Data visualization is defined as the filmic display of data. It will help you understand your data before you take any marketing decisions. Especially when we talk about digital marketing, it is essential since the variety of sources can gather the visitors metric quickly. In addition, it uncovers the patterns, trends and correlations in your marketing data.
If you have no idea what marketing solutions you should buy before engaging in production promotion, you need to excerpt your existing marketing report. Then, you can draw a chart that will compare the potential of your business on different platforms. This will help you make the right decisions for your business.
Data visualization will also help you tell stories by using pie charts, bar charts, and word clouds and creating heatmaps. Now, as we have seen briefly, data visualization lets us dive deep into it to see the types and why they are necessary for your marketing business.
How to Use Data Visualization?
Data visualization will help you combine your data with excellent visual design and keep your audience engaged. Data visualization enables you to visualize your data and data analysis, understand patterns, find relationships and more. But first, let us explain to you in-depth what we are talking about.
The first and most important thing. Data analysis will help you discover the different stories relevant to your business and help you get more ideas. Meaningful data divides the data into different ways in search of patterns that will reappear over some time between categories and across spaces. Now, most of these analysis depends on patterns and relationships.
Patterns will help you to look out for what is going to happen in the future. Suppose, for example, and you will invest in the stock market. There you go. You will have a visual view of whether to invest or not. So it is you are predicting how things will work for you in future.
For better marketing, the relationship in data is about finding correlations. Suppose, for example; you want to give your customers discounts, so you can have more chances of selling more products. So to achieve result-oriented data visualization, you should invest in quality data analysis.
Types of Data Visualization
Line Charts for Showcasing Trends
You can use line charts to show an entire shift or change concisely. Line charts are easy to understand the change in the results and are useful in explaining several categories over time. You can look at the image below to see the line charts.
Column Charts for Comparison
Column charts will help you compare the difference in the results. For example, you sell different types of products, so you can use these charts to compare the sale between them. You can also see the change that will happen over a period of time.
You can break down the bar charts into colour-coded sections to look for different results. You can compare different values using bar charts. It is like another different but similar type of column chart.
Bubble charts are similar to scatter charts, but these are better. Can you imagine they actually showcase the weight of the result values using the circle’s circumference. Another thing that will make the difference is that they pack several different values into a small location and portray a sole measurement per section.
Funnel charts are pretty attractive. They will show you the decreasing values like a funnel of the client journey in your business. It will help your conversion rates come alive with each step. In addition, this will help you detect where your buyers are exiting each stage through the funnel.
Benefits of Data Visualization
With raw data, you will only get the numbers, but with the help of visual data, you can easily spot patterns, designs and correlations.
Going through spreadsheets can be mentally draining for anyone. But with the help of visual data, you can easily simplify spreadsheets with understandable information without mentally draining yourself. And also, your audience needs relevant information without getting stressed out.
Data visualization will help lower content overload since we don’t want our customers to get bored. If you give them leveraging visual data, they won’t lose interest.