This report gives us some idea about cross purchasing at the specified level of item aggregation.  You have quite a bit of flexibility to define the product universe of the report with an attribute value, then to define the cross purchasing granularity by selecting a different attribute. Propensity


  • Location – Standard Location selector(s).
  • Time – Standard Time selector(s).
  • Product –
    • Product Universe – Select a value of a PRODuct attribute, like, Manufacturer Procter & Gamble.  The item aggregates in the report will all only contain items with the product attribute of Procter & Gamble.
    • Group Products by – Select a PRODuct attribute, like, Brand.  The report will aggregate P&G items into their BRAND groups and that will be the granularity for the cross purchase analysis

Other Filters

  • This report excludes information households, and their data, who had 3 or more transactions per day in the timeframe of the report.


  • Focus Product Group – The report data cube contains all the cross purchasing behavior, but displaying all those pairs would be confusing so the report displays the cross purchasing of all product groups against the single Focus Product Group on the page slicer selection.


Rows represent items aggregate groups defined by the “Group Products by” selection.


Grouped by across headings

  • Purchasing Metrics
    • Propensity – this metric is the number of households purchasing the Focus Product Group who also purchased the row item group, expressed as a percent.
    • Monthly Universe Spend for Bought Both – The total dollar spend on items in the Product Universe for households who purchased at least one item in both the page and row item groups.
  • Count of Households Purchasing
    • Both- bought at least one item in both the row and the page item groups.
    • Bought A – or Bought Page, bought at least one item in the Focus Product Group
    • Bought B – or Bought Row, bought at least one item in the row item group.