Raw data is tough to process when you’re fresh off your morning coffee, but even after a jolt (or two) of caffeine, drawing accurate conclusions from a mess of numbers is tricky at best. While the neatly stacked rows might tell a story, it isn’t easily digestible for any team member to view. This is where data visualization comes in.
So, what is data visualization exactly? It’s the process in which raw data (i.e. spreadsheets) transforms into a form that quickly communicates key points. While there are a variety of tools for this, Excel is common. You can use charts and graphs of various colors to illustrate your data that help viewers draw out the critical information contained inside.
Working within a CRM, this process is expedited as you create reports that pull the data straight from inside your CRM. You determine what you want in your report and instead of manually working through all the functionalities of Excel, the CRM handles the legwork for you.
Why data visualization matters
Converting data into a visual seems like a simple enough task with available software. Yet, that’s not the only factor. It’s also important to think about who the audience is. Determine who is viewing the data and what conclusions will they draw from it before you begin. Poorly formatted visuals or those that don’t emphasize the right takeaways can negatively impact the amount of time users spent interpreting the results or, even worse, lead them to draw inaccurate conclusions.
Essentially, a viewer’s ability to understand and retain the information you provide to them largely hinges on how well you present it. Seeking out trends and attempting to make projections are both major components of what data visualization is about.
How to create data visualization effectively
The best way to present your data visualization, as mentioned above, largely depends on the type of data, who your audience is, and what you’re trying to communicate. For example, sharing a set of data aggregated from a complex machine learning program with a group of researchers will look much different than the visual for a set of monthly analytics for a marketing team.
Popular formats include:
- Infographic
- Pie chart
- Heat map
- Scatter plot
- Histogram or Line plot
- Timeline
The accessibility of your data also depends on how well it is visualized. You may be able to understand and see the meaning behind the raw data. However, it might appear as a mess of information to the untrained eye.
Before you present your next set of data to anyone else, consider the importance of how its visualized. Think about how that might affect what your audience gets out of it. Doing so will ensure that your efforts in collecting and interpreting the data won’t be for not.
Curious to learn more about data visualization? Need help producing impactful reports within your CRM? Contact us today.
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