Data Storytelling: Why Every Business Needs to Adopt This Skill
Both startups and established businesses are now, more than ever, using tools and technology to collect, store, and analyze data.
After collecting and cleaning data, the next step is to extract value from it. Even with the advent of BI and analytics tools, however, extracting meaningful insights to make better business decisions remains a challenge for many organizations.
What's more, many companies—such as marketing agencies—need to not only extract value from raw data, but also communicate those insights to clients. Since many clients may not have technical expertise in data science, these insights need to be communicated in a professional yet understandable way. To do this, many marketers and analysts use what's referred to as data storytelling.
Telling a compelling data story might sound relatively easy, although many marketers and data analysts find it hard to use an engaging tone and create a narrative in their reporting. The reality is that most businesses tend to overlook this aspect of client reporting.
As we'll discuss in this article, data analytics and reporting are critical components in building the client relationship. That said, insights alone don't yield much value to the client if you don't combine it with a story that conveys the significance of the data. To that end, data storytelling is an essential skill that every business needs to adopt in order to build transparency and improve client communication.
What is Data Storytelling?
As discussed in our Client Reporting eBook, data storytelling is the process of taking raw data, analyzing it, and communicating its significance to clients. This is accomplished with the help of three core components:
- Data: The first element of storytelling requires that you have accurate and up-to-date data. One of the main benefits of an all-in-one reporting platform is that data is automatically pulled from various marketing platforms, which both saves you time and avoids the possibility of human-error in the data collection process. Once the data is collected and cleaned, it is then analyzed with the use of statistics and algorithms in order to extract key insights.
- Visualization: Data visualization is a graphical representation of data that uses graphs, charts, and other visual elements to convey information. Data visualization is key in both discovering and communicating underlying trends, patterns, and outliers in a given dataset. Ultimately, the goal of visualization is to uncover trends that may have otherwise been missed with a standard spreadsheet and convey that information in a comprehensible way.
- Narrative: Finally, providing a narrative alongside insights and visualization allows analysts and marketers to highlight the significance of certain metrics, KPIs, or changes that may have occurred during the reporting period.
Combining these three elements in your client reporting allows you to build a level of trust and transparency by communicating results in a way that anyone can understand, regardless of technical expertise.
Why is Data Storytelling Important?
There are many methods to communicate data insights, although since storytelling is an intrinsic human characteristic it allows you to blend the data-driven economy with visual and written communication. Before we discuss how to tell a good data story, let's review a few of the reasons why data storytelling is so important.
1. It’s a powerful competitor analysis model
Firstly, if you’re in a highly competitive market you're constantly at risk of losing potential customers to the competition. To draw a line between your business and the overall market, you want to identify competitive data insights from your campaigns and operations. Internal data allows you to tell a story about your brand’s personality and its unique strategies that solve your target customer's pain points.
Data storytelling is perfect for PR, and when done right, it can give your brand recognition over your competitors. In short, companies can enhance the value of their products or services to their target audience with a data storytelling culture.
2. It boosts client communication & engagement
While companies use many strategies to collect and analyze data, maintaining an engaging conversation for an extended period of time with clients can a difficult task for many agencies. Building effective client communication goes beyond compiling as much information into a presentation, you also want to use data storytelling to convey results in an intelligible way and demonstrate the value of your services.
3. It creates a visual appeal
As humans are notorious for having an ever-shrinking attention span, data visualization can go a long way in communicating your results. This can be done through visuals such as graphs, charts, heatmaps, and more—all of which boil down to creating a visual appeal to the end-user. The reality is that clients not only want to interact with hard numbers but also need to visualize the success story behind the results. In short, combining elements of data, information, knowledge, and insights into a visual format can be incredibly valuable in client reporting.
4. Storytelling is Key to Data Science
As mentioned, it’s human nature for us to be storytellers. Scholars have pointed out that storytelling has long been one of the most important mediums to influence, teach, and inspire an audience. In the context of data science, after collecting, cleaning, and analyzing data, the next step is to relay context using a compelling narrative and visuals that help them grasp the significance of the data.
As more and more companies have begun to realize the potential of their data to improve decision-making, data science has been one of the fastest-growing occupations and industries in recent years. In fact, a study found that the global big data market size is expected to grow from USD 138.9 billion in 2020 to USD 229.4 billion by 2025, representing a Compound Annual Growth Rate (CAGR) of 10.6%. That being said, many businesses will need experienced data storytellers to help them identify and communicate the metrics and KPIs that are essential for measuring growth.
How To Be an Exceptional Data Storyteller
Quite a lot goes into effective data storytelling besides having knowledge about marketing and analytics. The reality is that numbers and statistics alone can't communicate the relevance of each metric or KPI. Instead...
The first step in data storytelling is to have a reliable source of clean and organized data. In fact, a study by the data science company Anaconda found that many data scientists say that they spend 45% of their time on data preparation tasks, including cleaning and loading data. If, however, you're using an all-in-one reporting platform like AgencyAnalytics, you can simply connect to our 50+ marketing integrations and automatically pull data into a unified platform.
As mentioned, once data is ready to be analyzed the next step is to extract meaningful insights from it. Although these insights are crucial to client reporting, they must be combined with a data story in order to communicate meaning. As the Forbes contributor Brent Dykes notes:
When you package up your insights as a data story, you build a bridge for your data to the influential, emotional side of the brain.
To do so, the author highlights that data, narrative, and visuals work together in the following ways:
- Explain: Coupling a narrative with insights allows you to explain what's happening with the data and why certain metrics and KPIs are important to the overall trend.
- Enlighten: By using data visualization, you can enlighten the audience of key patterns, trends, and outliers that may have otherwise been missed.
- Engage: Finally, by pairing visuals with a narrative you create an engaging story that can drive change at the organization.
Ultimately, the main reasons why data storytelling is so important is that they increase the memorability, persuasiveness, and engagement of data insights.
Data Storytelling with AgencyAnalytics
Now that we’ve discussed what data storytelling is and its importance, let's review a real-world example using AgencyAnalytics.
One way to tell a story with your data is to add annotations and goals to your line charts and date-based column charts. This feature opens up a whole new level of your to your reporting as it gives you the ability to highlight important information directly within each chart. You can use this to tell stories with your data and ensure that clients are aware of your achievements.
To do this in AgencyAnalytics, you simply open the widget settings and you'll see options to add annotations and goals in all date-based line and column charts:
Once you’ve added your annotations and goals, they will automatically be displayed on the chart. As you can see below, this feature adds a level of transparency and accountability between you and your client:
Summary: Data Storytelling
As discussed, by combining data, visualization, and narrative you're able to tell an engaging story anyone can understand and that clients will actually remember.
In the context of marketing, data storytelling is one of the best ways to deliver an intuitive understanding of your campaign results—not only does it communicate the value of your services in a thought-provoking way, but also creates a level of transparency and accountability between your clients.
Written by Peter Foy
Peter Foy is a content marketer with a focus on SaaS companies. Based in Montreal, QC, when he’s not writing or managing ad campaigns he’s usually studying data science and machine learning.