Tips and Best Practices for Trade Data Visualisations

Why is data visualisation important?

By converting data into graphical or interactive tools, data visualisation enables quick processing and comprehension of massive volumes of information. It can aid in your understanding of complex data by displaying complex data relationships and data-driven insights in an understandable manner.

When analysing data on global trade data, people normally find that it might be difficult to gain immediate insights into the links between trading partners. This occurs as a result of the data’s inherent complexity. However, effective trade flow trade data visualisations can improve our understanding of a country’s economic activity.

Using visual data, data visualisation offers a rapid and efficient approach to conveying information about trade data to all audiences. Additionally, the practice can assist companies in determining the variables that influence consumer behaviour, identifying areas that require improvement or additional attention, making data more remembered for stakeholders, figuring out the best times and locations to sell particular products, and forecasting sales volumes.

Trade data visualisation also offers the following advantages.

• The capacity to rapidly process global trade data, gain new insights, and make decisions;
• A better knowledge of the actions that need to be performed moving forward to have a deeper understanding of trade data analysis;
• An enhanced capacity for retaining the interest of the audience with trade data analysis information they can understand;
• A simple information flow that increases the chance of trade data insight sharing among all parties;

Types of trade data visualisations: An overview

Each of these trade data visualisations has its own unique features that make it suitable for specific types of data and analytical goals. Choosing the right type of data visualisation depends on the specific goals of the analysis and the nature of the data being presented.

1. Bar Charts

Bar charts are a useful way to display data that can be broken down into categories. They show how the values of each category compare to one another.

2. Line Charts

Line charts are used to display trends over time. They are particularly useful for showing changes in data over a long period. For example, it is suitable to show how Turkey’s inflation declines after a yearlong rally.

3. Scatter Plots

Scatter plots are used to display the relationship between two variables. They show how one variable changes in relation to the other.

4. Pie Charts

Pie charts are used to display the proportion of different parts of a whole. They are particularly useful for displaying data where the categories are mutually exclusive. Academic institutions and logistics companies often use pie charts for presentations.

5. Bubble Charts

Bubble charts are used to display the relationship between three variables. They show how two variables change in relation to each other, and how the third variable is represented by the size of the bubbles.

Tips for creating effective data visualisations for trade data analysis

There are several best practices for you to create effective data visualisations for your trade data analysis. The following are some tips especially for you that organisations can apply to have good trade data visualisations:

1. Have a clear purpose and audience

You won’t wander through your data aimlessly if you have a clear goal. The purpose of data visualisation for trade data analysis is to make the trade data more obvious and to quickly communicate insights from data to the user. Because they were not developed with a defined aim and audience in mind, visualisations all too frequently fall short of effectively sharing insight.

Narrow the purpose of the data visualisation and be aware of the audience it will affect, whether it is for you or for an internal or external audience. Your trade data investigation and trade data presentation should be guided by this. When choosing various trade data sets to examine, deciding how to compare various data categories, or constructing the final visualisation and determining what finishing touches to add, having a clear objective can help you know where to start.

2. Choose the right type of chart for your trade data

Your data story will either benefit or suffer as a result of the sort of chart you use. There may be a variety of charts that are useful, therefore it’s important to be extremely clear about your data visualisation’s aim and target audience because they can both influence which chart is most appropriate.

The best tactic is to select a chart that you are sure everyone can understand. In most circumstances, data visualisation is about getting the work done and having an impact on the organisation; it’s not about creating the most detailed, attractive chart you can. The easiest way to do it is to tailor your visualisation to the audience that needs to be moved to action.

3. Use colour to differentiate

Trade data visualisations that use colour can be more captivating and fascinating. But there have been instances of data visualisations when colour is overdone, misinterpreted, or serves to further confuse rather than to further clarify. Always make sure that colour makes the objective of your data visualisation clear and draws attention to it. You probably don’t require colour if it doesn’t aid interpretation or add new meaning.

The best method to use colour in your trade data visualisation is to draw attention to the information that the viewer needs to see. When your brain notices a stark difference in colour, it gives that difference a purpose and draws your attention to it more. Utilise this to your advantage to make it easier for the viewer to read your trade data visualisation and comprehend your conclusion. One typical scenario where colour is vital is trade show presentation – read here to learn more tips for a successful trade show.

PS: Read this blog post to learn about how to leverage Import & Export Data in Trade.

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