What is Data Storytelling – Skills Needed, Elements, and Checklist to build Data stories in marketing

components of data storytelling
components of data storytelling
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Elements, skills, and components of action-provoking data stories

Throughout history and human evolution, stories have been used as the vehicle to bridge gaps between people and unite them. We, as humans are very accustomed to hearing stories, creating them, and using storytelling as a device. Through countless examples of successful uses of storytelling as a device in marketing, we know how important it is for growth. Stories have the power to help us understand meaningful information and, thus, can shape our values, determine our prejudices, and influence our desires. Some of the most successful brands in history have used storytelling as a device to convey their entire marketing strategies without even having to actually persuade people to buy their products.

Yet, despite the importance of stories, many digital marketing consultants, SEO consultants, and analysts alike fail to utilize this skill when presenting data or discussing performance, instead relying on dashboards or spreadsheets, which only speak of the what, not the why. Or otherwise, discussing the outcomes of what happened in the projects or niche discussed, not the actions needed to resolve the issue, or move the project forward.

What is data storytelling? 

Data storytelling is the ability to tell stories behind the raw data through a methodology that presents information, tailored to a specific audience with a compelling narrative. These three elements: the selected information, the audience, and the narrative, are the fundamental components of a data story. 

What are the elements of data storytelling and what skills do you need?

Data storytelling consists of several important skills that consultants should incorporate into their arsenal – data science, data visualization, narrative design, and relationship management. 

Data science skills and elements for data storytelling

The first skill you need for data storytelling is data science. In order for you to build data stories into your reporting, you must first know how to extract knowledge and insights from data and have the technical skill set of combining different data sources and manipulating them. This means knowing, for instance, how to blend data in Looker Studio, how to apply filtering to achieve your particular view, or how to create custom dimensions. It might also mean knowing how to scrape data, do entity or sentiment analysis, or otherwise – having a bit more technical hard skills in data science.

Data visualization skills and elements for data storytelling

The second component of data storytelling is data visualization. Here, you must understand how best to visualize data based on the data type and also help stakeholders to comprehend the high quantities of data that you have collected, as this is very important for your overall storytelling capabilities.

As part of this skill set, you must ensure that you know the best way to help promote change, as opposed to causing further confusion when you’re building reports and data stories. As part of this particular skill set, you might also want to learn to experiment with different visualization platforms and tools, as well as different ways to present the same data, depending on the stakeholder. What you might find, is that oftentimes, there’s no need for complex data visualization, if the story is simple, and the people at the top (e.g. c-suite) might often benefit from having a simple color-coded table in grasping performance at a top-level. 

Narrative skills skills and elements for data storytelling

The third skill you need for data storytelling is having a data narrative. How do you convey insights? How are you going to communicate wins? Do you know the best way to instill urgency in your stakeholders, whenever needed? Are you aware of how the different components of the project, and the relationships of stakeholders that are part of the project impact it? Do you know the best way to indicate a cause and impact effect to your stakeholders? 

The narrative is a critical component of data storytelling and it requires building skills in communication, as well as creativity. We will talk about the components of the perfect narrative in a later section of this guide.

Stakeholder relationship skills and elements for data storytelling

As well as knowing how to best convey insights and data, you must also be good at building relationships with stakeholders. Actually knowing them as people, not just as positions in the organization. Find out what type of person they are, and how you can best relate to them and communicate with them without friction in your day-to-day. Also, consider what motivates and worries them in their role and within the context of the projects that you’re working on together – or otherwise, what success and failure look like to them. If you are reporting to CSU, to executives, you need to know what they report on, to their executives, and so on. So what is the most important thing for them? With this knowledge, you can then present potential project bottlenecks or wins in a more clear way, related to their own goals and KPIs. 

I think a crucial component of data storytelling is actually your ability to build relationships and extract the most important aspects of these relationships and put that in the context of the data that you have.

Why is data storytelling so important and why is it often overlooked?

Storytelling is often overlooked as it requires a more advanced understanding of your stakeholders, as well as the soft limitations or risks for projects. It is also overlooked as it often is the last step of the reporting process, albeit arguably the most important step of it. 

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When you’re creating a performance report, you will start with the data collection stage. You will collect your data, connect the data sources, and identify the reporting areas. 

The second stage is to analyze the data and decide what metrics and dimensions are important to your stakeholders. 

In a typical reporting project, you will then add visualizations, choose the visualizations that best present your selected metrics and dimensions, and organize your report structure and style. 

The last step is data storytelling, creating a powerful story. This is often the last component of the dashboard creation process, probably the last 10%, but is one of the most important components of the entire process. 

What are the components of successful data storytelling?

There are three components of data storytelling: the data, the narrative, and the visuals. Let’s talk about how each of these elements can help engage, explain to, and enlighten your audience. Only with all three can you create a thought-provoking, engaging, and action-oriented report. 

Data as a component of data storytelling

Whenever you are choosing the data you report on, you should try to select data that is accurate, reliable, and appropriate for the insights that you’d like to reach as part of your story. Accurate data means making sure that the data you have is not sampled, or filtered in a way that distorts it. Reliable data means making sure that the data source can be reached and that the views that you are presenting can be achieved by other people trying to replicate this report as well. 

Think about this – if you have sampling applied to your data, or if the data is not accurate, if it’s not timely if it’s not real-time, how are you going to rely on this report being the source of truth for your client? Are you going to feel confident and comfortable presenting this data to them? Are you going to feel comfortable using this data when you are building your monthly report? Are you going to feel comfortable using it when you are doing C-suite executive-level reporting? Perhaps not. If you don’t feel comfortable with the report, your stakeholders are not going to feel comfortable with it as well. From that point of view, having accurate data is the first component of building a good story. 

Here are some questions to ask yourself, when validating your data: 

  • Is there sampling applied to the data?
  • Is the data accurate?
  • Is it timely (i.e. timed for the appropriate use)? Is it real-time? Is it historical? Is it forecasted?
  • Do you feel comfortable enough with the data to use it to inform strategy?

Narrative as a component of data storytelling

The narrative is the second component. The narrative of a data story should be compelling, action-oriented, and aligned with the needs of the project and its stakeholders.

When building a data story is very important to emphasize the action-oriented aspect. Think about the data in the context of projects that you are working on. Projects that have perhaps been delayed for reasons that are often, if you’re working in SEO, outside of your control. Perhaps someone from the web dev team has quit, or they have taken on an additional project that does not allow them to fulfill their duties. All these different things can mean that your projects are being delayed. However, if you are doing reporting and don’t provide that additional context, you are in a position where you are not pulling your weight as a consultant as you are not doing what is needed for these projects to move forward. 

Consider what actions are needed to resolve any existing conflicts in the data, and also what is the context for this data that is being observed. Speak the language that your stakeholders are speaking, but also allow them to understand the complexities of the project.Think about stakeholders’ perspectives on the project. 

For example, If you know that your stakeholders have communicated with you, that a certain KPI is very important to them, and this is the KPI that they report on, let’s say, for instance, an increase of 20% in organic sessions. If you know that you have three projects that have been blocked for reasons that are within the scope of control of this particular stakeholder and you are reporting directly to them, you need to build the narrative that the underperformance is within their control to fix. Because the reasons for that are partial because projects have not been actioned and as a stakeholder, they have the ability to change that story -it is within their power. By building that kind of narrative, you can tie in very easily the actions that are needed to fix the performance and to illustrate the next steps. 

Here are some questions to help guide your narrative: 

  • What does the data show? Is the demonstrated performance aligned or misaligned with expectations?
  • Can you derive the actions needed as a next step from analyzing the data and performance shown?
  • How does the data shown relate to the projects that you are working on?
  • Is the data you are seeing influenced by external projects or stakeholders within the team?
  • Can potential improvements in the performance observed be influenced by people on the team or the acceleration of projects in the pipeline?

Visuals as a component of data storytelling

The visuals are important because they need to help the reader to spot trends, spot patterns, and enable insights that are not easily seen in the rows and columns of spreadsheets, or raw data. 

There are a few important things to note when it comes to visual selection for the purpose of storytelling: 

  • Experiment with different types of reporting tools and formats for different audiences – Not everyone will be the perfect audience for a dashboard, or a deck. Adapt the reporting method used for your audience. Your choice needs to persuade the audience that whatever style of reporting you have selected allows you and them to have an advanced understanding of the data and enables them to extract more insights via that understanding. The visuals are the vessel for you to achieve that purpose. 
  • Don’t just choose a visualization vessel cause it looks nice, and don’t choose colors randomly – every selection you make should be a reflection of the story you are telling with the particular data point, metric, or dimension. Use your knowledge about the metric or dimension when building your reports, to support what’s important to highlight about the changes that have occurred. 

Below are samp questions you can use to validate your visuals selection: 

  • Are the visuals you’ve selected the vessel to your data story?
  • Do the charts, graphs, scorecards, and tables help you gain a more advanced understanding of the data presented?
  • Do the visuals selected help with the identification of patterns and trends, that would otherwise remain hidden in the data?

If you only have the narrative and the data, you will be able to explain something. If you only have the visuals and the data, you will enlighten your understanding of the data. If you only have visuals and the narrative, you will have a very engaged audience. But if the data is not tied into this, it’s not a very compelling story and might not lead to any actions implemented. You’re just going to capture the short-term attention of your audience. When combining all of these three elements, you can allow your stakeholders to not only envision the change that needs to happen.

What are the benefits of incorporating data storytelling in your role?

Improve the actionability of reports

Whenever you are creating data stories, instead of simply reporting on stats, you are building a bridge to the influential, emotional side of the brain. We know from studies, research, and millions of years of collective human history and evolution, that emotional characteristics invoke action. ​​SKdrDDCgFSi4d0tKbRMZs9aQSRixlEQPT0CJQqPvecys63qo rxs 1n3WEculpRGV2Xenn3tTXY0t84EvUYYIW4lBzUvIdD80B8QoUFL yklYTMcKVQ4EDloIfYKHIP7WkWSi7e4IsjEQwTb86Wad7Q

Improve the memorability of your reports

As presented by author Brent Dykes, a study by Stanford professor Chip Heath found that 63% of people can remember stories, but only five could remember a single statistic. Despite there being recent studies from 2022 that question the data on differences between recall of traditional visualizations and data storytelling visualizations, there are also findings that suggest that the cognitive load induced by different chart types and self-assessed prior knowledge on the chart topics could possibly have a moderating effect on information recall. To put it simply, the easier you make it for your stakeholders to understand your presentation, the more memorable it will be.

Improve the persuasiveness of the data that you are presenting

Another argument that Brent makes in his aforelinked article is that data storytelling can help make your arguments more persuasive, based on data from separate studies showing that packaging the data or the action into a story, can outperform another version of the same kind of action or call to action. In a Carnegie Mellon study, researchers asked for donations by testing two versions of a brochure on the charity, where the story version had twice the donations as the statistics-only version.

Enjoy a less critical and more engaged audience

Although there is evidence on both sides of the argument, there is a prevailing notion that good stories help the storyteller and the listener form a bond that helps for a smoother transition throughout the presentation. This is often showcased as a suspension of disbelief and a heightened interest in the story.   Rather than nitpicking over the details, the audience would like to know, what are you trying to say with the storytelling device? Why are you doing this? What is the end result of this particular story, often impacting the project’s success? 

Instead of falling into the trap of trying to explain every data point or chart functionality (which should be done in the supporting documentation), use storytelling in order to only show the main aspects of the data that are the most impactful components of the performance and the project’s next steps.

As Yarden Katz (2013) warns in an issue of Nature Methods in which the editors cautioned that over-emphasis on telling a good story could risk compromising good science. Make sure that the storytelling you are doing does not compromise the accuracy of data.

Additional Resources (and link to part 2 – How to Implement Data Storytelling)

If you want to learn more about the tips and tactics to use to implement storytelling in your day-to-day, check out part two of the data storytelling guide, titled: Six Practical Ways to implement data storytelling to your digital marketing and data consulting.

Make sure you copy the checklist for a practical guide on validating your data, visual, and narrative storytelling elements.

Get a copy of the checklist by clicking on the image, or follow this link: WTSFest 2023 – Data Storytelling Checklist for Digital Marketing Consultants (by Lazarina Stoy)

If you want to check the full slides of the presentation I gave at WTSFest 2023, click on the link below: