Impossible?

powerbiuser9999 Sure, here it is with comments:

Measure =
  // Get a distinct single column table of customers that have bought Instore
  // Since we need to filter the table for Instore, we need to use SELECTCOLUMNS
  // to return a single column from the FILTER statement and then apply DISTINCT
  // to only get the unique values. We set this table variable aside until the end
  VAR __Table = DISTINCT(SELECTCOLUMNS(FILTER('Table',[Type of Shop] = "Instore"),"Customer ID",[Customer ID]))
  // This is the tricky one. We start with a distinct list of customers and then add 
  // two columns that use the iterator function, MAXX to return the highest rank for
  // Instore and Online. The columns are called "Instore" and "Online" and the only
  // difference is the filter for Type of Shop. Each column calculation starts by 
  // getting the "current" value of [Customer ID] for the row and then uses that as
  // part of the filter clause to ensure we are getting the rank for that customer.
  VAR __Table1 =
    ADDCOLUMNS(
      // This is the start of the table.
      DISTINCT('Table'[Customer ID]),
      // Adding Instore column.
      "Instore",
        // This is the calculation for the Instore column, nested VAR and RETURN
          VAR __Customer = [Customer ID]
        RETURN 
          MAXX(FILTER('Table',[Customer ID] = __Customer && [Type of Shop] = "Instore"),[Rank of shops]),
      // Adding Online column
      "Online",
        // This is the calculation for the Online column, nested VAR and RETURN
          VAR __Customer = [Customer ID]
        RETURN 
          MAXX(FILTER('Table',[Customer ID] = __Customer && [Type of Shop] = "Online"),[Rank of shops])
    )
  // Now we use Table1 to create a new table var that simply filters our __Table1 where
  // the Online rank value is greater than the Instore rank value. We also only want the
  // customer IDs so we use SELECTCOLUMNS again to just grab that column.
  VAR __Table2 = SELECTCOLUMNS(FILTER(__Table1,[Online] > [Instore]),"Customer ID",[Customer ID])
RETURN
  // We now have two table vars, __Table and __Table2 that each have single column of 
  // unique customer values. __Table lists customer that have bought Instore and __Table2
  // has a list of customers that have an Online rank that is higher than the Instore rank
  // so, since we want customers with an Online rank higher than Instore rank that have
  // also bought Instore, then we want the INTERSECT of the two tables (basically the values
  // that exist in both tables). We then simply use COUNTROWS to count the number of rows
  // in the intersection of the two tables.
  COUNTROWS(INTERSECT(__Table2, __Table))