Storytelling With Data

By: Kelsey Jones

With so much content being created and published today (2.5 quintillion bytes daily as of 2021, to be exact), producing content without data to illustrate it practically guarantees the content has no basis in long-term effectiveness in meeting its goals and objectives.

Take the stat mentioned in the first sentence as an example. Simply saying “we as people produce a lot of content” doesn’t have the same effect as naming the exact amount of content that is being produced: 2.5 quintillion bytes daily (which is 2.5 billion gigabytes). Using data allows us to properly showcase the importance of our point without relying on flowery language or false dramatic effects. This is the power of storytelling with data.

In this guide, we will be diving into data visualization, how it works with SEO, and best practices with examples. Read on to learn more about how to ensure your data is clean and where to collect data that makes an impact on your content.

What is Data Visualization?

According to Microsoft BI, data visualization is explaining information through data imagery. But what does this mean in terms of how data fits into your content? Data visualization is important because it allows us to set the story of what we're trying to tell with proof in the data.

Visualizations are crucial for communicating your findings. It's much easier to see patterns or trends in a graph or chart than simply stated in a sentence, and it's easier to convey those trends to others if you have good visualizations.

Some popular visualizations in content include:

• Infographics

• Interactive tools, such as quizzes and sliders

• Various types of charts, such as pie charts or bar graphs

• Visual representations of numbers or steps, such as milestones in a project or dots to represent individual users

• Graphics that emphasize a key metric, such as the number of users for an app you’re covering or a large percentage increase or decrease you want the reader to remember

In a nutshell, the overall piece of content we’re creating is attempting to tell a story, whether it’s to prove our product or service is the best one, or to showcase that something in our industry or world is changing and we need to understand it. For instance, if a support SaaS tool wanted to tell the story that they are the best customer support dashboard available, they would “prove” that by showing data that shows their point.

This might include how their average customer decreases customer support response time by a specific percentage, or that customer churn decreases after a company starts using their support dashboard.

Data visualization helps us to tell a story with a beginning, middle, and end. The content can set up our story and the data fills in the gaps to drive home the point we're trying to make. If we wanted to explain industry trends, we might start our story by explaining how the industry currently operates, introduce the issues that come up with the status quo, and then bring in data to show why there are issues, and then how we can fix it.

The first step to developing a data visualization strategy within your content is to define the goal of your content, and therefore, the purpose of the data itself. Defining the goal of your content will help you avoid creating something that’s not useful or actionable, and instead create something that people can use as they go about their day-to-day activities.

It is important to start by clearly defining what you want to achieve or accomplish before building out a piece of content and its accompanying data. You should ask yourself: “What do I want my user to learn from this?” and “How does this user benefit from seeing this information?”

These questions will help guide you in determining what type of information needs to be included in the final product, whether there are any actions users should take based on what they see, and whether there are any immediate issues that need addressing because of your findings/data analysis (for example, business process changes).

No matter where we are getting our data, we can use it to build a foundation upon which we can explore key points in our content.

Tell your data-driven story with Moz Pro

Communicate the status, the impact, and the value of your work to your team, manager, and clients in a way each group can understand and appreciate with Moz Pro Custom Reports.

Start my free trial

Analyzing External Data to Create Unique Content

You don’t have to gather or use proprietary data to make great content that utilizes storytelling through statistics. Take this infographic from Visual Capitalist as an example.

Infographics are larger images of data presented in a visually pleasing way. It makes the statistics easier to digest and understand. For this topic, Visual Capitalist lead with the infographic at the top of the page, then included supporting content below that elaborated on the infographic’s main points.

As the article progressed, Visual Capitalist also used graphs to go into more detail about specific data mentioned.

By showcasing how the top company’s revenue increased during the pandemic, it’s fair for the writer to assume that the pandemic, in fact, increased these companies’ growth. By comparing their revenue YoY during 2020 and 2021 (the first two years of the COVID-19 pandemic), it’s fair for the writer to explain that the pandemic increased revenue, not damaged it (which wasn’t the case for many businesses and industries).

This example showcases the point that when data isn't used in content storytelling, we come across as unreliable. Most users are consuming content on the internet daily, and with that comes a healthy skepticism of content that's being shared online (as there should be, as essentially anyone can publish anything at any time). The data helps us prove that what we are saying is valid and offers a successful explanation of the points made throughout the rest of the content.

Using Data Visualization as a Marketable Moment

Another big benefit to storytelling with data is the ability to use your own data to influence your industry or prove your thought leadership. Music streaming giant does this every year with Spotify Wrapped. Not only do individual listeners get to see the songs that they most listened to at the end of every year, but Spotify also releases an annual report showcasing the trends in their users’ listening habits.

While this is valuable for the music industry to see what the current trends are in music, it also gives Spotify a marketable moment. Their thoughtfully-designed visuals are easy to share on social media and in press articles, giving Spotify what’s likely millions of dollars in “free” advertising, due to user-generated content and press coverage.

If you are using your proprietary data, or are able to analyze public data in a new way, you can turn your data visualization and the accompanying content analysis into a powerful opportunity to gather more links, pageviews, and conversions. Make data visualization an integral part of your content development strategy to capitalize on its benefits.

Best Practices for Data Gathering For Storytelling

Before you can start storyboarding a content piece, it’s important to understand the audience and their expectations. What do they know? What don’t they know? How much detail do they need? All of these questions are critical to answer before you begin making decisions about data design and storytelling.

Whether you are creating a large-scale data visualization project, like #SpotifyWrapped mentioned above, or you just want to gather and analyze data to support your content, it’s still important to understand the main points you want to convey and how data can help you reach that.

Before gathering data, decide what data you want to tell a story with. Ask yourself:

• What is the main point of my content?

• What data is available?

• How can you find the data?

• What kind of data do you already have?

• What kinds of data do you still need to collect or create in order to tell your story, and how much time will it take to get them?

Data is so valuable in our content because it allows us to create a narrative that educates the reader and give them valid points on which to take action. The idea of data and what points are needed to contribute to the desired narrative can be overwhelming at first, especially if you have a lot of data sources to use.

Whether you're using proprietary data or external data from a source like Google Trends or an SEO tool like Moz, knowing what you expect the reader to get out of a piece is crucial at every step of the process.

How to Ensure Your Data is “Clean”

“Clean” data means data that has been properly vetted and doesn’t contain any inconsistencies, such as included data that was supposed to be disregarded, or data that was pulled in the same way so it was standardized during the entire collection process. “Dirty” data is data that hasn’t been reviewed yet for these types of inconsistencies or errors that could influence the results.

Good storytelling relies on a sound foundation, which requires that your data is thoroughly collected, verified, and complete. This can be a daunting process, particularly when dealing with large or complex data sets.

If you will be collecting data internally (before analysis), there are several common best practices for gathering your data to make sure it is clean and accurate:

• standardization of the collection process

• use of multiple methods of data collection

• determining the scope of your data set (in terms of time and location)

• ensuring accuracy at every stage of the data gathering process

This is especially useful for data collection from methods like surveys or polls. You must ensure proper data collection practices are followed so you have the best data possible.

According to Tableau, you also need to verify the data you do gather, no matter if you have followed the above best practices or not. Verify data by checking for outliers or missing data, fixing inconsistencies (such as #ERROR and error being marked as separate entries when they actually mean the same thing), and QAing data against previous timeframes or sources to make sure it is accurate.

For example, if you were pulling data from Google Analytics and it said that you got 500 visits from a link on a specific Facebook campaign, you could also look at the link tracking URL (if you used a service like bit.ly) to see if it correlated with the same amount of clicks.

For external data that you can’t internally cross-reference, you can compare other similar studies or data sources to see if the information is within the same range. For example, if we were reviewing data about endangered animals in the United States from the National Wildlife Federation, we would try to find other studies about endangered United States species from other organizations to see if the patterns were similar.

To learn more about gathering clean data, Towards Data Science has a comprehensive guide on clean data collection and analysis.

Four Steps For Gathering Existing Data

Once you know the data needed to properly contribute to the narrative of your content, you must go through the following steps to gather it in a way that makes the most impact.

1. Choose the source of your data, whether it be from a public source or your data collection sources, like customer information or other tracking sources.

2. Choose the best timeframe of data to support your content. For example, a study about technology over time wouldn’t benefit much from data solely collected in the last six months. Instead, you’d need years’ worth of data to analyze and showcase.

3. Choose the best metrics within your data. Many times, data will be downloaded with an overwhelming amount of data points. For instance, an export file of customer orders could not only include the frequency and dollar amount of the orders, but also what products were purchased, what time of day, and from what type of computer (phone, desktop, tablet). Remove the data that isn’t useful to your main narrative and keep the rest.

4. Start organizing your data. Once you have the data narrowed down to the points you need, you can start analyzing it for patterns. Some data visualization tools will provide analysis for you, but raw exports of data require someone to plot it into charts or tables to find trends. This requires you to know how you’re going to use the data to illustrate points in your content, so make sure this is outlined first.

5. Clean your data. Make sure there aren’t inconsistent labels that are counting as multiple entries, that there is no missing data, and that you have all necessary data points for each entry to plot usable graphs or summaries.

With these steps, you can choose the best data source for your story, decide how to represent the data in a visual way, and determine what narrative you want to emphasize. If data is the main feature of your content, or just supporting your main points, it’s still important to have a plan in place to ensure it’s collected properly and proves the point that you need it to.

No matter the reason why content is being created in the first place, data visualization and SEO have the same goal in mind: to get the right people onto our websites in order to complete an action, whether that is to turn into a conversion, learn how to do something, or become more educated about the topic at hand. There are many aspects of SEO that tie into ensuring data is properly displayed in the content.

When done in an accessible way with adherence to ADA recommendations, data images are created in such a way that they're accessible by both human readers and search engines alike, making them an ideal tool for reaching new audiences and increasing your site's organic ranking potential. This could include:

• Captions in videos or animations: this helps the visually impaired know what is in your moving content and the transcription files can also be crawled and indexed by search engines

• Proper alt attribution: also commonly known as “alt text,” placing descriptions of charts or other data representations in your content will ensure those with visual impairments can still understand the data it’s showcasing, while search engines can use it for better indexing of images.

• Captions under graphics: adding illustrative captions under images can further explain the main posts of any graphics

Make sure any alt text or captions that are included with data media are also carried over to social media as well when shared. For instance, add captions to any YouTube data videos you upload or ensure that social media scheduling tools are pulling useful text content from the piece that best explains the visual data that is being shared.

Sharing a pie chart with a link to the full blog post won’t have as much of an impact as using copy to drive engagement. An example of this would be “Did you know that 84% of our customer support solution users increase their profits 200% in the first two months with us? Learn more in our annual usage report here: {URL} [upload of pie chart]”

This type of specific copy not only drives user interest but also is more descriptive of what the link is, which is helpful if search engines index your social media posts and they come up in search results for one of your target terms (which you could mention in the social media copy, as we did with the “customer support solution” keyword inclusion).

Building a Cohesive Story With SEO

Properly describing your data for accessibility and social media is only part of how SEO plays a part in storytelling with data. Oftentimes, we may find ourselves starting to tell a story that users may not even know they need to hear. That's where it makes sense to use SEO keyword research to influence not only the content that you're writing but the data that you're choosing to showcase throughout your pieces.

For instance, if users don't know that a product you offer even exists, any data that you have that talks about what your product does is inefficient and isn’t speaking to your customers’ pain points. It's important to use keyword research to determine what users are actually searching for, and then the story you tell can be built around that. We are often too close to the products and services we offer to understand how a customer may actually be using them.

Once we have published a piece with that we consider to be the right data, we can continue to use SEO to figure out if anything needs to be tweaked depending on how search queries have changed through time. More specifically, you can use your data to determine how users are finding your pieces and if the data you’re showcasing is making an impact.

Additionally, if you add data to a piece of content and are finding that it's not increasing time on site or conversions (or some other metric you have chosen), then the data may not be used in the best way to illustrate your points. This is how SEO can be used to help you make decisions about the success of your storytelling with data.

SEO Data and Reporting Solutions

Moz Pro provides data and reporting solutions to cover a broad scope of SEO tasks. From detailed site audit reporting and rank tracking to unique link metrics and keyword data. This data analysis can be used in marketing pieces to describe trends in over time, or you can use this type of data in your internal stakeholder content, such as when you want to illustrate the success of your organic content campaigns or how the number of links to specific pages has increased over time since you started updating old posts.

• Site crawl data - Moz Pro monitors a wide range of site issues like broken redirects, missing title tags, and many more.
• Rank tracking - Track your site, or your competitors site's, keyword ranking performance and overall visibility on the SERP over time to know what’s working and what’s not.
• Page optimization reports - Improve your page's relevance to meet customer needs, which in turn boosts your ability to rank higher and drive more traffic.
• Custom SEO reports - Communicate the status, the impact, and the value of your work to your team, manager, and clients in a way each group can understand and appreciate.
• Keyword research data and reporting - Keyword Explorer streamlines your workflow and takes the hassle, bad data, and repetitive busywork out of the process.
• Backlink research data and reporting - Analyze your link profile and competitive standing with the industry's most trusted link metrics.

Numbers can be intimidating, but there are many ways to present data that make it easier to understand by creating stories that will impact people in a powerful way. Data visualization allows us to build a narrative that has a beginning, middle, and end, and is supported by proven data throughout.

Without data, our content can come across as unreliable, not trustworthy, and lacking the credibility to follow through on its claims. Whether your data is collected from internal or external sources, make sure it's clean and isn’t missing any fields or has incorrect information.

To learn more about using Moz effectively to drive storytelling with data, take some of our Moz Academy courses or sign up for Moz Pro to get exclusive data about your website.

To learn more about storytelling with data, check out these pieces on the Moz blog:

• Here’s How to Combine Storytelling and Data to Produce Persuasive Content

• PICA Protocol: A Visualization Prescription for Impactful Data Storytelling

• Storytelling 301: Site Content as a Story

• Tasty SEO Report Recipes to Save Time & Add Value for Clients [Next Level]

• The Best Tools for Storytelling With Data Visualization

Written by Kelsey Jones, writer and digital marketing consultant at SixStories.

All screenshots were taken Jun 21, 2022.