Edited by Emilie Martin

Join Lazarina in this Whiteboard Friday where she discusses the critical skills and elements involved in data storytelling. Learn about data analysis, and data visualization, as well as how to communicate wins and balance relationships with stakeholders.

Click on the whiteboard image above to open a high resolution version in a new tab!

Video Transcription

Hi there. Today we're going to talk about data storytelling. Throughout history, we humans have used stories to communicate information, to cross boundaries, and to also relate to one another. So today we're going to talk about data storytelling and how that can be used as part of an SEO or a marketing consultant's role.

We're going to talk about the four main components of data storytelling and the skills that you need in order to create beautiful data stories.

Data Science

So the first component of data storytelling is data science. So data science is all about knowing what insights you want to extract from your data, but it's also about the technical skills that you need as a consultant or a marketer in order to extract that data.

So it combines a little bit of data analysis. It combines a little bit of data engineering. But it's all about knowing what data you need in order to tell a good story.

Data Visualization

The second component of data storytelling is data visualization. So data visualization is all about knowing how to visualize the data that you have at hand based on the insights that you want to communicate.

It's also about choosing the visuals that help you communicate the narrative that you want to your stakeholders better. So this means if you have a particular data type, whether it's numeric or text-based, it means choosing the visuals or otherwise the charts, the graphs, or tables that will help you to communicate those insights to your stakeholders better.

The Narrative

The third component is the narrative. So the narrative is all about how do you convey insights to your audience. What is most important here is that you learn how to communicate wins, how to evoke emotions in your stakeholders, how to maybe create some urgency with the stories that you are saying, and also how to communicate the relationships between the projects that you're working on and the outcomes that you are seeing within the data.

What is also very important here is to show the cause and impact relationship between the data points, the projects that you're working on, and what the outcomes of these are.

Relationships

The fourth component, the big circle here that typically people don't really consider in data storytelling is actually the relationships.

So when we talk about relationships, it's all about the relationships that you have with your stakeholders. This is something that typically you will need to work on as you are working with your stakeholders. But what is most important here is to understand your stakeholders. Who are they?

What are their hidden motivations? Who are they reporting in to? Or what is the most important outcome for them for this particular project? It's also very important for you to know before you create a report or any sort of data story what success looks like for that particular person and how you can best bridge the gap between the current performance and their ideal performance through the story that you tell.

So now that we have all of these different skills that you need to know, we can see the three main components of a successful data story, and that is first of all the data. We know that the data should be accurate. It should be reliable. So what is most important, when you are looking at your data, is to understand specifically whether there is any sampling applied, whether this is a reliable data source, whether the data is complete.

So these are the kind of questions that you should be asking yourself whenever you are analyzing the data that you want to present to your client. The second very important component and what we have learned is that you need to have a very compelling narrative. So the narrative is a combination between your ability to bridge the gaps between the data and the projects that you're working on.

But it's also a combination between who you are reporting in to. So depending on who your audience is, your narrative is likely going to change even though you are reporting the same data. The third component is actually the visuals that you are going to use. Whenever you are choosing visuals, always think about whether this is the most appropriate way to present the information that you have to that particular audience, because even though sometimes you might prefer to present to the audience in a certain way, like let's say, for instance, a dashboard, that might not be the ideal vessel for this data and for this narrative for the particular person.

Whenever you are choosing your visuals, it's very important not only to think about the platform where you are storing your reports and how you are building them, but it's also important to think about whether you are choosing the most appropriate graphs and charts in order to help the audience understand quickly what the desired actions after the report should be.

So whenever you are thinking about your data, your narrative, and your visuals, click on the link within the blog post because there will be a checklist there to help you through different questions about how to best organize these three elements when you're building your data story. With all of that, we have covered a lesson for data storytelling components and skills that you need to succeed.

Further resources:

Youtube Video: Telling Stories with Data - What is Data Storytelling and How to Implement as a Consultant

Part 1: Beginner’s Guide to Data Storytelling for Digital Marketing Consultants and Analysts - Elements, skills, and components of action-provoking data stories.

Part 2: Six Practical Ways to Implement Data Storytelling in Your Consulting - Actionable examples, tips, and best practices for implementing data storytelling.

Video transcription by Speechpad.com