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Hello hoping someone can help with my query
I have a set of telephone data as below and I need to add together the talk times and wrap times (as seperate figures) where the same phone number appears on the same day, thus giving a total amount of the for each customer on each day. I also need to factor in the queue and be able to do a calculation based on each queue name, so it would be per customer, per day on an individual queue. I thought about adding a custom column with an if calculation but then it will add a total on each line the phone number appears and then it would make the calculations for the visuals difficult to create.
Would creating a new table for the data be the best way to go? Maybe adding an index column and then creating variables to add together the calls from the same day?
for the output/visual I need to calculate the average talk time and wrap time per customer, per day, per queue.
For example:
01234 567890 had 3 calls on one day, one 1234 minutes on outbound 1, one 2345 minutes on outbound 2 and one 345 minutes long on outbound 1, so the total amount of time would for this customer on that day would be outbound 1, 1579, and for outbound 2, 2345.
02345 678901 had 1 call on the same day lasting 3456 minutes on outbound 1
Add together the talk times and divide by the number of customers per queue:
outbound 1= 1579+3456=5035/2=2517.5
outbound 2 = 2345/1=2345
So the average call length per customer for that day would be 2517.5 for outbound 1 and 2345 for outbound 2
Any help on how best to do this would be greatfully received
Ignore the average in the column header for wrap, it is the total time for each call not the average in that column
Solved! Go to Solution.
Thanks for this but unfortunately didnt quite work for how I need the visuals, it has been really useful though as I used the basis to create a table and the created measures from that table
Table
what is your definition of "Day"? Single timezone? What should happen to calls that cross past "midnight"?
@AllisonB , better to measures
talk time Measure= Sum([Talk Time])
Avg per customer = Sumx(Summarize(Table, Table[Customer]), [talk time Measure])
Avg per customer per day= Sumx(Summarize(Table, Table[Customer], Table[Date]), [talk time Measure])
Avg per customer per day per Q= Sumx(Summarize(Table, Table[Customer], Table[Date], Table[Queue]), [talk time Measure])
Thanks for this but unfortunately didnt quite work for how I need the visuals, it has been really useful though as I used the basis to create a table and the created measures from that table
Table
Hi @AllisonB,
Kindly try the DAX calculations provided below. If the issue still persists, please share the sample data in a workable format (such as text or an Excel file, rather than screenshots), along with the expected output. This will help us assist you more effectively.
Create an aggregated table
CustomerDailySummary = SUMMARIZE('Outbound Calls',
'Outbound Calls'[Date],'Outbound Calls'[Customer Phone],'Outbound Calls'[Queue],
"TotalTalkTime", SUM('Outbound Calls'[Total Outbound Talk Time]),
"TotalWrapTime", SUM('Outbound Calls'[Average Outbound Wrap Up Time]))
Measure:
AvgTalkTimePerCustomer =
AVERAGEX(FILTER('CustomerDailySummary', 'CustomerDailySummary'[Queue] = "Outbound 1"),
[TotalTalkTime])
Measure:
AvgWrapTimePerCustomer = AVERAGEX(FILTER('CustomerDailySummary', 'CustomerDailySummary'[Queue] = "Outbound 1"),[TotalWrapTime])
I've already solved it, please see my reply above, I have now marked it as solved to stop any future confusion.
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