Our metrics range from the simple to the complex. Here is some discussion to while away those hours when there is nothing interesting on Cable.

$, or Dollars

There are several choices of how to represent this spending metric.  You will need to visit the individual report’s help page to read which one was used for your report of interest.  Here are some formula we have used

  • list – this would be just adding up the “list_amt”, or list price, column in the transaction data
  • net – this is the list price less the item specific markdown, or discount, amount.  So, this represents the price paid, but does not consider any transaction, or basket level discounts.
  • net plus tax – this is like net but includes any taxes paid. It is usually only used at the transaction, or basket level as there is not a convenient way to allocate basket level taxes to individual items.


quantifies the relative performance of a subset of things contained in a larger group of things to the performance of the larger group of things.  In our normal context “things” could be shoppers, or stores, or products.  For example, “Did the shoppers in the Diamonds segment spend more or less per capita than the average shopper?”

Calculated this way

100 * (Dollar spend by Diamonds / Count of Diamonds shopping)  / (Dollar spend by All Shoppers)/(Count of All Shoppers)

it is read as “compared to 100″.  So, if the Diamond Shopper Index is 145 that would mean that an average Diamond shopper spends 45% more than the Average shopper.  100 indicating average performance.


quantifies how likely a shopper who purchased product (group) A is to purchase product (group) B by showing what percentage of shoppers who purchased product (group) B also purchased product (group) A.


  • 41% of the shoppers who bought Cheerios also bought Frosted Flakes.  Here Cheerios and Frosted Flakes are each Brands representing a group of SKUs.
  • 18% of the shoppers who bought 18 oz. Cheerios also bought 24 oz. Frosted Flakes.  Here Cheerios and Frosted Flakes are each individual SKUs.
  • 84% of shoppers who bought Beer also bought Salty Snacks.  Here Beer and Salty Snacks are product Categories representing a group of SKUs.

Clearly the selection of the granularity of the product groups being compared

  • individual SKUs
  • categories
  • departments
  • brands

strongly affects the informational content represented by the propensity figure.