Because data-driven storytelling combines compelling stories with factual evidence, it’s a powerful tool for anyone looking to make their content stand out.
What are some data storytelling examples?
Spotify’s Wrapped Campaign: Spotify utilizes user data and listening habits to create personalized year-in-review summaries, showcasing users’ most listened-to songs, artists, and genres. Spotify releases this campaign annually.
Zillow Campaign on Valuable Words: This campaign by Zillow analyzed home sales to determine which words in listings were most common to see if certain keywords help a home sell.
Data-driven storytelling helps communicate insights, engage audiences, and drive meaningful action. It brings data to life, making it relatable and impactful. By combining data analysis, visualization, and narrative, you can create content that informs, engages, and inspires.
If you want to learn more, check out our other resources on creating content: