Tableau Clustering

Clustering in Tableau automatically groups similar marks together based on selected measures, using the k-means algorithm - useful for spotting natural segments in data without manual analysis.

Adding a Cluster

Build a scatter plot (or any view with multiple measures)
Analytics pane -> drag Cluster onto the view
Choose the number of clusters, or let Tableau determine it automatically

How It Works

Tableau's clustering uses the variables placed on the view (typically on Rows, Columns, and Color/Size) to calculate distances between data points and group the closest ones together.

Interpreting Clusters

Each cluster is automatically assigned a color, and a Clusters card in the view shows summary statistics for each group, helping you understand what separates one cluster from another.

Common Use Cases

• Customer segmentation based on spending and frequency.
• Grouping products by price and demand patterns.
• Identifying outlier groups within operational data.