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The more data, the easier it is to persuade customers to purchase our products and services, right? Data can help build consumer trust, set you apart from your competition, and create product worth. Unfortunately, many marketers and companies fall short of creating effective data visualizations that bring value to consumers.
The best data is data that is easily understood. Using visualizations to convey facts is key for a successful marketing strategy. Data visualizations can vary from simple graphs to detailed infographics. Knowing how to create and use these visualizations effectively will mean the difference between providing either value or information overload to your customers. Use these helpful tips to create valuable data visualizations.
Image via Flickr by morebyless
We’ve all been there before, overwhelmed with data, trying to make sense of all the numbers shoved in front of us. As marketers, we bombard consumers with statistics and facts. Before you begin to convey your data visually, start with good data. Good data includes statistics that are accurate, concise, and valuable. Being truthful when you’re displaying data will assist in establishing trust that you have a high level of expertise in your field. Use data that is meaningful and memorable to the reader. Information that is common knowledge is not adding value to your visualizations. Once you decide on the appropriate data to use, do not forget to source it.
Proper data visualizations tell a story. Use facts and statistics that enhance and complement your content instead of using them as filler. Charts, graphs, and maps help grab the reader’s attention while presenting your most important data throughout your content. How do you tell a story with data? Harvard Business Review’s article by Jim Stikeleather suggests a few pointers to help with creating a story through your data visualization. With any type of visualization you choose, use it to boost your message.
Bar graphs, pie charts, icons, or infographics? When creating effective visualizations, choose the appropriate graphic to display your data. The goal of visualizations is to convey your data accurately and easily for readers to understand. Using an incorrect method to express this data can confuse readers and consumers, or even have your data misinterpreted.
To help determine which graph or chart will be the most effective for your data, ask yourself a few questions. What is the purpose of your data? Define your facts and how you want readers to interpret them. Bar graphs should be used to compare data, pie charts to analyze portions of a whole, line graphs to show statistics over time, icons to represent data, and infographics to convey larger amounts of information.
One of the biggest mistakes people make when creating visualizations is not keeping things simple. Many visualizations are over-designed, over-complicated, and cluttered with too much data. While it might be tempting to add as much as you can, keep in mind you want people to quickly and easily interpret the information. Over-designed graphics can be an eye sore to readers and divert their attention elsewhere. If there is too much data being displayed, your reader will not know what information to focus on.
The way a visualization is organized greatly impacts the effectiveness. Charts and graphs can be disorganized, often leading to incorrect data interpretation and unappealing visuals. Organize your information in a common, simple way for readers to digest. Pie charts should be organized with the portions descending in either a clockwise format or counter clockwise format. Arrange any labels or bullets alphabetically. You can vary the types of visualizations types used throughout your content, just be sure to keep your formatting style the same.
While you want to keep things simple, don’t forget to add proper design elements to your visualizations. Design elements should be used to pull the reader’s eyes to your data, not crowd the information. Simple design elements are key. Use a complementing color scheme for your visualizations, just do not use the entire rainbow. Complementing color schemes can make the most important information “pop” or keep your story flowing. Bold font or vary font and image sizes to display pertinent data. There are many design elements you can add to your visualizations that enhance your data and message, while still keeping things simple.
Label your data visualizations to help clearly describe your figures, statistics, and overall message. Give as much information as you can so the data is easy to comprehend. A title explains what the readers will be interpreting. An axis on a chart or graph depicts how the data is measured. Headlines help break up your data throughout your story. Try not to use a legend or key when creating visualizations, as readers will have to look at the graphic then back to the legend to find out what each means. This could confuse some people, adding more work for the reader, and cluttering your visualization.
You are not alone when creating effective visualizations. There are many programs you can utilize to help you. Discover a few options and use one that fits your expertise level. Nishith Sharma, co-founder of Frrole, recommends using Datawraper or Tableau if you do not have developer knowledge. If you have knowledge in developing and coding, D3.js or FusionsCharts are a couple of the top programs chosen.
If creating your own visualizations is unfeasible or a daunting task, use a production company to manage and create effective content for you. Production companies can be used as an external marketing team. They have the ability to create consistent, branded visualizations without the time or employee expense. Designers can be expensive payroll additions that might not be needed full time.
Outsourcing creative work will allow you to utilize professional designers without adding the extra expense of another staff member. Choose a production company that uses internal client managers to consolidate communication and be your brand advocate, and one that offers multiple levels of editing and quality checks.