How do you prove the value of data visualization?

1 Know your audience

The first step to prove the value of data visualization is to know your audience and their needs, preferences, and expectations. Different audiences may have different levels of familiarity, interest, and attention span with your data. You need to tailor your data visualization to suit your audience and their context. For example, if your audience is a group of executives who need to make a quick decision, you may want to use a simple and clear chart that highlights the key insights and recommendations. If your audience is a group of researchers who need to explore and analyze the data in depth, you may want to use a more interactive and detailed visualization that allows them to filter, zoom, and compare the data.

2 Define your goals

The second step to prove the value of data visualization is to define your goals and how you measure them. What are you trying to achieve with your data visualization? What are the desired outcomes and actions that you want your audience to take? How will you know if your data visualization is successful or not? You need to set specific, measurable, achievable, relevant, and time-bound (SMART) goals for your data visualization and track them using appropriate metrics and indicators. For example, if your goal is to increase the awareness and engagement of your data story, you may want to measure the number of views, shares, comments, and feedback that your data visualization generates.

3 Choose the right format

The third step to prove the value of data visualization is to choose the right format and design for your data. There are many types of data visualization, such as charts, graphs, maps, dashboards, infographics, and animations. Each type has its own strengths and weaknesses, and you need to select the one that best suits your data, your goals, and your audience. You also need to follow some basic principles of data visualization design, such as choosing the right colors, fonts, labels, legends, scales, and layouts. You want to make sure that your data visualization is accurate, clear, consistent, and attractive.

4 Test and improve

The fourth step to prove the value of data visualization is to test and improve your data visualization based on feedback and results. You need to evaluate how well your data visualization performs in terms of your goals and metrics, and how well it meets the needs and expectations of your audience. You can use various methods to test and improve your data visualization, such as user testing, surveys, interviews, analytics, and experiments. You want to identify the strengths and weaknesses of your data visualization, and make changes and improvements accordingly.

5 Tell a story

The fifth step to prove the value of data visualization is to tell a story with your data. Data visualization is not just about showing numbers and facts, but also about creating a narrative and a connection with your audience. You need to use data visualization to tell a story that is relevant, engaging, and persuasive. You can use various techniques to tell a story with data, such as framing, context, structure, flow, emotion, and call to action. You want to use data visualization to capture the attention, interest, and trust of your audience, and to inspire them to take action.

6 Show the value

The sixth and final step to prove the value of data visualization is to show the value of your data visualization to your audience, your stakeholders, and yourself. You need to communicate and demonstrate how your data visualization has helped you and your audience achieve your goals, solve your problems, and answer your questions. You need to highlight the benefits and impacts of your data visualization, such as increased understanding, awareness, engagement, satisfaction, or performance. You need to showcase your data visualization as a valuable and effective tool for data analysis and communication.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?