Trend Calculation in Web Analysis

Question

I am creating a sales and margin trend analysis in web analysis and am having problems making the trend calc dynamic. I select period and use a sub variable to select (CMCY) and then show subset to show the previous 2 months to give a 3 months trend view. I can use the trend calc to develop a revenue trend based on the revenue measure but I have to use advanced and select the actual months ex Revenue:Oct, Revenue:Nov, Rev:Dec. The calc works correctly this way, but next month it will not. How can you grab current month, then CM-1, CM-2 into the trend calc directly so you don't have to reformat the report each month? Thanks for the help.

Answer 1

I have never done this before but may work just like following.
Following is from HR user guide:
Count
Count is a mathematical function that returns the number of values in a group of numeric values,
rows, columns, or cells. Count excludes #missing and #error when obtaining the count. The
function syntax is:
Examples:
The following example returns the count of three rows, 1, 6, and 8:
Count(row[1], row[6], row[8])
The following example returns the count of 3 columns:
Count( column[E], column[G], column[I] )
The following example calculates the count of two columns located on different grids:
Count( grid1.column[E], grid2.column[E] )
The following example calculates the count of the cell located at row 4, column D:
Count(cell[D,4])
The following example calculates the count of aggregate row 3 in grid 5:
Count(grid5.row[3])
CountA is a mathematical function that returns the number of values in a group of numeric
values, rows, columns, or cells. CountA includes #missing and #error cells when obtaining the
count only for rows or columns that are not suppressed.
Example
In the following example, if a grid has 4 rows with the values 10, 20, 30, and, #error. The following
formula in the 5th row returns the count of four rows:
CountA([1:4])
The following example returns the count of four rows:
CountA(row[1], row[6], row[8] row[where data yields #error])