Using tools and technology to collect, store, analyze, and report data is essential to growing your business-savvy clients’ brands. To report on a mountain of data so your clients can quickly glean insights from their marketing campaigns, agencies rely more on data storytelling than ever before. But what is data storytelling, anyway?
Simply put, data storytelling is a way of framing data in a way that is easy to understand and engaging. It is used to illustrate trends or patterns or to explain complex concepts. By using graphs, charts, and other visuals, data storytelling helps make data more interesting and accessible to clients who are less familiar with technical marketing figures.
After collecting and tidying up the data, the next step is to extract value from it. Even with Business Intelligence (BI) and analytics tools, extracting meaningful insights to make better business decisions remains a challenge for many organizations.
Also, marketing agencies not only need to extract value from raw data but also effectively communicate those insights to clients and stakeholders. Since many clients may not have technical expertise in data science, these insights need to be communicated professionally, yet understandable.
Telling a compelling data story might sound relatively easy, but 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 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. After all, insights alone yield little value to the client if you don't combine them with a story that conveys the significance of the data. Data storytelling is an essential skill every marketing agency needs to adopt to build transparency and improve client communication.
What Is Data Storytelling?
As discussed in our Client Reporting eBook, data storytelling takes raw data, analyzes it, and communicates 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, saving time and preventing human error in data collection. Once the data is collected and cleaned, it is analyzed using statistics, benchmarks, targets, and algorithms 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 tools are key to discovering and communicating underlying trends, patterns, and outliers in a given dataset. Ultimately, the goal of visualization is to uncover trends that may have been missed with a standard reporting spreadsheet and convey that information comprehensibly.
Narrative: Finally, providing a narrative alongside insights and visualization allows analysts and marketers to highlight the significance of specific metrics, KPIs, or changes that may have occurred during the reporting period. This is your agency's chance to showcase what is happening, provide your unique insights into why, and explain how you plan to make the data actionable.
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.
Data Stories vs. Data Visualizations
Traditional static reports are on the decline. Increasingly, marketing agencies are looking to data storytelling to help them make better decisions and provide better reporting to their clients. Data stories and data visualizations are two ways of representing data that are often used interchangeably. However, there are some key differences between the two:
A data story is like a regular story but has extra information to help explain what is happening. They often tell stories in the traditional format of having a beginning, middle, and end.
Data visualization is a graphic representation of data that can be used to highlight trends or patterns. Visual tools such as bars, charts, and graphs help explain the data story and are usually more focused on the raw data itself. Although data visualizations can be used to tell a story, they are often more about exploring and understanding the data than conveying a specific message.
Both data stories and data visualizations have their strengths and weaknesses. Data stories are good for conveying complex information in an easily understandable way. They can also be used to tell a persuasive story that motivates people to take action.
On the other hand, data visualizations can help the reader absorb, digest, and understand complex data points faster and easier than if the same data was provided in a table or text format.
Data visualization example:
Data stories can be time-consuming to create, and they may require a lot of text and annotations to explain the data and the story behind the data. On the other hand, data visualizations are good for quickly conveying information and can be used to highlight trends that might not be immediately obvious in the data. However, data visualizations can be difficult to create without the proper tools, and they may not always be accurate.
There is no one-size-fits-all answer to whether data stories, data visualizations, or a mix of both are better for conveying information. It depends on the specific situation, what type of information is being conveyed, and the intended audience.
Why Is Data Storytelling Important?
There are many methods to communicate data insights, although storytelling is an intrinsic human characteristic that allows you to blend the data-driven economy with visual and written communication.
Data storytelling is important because it allows for the effective communication of data. When data analysis is communicated effectively, it can improve decision-making, reinforcing your working relationship with your clients. This kind of data analysis can also help change people's behaviors and improve their understanding of complex issues.
Before we discuss how to tell a good data story, let's review a few reasons why data storytelling is so important.
1. It’s a Powerful Competitor Analysis Model
First, if your client is in a highly competitive market, they're constantly at risk of losing potential customers to the competition. To draw a line between your client 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 the brand’s personality and unique strategies that solve the target customer's pain points.
Telling stories with data is perfect for PR, and when done right, it can increase brand recognition over competitors. In short, companies can enhance the value of their products or services to their target audience with a data storytelling culture.
As an agency, competitor analysis can help reinforce that you've got your client's best interest in mind and are constantly monitoring what is happening within their niche.
2. It Boosts Client Communication & Engagement
While agencies use many strategies to collect and analyze data, maintaining an engaging conversation with clients for an extended period can be a difficult task. Building effective client communication goes beyond copying and pasting as much information into a presentation as possible; you also want to use data storytelling to convey results intelligibly and demonstrate your services' value.
Although most of your clients will want to see the numbers connected to your efforts, the best agencies take that a step further and craft a compelling narrative that paints a clearer picture for their clients. Think of it as providing the “why,” “when,” “where,” and “how” to help explain the “what.”
3. It Creates a Visual Appeal
As humans are notorious for having an ever-shrinking attention span, data storytelling with visuals can go a long way in communicating your results. This can be done through graphs, charts, heatmaps, and more—all of which create 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. Data 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, the next step after collecting, cleaning, and analyzing data is to relay context using a compelling narrative and visuals that help the client 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 said, many businesses will need experienced data storytellers to help them identify and communicate the metrics and KPIs essential for measuring growth.
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How To Be an Exceptional Data Storyteller
Quite a lot goes into effective data storytelling besides having knowledge about marketing and analytics. Numbers and statistics alone can't communicate the relevance of each metric or KPI. 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. Using an all-in-one reporting platform like AgencyAnalytics, you can simply connect to our 75+ marketing integrations and automatically pull data into a unified data storytelling platform.
Once data is ready to be analyzed, the next step is extracting meaningful insights from it. Although these insights are crucial to client reporting, they must be combined with a data story 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 specific metrics and KPIs are important to the overall trend.
Enlighten: By using data visualization, you can enlighten the audience about 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 organizational change.
Ultimately, data storytelling is so important because it increases the memorability, persuasiveness, and engagement of data insights.
6 Ways to Incorporate Data Storytelling Into Marketing Reports
Data is everywhere, and it's becoming increasingly difficult to make sense of it all. A compelling data narrative can help make sense of data and communicate its significance in a way that is both clear and interesting. Here are some ways to incorporate data storytelling into your marketing reports:
Start by finding the most important data points from your report. Begin by finding the most important data points from your report. This will help you focus on the most important information and ensure that it is included in your data story.
Create a storyline to accompany the data points. Once you have your key data points, create a story that accompanies them. This can help make the data more interesting and easier to understand for your audience. The data should support this message, and no extra information that could distract from it should be included.
Use graphs and visuals to help explain the data. Graphs and visuals can help to explain the data more effectively. This will help your audience better understand the data you are presenting.
Use images or videos to help explain your data points. Going behind charts and graphs, images - even simple GIFs - or videos that provide the thoughts behind that data can help your agency effectively communicate the meaning behind the data.
Write a headline that captures the essence of your data story. A data story does not differ from any other story; it needs a catchy headline. The headline should capture your data story's essence and help draw in your audience.
Use key takeaways to summarize your data story. At the end of your data story, include key takeaways. This will help your clients remember the most important points from your data story.
Data storytelling is a great way to improve your data visualization skills and your understanding of your customer base. By telling stories based on data, you can help illustrate what is happening with your client's marketing campaigns (and why) and how well your agency understands their business and customers.
Data Storytelling With AgencyAnalytics
Now that we’ve discussed data storytelling and its importance, let's review a real-world example using AgencyAnalytics.
Many data visualization elements, such as charts and graphs, are built into the report and dashboard templates. The report summary section is the perfect place to include other visual elements - including images and videos - that will help drive home your data-driven story.
Another way to tell a story with your data is to add annotations and goals to your reports. This feature opens up a whole new level of 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 know 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–available on Agency and higher plans–adds a level of transparency and accountability between you and your client:
Summary: Data Storytelling
By combining data, visualization, and narrative, you tell an engaging story anyone can understand and that clients remember. After all, you're not building and sending reports for the reports themselves. These reports should be an opportunity to build a deeper relationship with your clients.
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 it also creates a level of transparency and accountability between your clients.
Peter Foy is a content marketer with a focus on SaaS companies. Based in Toronto, when he’s not writing he’s usually studying data science and machine learning.Read more posts by Peter Foy ›