How to do a Scatterplot in Tableau?

Preparation time: 5 minutes

Level of difficulty: Easy

Objective: Make a Scatterplot chart

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The scatterplot, or scatter plot, is an essential tool for visualizing the relationship between two quantitative variables. In this guide, we'll take you step-by-step through building a scatterplot in Tableau Desktop. This type of graph is particularly suitable for identifying trends, clusters, or correlations within your data.

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Data required

• 1 data set, such as the Email Performance Overview accelerator,
• 2 measures, such as the number of emails sent and the number of emails opened,
• 1 dimension, such as IDs, Countries, or Geographic Areas.

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Instructions:

1. Swipe the measurement Feel email In the Columns,
2. Slide in the second measure Clickthroughght Emails In the Lines,
3. Slide the dimension Mailing ID in the tab Details of the landmark,
4. Add a Trend line from the tab Analysis.

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Analysis

This scatterplot analyzes the relationship between the number of emails sent and the number of clicks obtained. Each point represents a unique email campaign, identified by a “Mailing ID”.

In this example, we see a positive relationship between these two variables: as the number of emails sent increases, the number of clicks tends to follow the same trend. However, there are some points that deviate from the trend line, highlighting campaigns where the click rate is disproportionate to the volume of emails sent. These differences reveal atypical performances, whether above or below the norm. Analyzing these specific campaigns can provide us with valuable insights into the factors that influence their success, such as email content, target audience, or when they were sent.

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Advice

Here are some tips for analyzing and getting the most out of your scatterplot:

• Use the trend line to visualize the general direction of the relationship between the two variables. An ascending line indicates a positive correlation, while a descending line indicates a negative correlation.
• Spot The points that deviate significantly off the trend line, as they may indicate data with exceptional performance or anomalies that deserve further analysis.
• Use colors, sizes, or labels to distinguish and identify data according to additional criteria.
• Be careful Read the scales the axes of a scatterplot to ensure accurate interpretation and optimal understanding of the data.

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