In this example, we want to categorize customers based upon their relative contribution to revenues. We will do this by first categorizing them according to revenue category. The categories will be in ranges of $1000, and range from $0-$1000 to $199,001-$200,000.

We create a single dimensional analysis, where the only dimension is revenue category. The volumes that are sliced-and-diced are customer count, revenue, and widget count. Once we have that analysis, we put it into a spreadsheet, sum the total revenue and customer count, and calculate the contribution toward total revenue for each cell. We also calculate the contribution toward total customer count for each cell. This allows us to determine what percent of customers contribute what percent of revenue.

In the analysis, MAST (our tool) has created the following columns:

• Revenue Category (A customer categorization based on total spending for each customer)
• Customers (Count of customers in each category)
• Widgets Purchased (Total number of widgets purchased by customers in each category, for extra information)
• Revenue (Total revenue for customers within the categorization)

The business wants two customer lists:

1. Those who are in the 0.18% that contribute 42% of the revenue
2. Those who contribute the remaining 8% of the upper 50% of revenue

1. Contribute over $1999
2. Contribute over $999, but less than $2000