Investopedia defined cluster analysis as a technique to group sets of objects with similar characteristics.
If we look at the scatter chart below, what insights can we derive from it?
The good thing is that you can transform absolutely nothing into something by creating clusters for these customers.
Now let’s group these customers by profit and let’s see the behaviour of these customers in those clusters.
To carry out cluster analysis, we need to make an assumption. My assumption is as seen in the image below.
Our assumption is that if a customer's profit falls between $0 and $5000, place that customer in the fair customer cluster. Here we have four different clusters.
Now we have to find a way to incorporate these clusters into our data model.
Since it is a customer cluster, we will incorporate it into the customer table. The data model is a pretty straightforward one.
The DAX formula incorporates each customer into a cluster based on our assumption.
Note that we could have created assumptions over another metric, e.g. profit margin, revenue, etc.; it doesn’t have to be profit. Let’s see how this DAX works in Excel.
No inference can be derived from the chart on the left, but by creating clusters, we can make better inferences.
As an organization, you can start creating strategies around this, e.g., making customers regarded as good customers spend more. Say the organization can move 50% of customers in the good customer cluster into the Top customers; that’s massive revenue growth.
That’s all on cluster analysis. See you next time