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Helper I

## Analyzing sales data by quote size

Hi folks, I must be having a brain fart today because my question seems so basic.

I have transactional level sales data that looks like any other sales data - customer names, line item numbers, regional info, sales, discounts, profit, item number, etc.  The data are broken out into line item level of detail meaning I have multiple rows of data for each sales order number.  All I want to do is analyze my data for sales orders that are below \$1,000,000 total value.  Then I want to analyze my data for sales orders that are between \$1,000,000 and \$5,000,000.  Lastly I want to analyze my data for sales orders that are greater than \$5,000,000.  What is the easiest way to do this?  I do not need enything exotic.

Putting Sales Order# in a filter and filtering the Sales Order# on sum of Total Revenue = "what ever value I need" would do the trick.

Thanks!

1 ACCEPTED SOLUTION
Helper I

Hello @amitchandak , I figured it out!  I created a calculated column with the following code

Quote Size = Calculate(Sum(Table[Quote \$)]), ALLEXCEPT(Table,Table[Quote ID]))

From this column I can create a second column that uses a nested IF statement to define my bin sizes.  Its primative but effective.
4 REPLIES 4
Super User IV

@Frenchtom811 , if you want to bucket data after adding up, means bucket on the measure you need to do dynamic segmentation or binning

Refer my Video: https://youtu.be/CuczXPj0N-k

or

Proud to be a Super User!

Helper I

Hello @amitchandak and thanks for your response.  These solutions look promising but also very complicated.  All I am really trying to do is group my sales orders into 3 categories as described in the original post.   Is there a simple DAX expression I can write that will group my sales order numbers into one of 3 categories based on total sales order value?  I need to slice and filter on these 3 groups so that I can analyze the sales order profiles (customer types, products, profit, etc.)  Creating a separate bin table that has no relation to my sales table means that I cannot filter/slice my sales table using bins defined in the bin table.

Super User IV

@Frenchtom811 , if you need bucket on the measure (means after aggregating the data) , I doubt there is not simple way.

If it is on the line level data, we can always create a new column

New bucket column =

Switch( True() ,

[sale] < 50000, "  less than 50K",

[sales] <100000, " from 50K to 100K",

"Others" //default

)

Proud to be a Super User!

Helper I

Hello @amitchandak , I figured it out!  I created a calculated column with the following code

Quote Size = Calculate(Sum(Table[Quote \$)]), ALLEXCEPT(Table,Table[Quote ID]))

From this column I can create a second column that uses a nested IF statement to define my bin sizes.  Its primative but effective.

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