How to Design Attractive Data Visualizations for a Business Blog

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Ronita Mohan
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越来越多的企业在其内容中采用数据可视化实践. This isn’t surprising considering how much data is now being shared online.

数据可能非常令人兴奋,但原始数据并不总是能讲述一个令人信服的故事. Not to all audiences.

On the other hand, a data visualization infographic, like the below example, shares a memorable story.

computer consumer stats

Source: Venngage

还有另一个重要因素促成了数据可视化的日益流行. We have more content available to us than time to absorb it.

Online users simply do not have the time to read paragraphs of text. They want their information condensed and easy to skim. A visualization makes that possible.

Designing visuals has also become easier for marketers, which is also why we are seeing more cohesive visuals.

There are numerous data visualization tools at marketers’ disposal. 例如,一个简单但有效的设计,如下面的报告,可以在几分钟内使用 graph maker.

toronto real estate

Source: Venngage

So, what is data visualization? And how can marketers create attractive visuals for their business blogs? We explain it all in this guide.

What is data visualization?

A good data visualization combines three key aspects:

  • Data on a topic with a precise angle
  • A functional and purposeful visual
  • A design that is impactful but balanced

Instead of trying to define data visualization, why don’t I show you what it is via this visualization?

Source: Venngage

The important thing to remember is that one can’t just take some data, put it together in a visual format, and call it a day. That isn’t the purpose of this exercise.

Data visualizations are meant to communicate information on their own. But they also need to be creative and appealing to engage the audience.

What is the importance of data visualization?

大数据可视化设计可以将复杂的信息压缩成易于理解的图形. 这是因为数据可视化使用了讲故事的方式来传达信息.

Since human beings love stories, a data-driven approach to marketing helps build connections between users and brands.

For example, this report was created using data about potential audiences. 它帮助品牌计划和预测,使他们的产品和营销活动反映消费者的需求.

Source: Venngage

What else are data visualization techniques used for? Here are a few use cases:

  • Making complex data interesting and understandable
  • Backing up an opinion with facts
  • Presenting patterns between data points
  • Highlighting important data points to audiences
  • Storytelling through data

There are numerous data visualization types, and they can be used for multiple purposes:

  • Bar graphs
  • Infographics
  • Line graphs
  • Maps
  • Pie charts
  • Scatterplots
  • Timelines
  • Venn diagrams

While maps are great for showing geographical information, other types of data visualizations, like bar charts, are better for displaying comparisons between data points, like this example.

Source: Venngage

Choosing the right visual to convey your message takes time and practice. 如果做得好,出色的视觉效果将有效地传达一个故事,并产生一个新的线索.

7 Data Visualization Best Practices

你如何创造漂亮的视觉效果,与观众简洁地分享数据? 十三水游戏提供了一些产生数据可视化想法的技巧以及7个最佳实践.

1. Understand your audience

最好的数据可视化例子是品牌采用移情方法的结果. You have to ask yourself: what does my audience need from this visual?

品牌为其产品和营销活动创造了理想的用户角色. Use a similar technique to generate ideas around data stories. This will help make the visual more impactful.

Here are a few user-related questions to ask before you start designing:

  • Who is the target audience for the data story?
  • What are their frustrations/ pain points that the data will resolve?
  • Is the data for mass consumption or does it have a narrow focus?
  • What metrics or KPIs is the visual supposed to help you reach?
  • What action do you expect audiences to take when they see the visual?

例如,下面的信息图很大程度上是信息,吸引了更广泛的受众.

On the other hand, if your target audience is very niche, your data visualization can be more complex. You can also include niche terms because the audience will understand them.

But most importantly, your visuals must have an aim. They must evoke the audience’s need to act. This will help you create content that is actionable and measurable.

2. Source your data

Before you begin designing your visuals, you need to collect your data. This process sounds simple but it requires some nuance.

Data should be collected from trusted sources and verified. This is to ensure that the data isn’t biased in any way. If you can’t find the source of the information, don’t use it.

Additionally, verify the data you have with at least two other sources. Use this technique to prove that conclusions weren’t reached by fluke.

When doing your research, 从尽可能多的受访者那里收集数据,这样你的结果就不会有偏差. This infographic from Workfront includes data from 2000 workers.

Source

Also note how the graphic uses simple data visualizations, alongside icons, so that the information is easy to understand by all audiences.

It’s worth using a data quality tool to parse through large amounts of data and remove any irregularities.

3. Choose your visuals

Jumping off of the previous point, 您需要为您的主题选择正确的数据可视化图.

如上所述,不同类型的数据适用于不同类型的可视化. 使用错误的图表会使数据对受众产生混乱,甚至误导.

How do you choose the right visualization technique for your data? You have to determine the purpose of your data story first. This can be broken down into five categories:

  • Informing the audience
  • Comparing data
  • Showing change over time or area
  • Showing how data is organized
  • Showing how data points are related

下面的图表说明了这些点,并分享了在每个实例中使用的最佳图表类型.

For example, if you want to compare multiple data points, bar charts, pie charts, and word clouds are the best tools.

要显示随时间的变化,折线图、区域图或时间线是最好的选择. You can use a map chart to show changes over locations.

Venn diagrams and tables are best for showing how data is organized. 散点图或直方图表示数据点之间的关系.

With a bit of practice, 它将更容易确定哪种类型的可视化适合您的数据. 在那之前,你可以使用十三水游戏分享的图形指南来帮助你做出决定.

4. Chart axes and labels

As important as it is for your visuals to do all the storytelling, 最好的数据可视化方法包括提供数据上下文的轴和标签.

For example, this fun pie chart infographic uses icons to denote the data its describing, alongside text labels.

用户只需看一眼披萨图形就能知道他们需要知道的一切,他们还可以查看标签以了解更多细节.

While designing data graphics, always include the axes and keep them equal. 这有助于避免数据失真,让你的视觉效果看起来更可信.

Additionally, 坐标轴使十三水游戏更容易理解数据的数量和分布,以便进行比较.

5. Create visual connections

Great data visualization ideas focus on telling a story. 最好的方法是使用视觉线索,让故事更容易理解和消化.

Icons are a great graphic design tool to incorporate in data visualizations. 他们立即吸引眼球,同时也传达了广泛的信息一眼.

使用图标的最好的数据可视化例子之一是比尔和梅琳达·盖茨基金会关于世界上最致命的动物的这个例子.

Source

越来越大的图标显示了动物有多危险. 线条的长度加强了这一点,也促使人们的视线向下移动.

6. Data highlights

What do good data visualization examples have in common? Colors used with purpose.

光谱是巨大的,它可以诱惑使用尽可能多的颜色为您的数据. But color should be used to highlight information; not to drown it.

For example, this graph on sports franchises uses colors to differentiate groupings, making it easier to follow the information.

Source

这是一种简单而有效的方法来分组数据点,并将用户的眼睛引向一个主要结论——某些运动队赚的钱比其他运动队多得多.

另一方面,这个看似简单的图形在黑色背景下只使用了两种颜色. The point of the limited color use is to highlight key information.

You can also use fonts to highlight information. 在图像中加粗或加下划线显示重要文本,以便用户能够立即看到关键信息.

7. Diversity in design

多年来,设计领域一直缺乏一定程度的公平性. 但这种情况已经发生了改变,越来越多的人开始呼吁创造包容性的视觉效果.

Here are a few ways that brands can start designing for diversity in data visualizations:

  • Collect and analyze data without bias
  • Include designs—such as illustrations and icons—that are representative
  • Use inclusive language in designs
  • 注意颜色,以便有视力障碍的人能够看到
  • Get feedback on inclusive designs and data from representative groups

Brands should take the time to educate their staff and executives on diversity. 这张关于多样性和包容性术语的图表可以与团队共享或包含在新员工中.

The best data visualizations tell compelling brand stories

视觉内容营销已经成为一种与消费者联系的强大手段. And one of the essential elements of visuals lies in data.

虽然有很多数据需要挖掘,但品牌需要记住这些数据的目的是什么. Collect data according to the stories your customers want to hear.

一旦收集了数据,创造有吸引力但有目的的视觉效果来分享你的故事. 对于没有内部设计团队的品牌,可以使用数据可视化工具.

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Ronita Mohan

Ronita Mohan

Ronita Mohan is a content marketer at Venngage, the online infographic maker and design platform. 罗妮塔定期撰写有关数字营销、视觉设计和小企业成长的文章.

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