Product Metrics and Columns
For each of the myKaarma products we have a collection of metrics and calculated columns that you can request from our API. We are always adding new metrics and columns along with new products, and we are open to suggestions if you would like us to add more. You can see a list of many metrics within our Insights -> Advanced Search tool as well.
Now that you are familiar with the categories mentioned in the previous section, here is a simple example to help visualize them along with product metrics. Below you will see data from date 01/01/2023 for Dealer1 that only has two service advisors, User1 and User2. On the right side you can see we requested two metrics, ROCount and TotalTexts.
| Categories | Product Metrics | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Date | DealerUUID | DealerAssociateUUID | Department | OrderType | Brand | PayType | CPAmountRange | ROCount | TotalTexts |
| 01/01/2023 | Dealer1 | User1 | Service | RO | BMW | Customer | 1001-2000 | 2 | 5 |
| 01/01/2023 | Dealer1 | User1 | Service | RO | MINI | Customer | 1-1000 | 1 | 4 |
| 01/01/2023 | Dealer1 | User2 | Service | RO | BMW | Customer,Warranty | 2001-3000 | 1 | 6 |
In the data above you can see that User1 has a total ROCount of 3. You can also see that 2 of the ROs from User1 were for a BMW brand vehicle and both had a final CPAmountRange value between 1001-2000. You can also see that User1 had 1 RO for a MINI brand vehicle on the same date. User1 made a total of 9 text messages. Currently we have to calculate the totals manually because we didn't request a GroupBy which you will read about in the next section.
With this example you can imagine what would happen if we requested a CPAmountRange filter with 1-1000. We would get only a single record from User1 and it would be a single RO with a vehicle brand MINI.
Calculated Columns
You can also request calculated columns, for example percentages and averages. They are metrics which are precalculated on the server side. Here is an example request result for the calculated column OnlinePaymentIndex. I also added PaidROs and OnlinePayments which are the two metrics used to calculate OnlinePaymentIndex. They are not needed and only added here for clarity.
| Categories | Product Metrics | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Date | DealerUUID | DealerAssociateUUID | Department | OrderType | Brand | PayType | CPAmountRange | OnlinePaymentIndex | OnlinePayments | PaidROs |
| 01/01/2023 | Dealer1 | User1 | Service | RO | BMW | Customer | 1001-2000 | 50 | 5 | 10 |
| 01/01/2023 | Dealer1 | User1 | Service | RO | MINI | Customer | 1-1000 | 100 | 1 | 1 |
| 01/01/2023 | Dealer1 | User2 | Service | RO | BMW | Customer,Warranty | 2001-3000 | 0 | 0 | 1 |
NOTE: In a real-world API result we only return the metrics and columns that are requested. We don't always return the Categories as shown in the table examples above, that is just for visualization purposes.
The calculated column OnlinePaymentIndex is a percentage equal to ROUND((SUM(OnlinePayments)/SUM(PaidROs))*100,0) in SQL that we run on the database. You can see for User1 and all BMW vehicles with ROs in the 1001-2000 CP range the result is 50% because OnlinePaymets is 5 and total PaidROs is 10. This means 50% were paid online.
What if you want to see the OnlinePaymentIndex for all of User1? This is where GroupBys come into play. You can read about them in the next section.