As we explained,

in a previous blog, the goal of data visualization is to present large amounts of data in an understandable, easy to read way. By playing to our brains’ strengths, companies that use data visualization are five times more likely to make faster decisions and three times more likely to execute them! Since there’s a plethora of visualization types to choose from, picking the right one can be a challenge. In this blog, we will explore some of the various graphs businesses can use and explain the scenarios in which each one works best.

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Comparison Visualizations

This data visualization type uses charts, graphs, or diagrams to showcase the commonalities between variables. Bar and column charts are the most commonly used. They display categorical data through rectangular bars that are placed horizontally or vertically. Bar graphs, specifically, compare information from different groups and track changes over time. Your brand could use this visualization type to analyze product usage, marketing traffic, conversions, and more. Though similar to bar graphs, column charts are best at displaying negative data over time. Column charts are great for analyzing customer survey data, sales volume, and profit changes.

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Relationship Visualizations

Heat maps are a popular tool for visualizing relationships. They use color-coded systems to depict different values in a dataset. 42 percent of brands use heat maps to analyze behavior across their web and mobile sales. Heat maps can also identify where users have clicked on a website and how far they scrolled down. Similarly, tree maps illustrate part-to-whole relationships through colors and rectangles. The colors represent dimensions and measures. Viewers should also pay attention to the size of the rectangles. The largest rectangle shows the largest part of the whole while the smallest rectangle does the opposite. For businesses, tree maps provide insight into the performance of products and similarities between multiple categories.

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Pattern Visualizations

As the name suggests, line graphs convey changes over time through connected line segements. Since line graphs can track short and long time periods, the duration depends on the viewer’s preference. They can be used to find patterns among multiple groups in the same period or to measure how different groups interact. From a business perspective, line graphs are effective at comparing sales rates for different products and measuring the performance of service channels. Unlike line graphs, scatter plots use dots to indicate values for an individual data point. When analyzing large data sets, scatter plots make it easier to find similarities, outliers, and trends. Market research analysts typically use scatter plots to assess how demographic factors relate to consumer buying habits.

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Data Visualization Through Surf

Surf’s NLP dashboard with integrated AI breaks down ethically sourced data from various categories into intuitive charts. Our partners leverage the analytics to understand user demographic information, search habits, preferred social platforms, and more. Book a meeting to learn more about the insights that Surf’s dashboard offers.