How do you choose the right data visualization tool for your digital strategy?

1 Assess your data sources

Before you start looking for a data visualization tool, you need to understand what kind of data you have, where it comes from, and how often it changes. For example, do you have structured or unstructured data? Do you use a data warehouse, a cloud service, or an API? Do you need real-time or historical data? These factors will influence the compatibility, performance and cost of your data visualization tool.

2 Define your objectives and KPIs

Next, you need to clarify what you want to achieve with your data visualization and how you will measure it. For example, do you want to inform, persuade, or inspire your audience? Do you want to show trends, patterns, or relationships? Do you want to compare, contrast, or rank data? What are the key performance indicators (KPIs) that matter for your digital strategy? These questions will help you narrow down the type, style and features of your data visualization tool.

3 Know your audience and context

Another important step is to consider who will see and use your data visualization and in what context. For example, who are they, what do they care about, and what do they already know? How will they access your data visualization, on what device and platform, and in what setting? How much time and attention do they have, and what actions do you want them to take? These factors will affect the design, interactivity and accessibility of your data visualization tool.

4 Compare and evaluate different tools

Now that you have a clear idea of your data, objectives and audience, you can start exploring different data visualization tools that match your criteria. There are many options available, from simple and free tools like Google Charts or Tableau Public, to more advanced and paid tools like Power BI or D3.js. You can compare and evaluate them based on their functionality, usability, scalability and security. You can also look for reviews, testimonials and examples of how other digital strategists use them.

5 Test and refine your data visualization

Once you have chosen a data visualization tool, you need to test and refine your data visualization to ensure that it meets your expectations and delivers your message effectively. You can do this by following some best practices, such as choosing the right chart type, using appropriate colors and fonts, adding labels and legends, highlighting key points, and avoiding clutter and distortion. You can also ask for feedback from your colleagues, clients or users, and make adjustments based on their input.

6 Monitor and update your data visualization

Finally, you need to monitor and update your data visualization to keep it relevant, accurate and engaging. You can do this by tracking and analyzing the performance of your data visualization, such as the number of views, clicks, shares and comments. You can also use tools like Google Analytics or Hotjar to understand how your audience interacts with your data visualization, what they like and dislike, and what they learn and do. Based on these insights, you can make improvements or changes to your data visualization as needed.

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?