Forum Discussion
How to calculate coverage rate
- Anonymous2 years ago
Hi Anonymous ,
For future reference, if you want to count the number of unique customer IDs for each client classification, you can use the following DAX formula:
UniqueCustomers = CALCULATE(DISTINCTCOUNT('Interactions'[customer ID]), ALLEXCEPT('Interactions', 'Interactions'[ClientClassification]))This formula will count the number of unique customer IDs for each client classification, regardless of the filter context.
To calculate the percentage covered vs the universe in each classification, you can use the following DAX formula:
Coverage = DIVIDE([UniqueCustomers], 'Classification'[totalTier1])As for the visualization, a doughnut chart is a good option to show the percentage covered vs the universe. However, you might also want to consider using a stacked column chart to show the total number of unique customers for each client classification, with the percentage covered vs the universe as a data label.
Best Regards,
Neeko Tang
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi Anonymous ,
For future reference, if you want to count the number of unique customer IDs for each client classification, you can use the following DAX formula:
UniqueCustomers = CALCULATE(DISTINCTCOUNT('Interactions'[customer ID]), ALLEXCEPT('Interactions', 'Interactions'[ClientClassification]))
This formula will count the number of unique customer IDs for each client classification, regardless of the filter context.
To calculate the percentage covered vs the universe in each classification, you can use the following DAX formula:
Coverage = DIVIDE([UniqueCustomers], 'Classification'[totalTier1])
As for the visualization, a doughnut chart is a good option to show the percentage covered vs the universe. However, you might also want to consider using a stacked column chart to show the total number of unique customers for each client classification, with the percentage covered vs the universe as a data label.
Best Regards,
Neeko Tang
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.