Metric aggregators define how the data queried by a metric is calculated. For example, the metric **Full resolution time (days)** defaults to showing the median (MED) of the time in days it took to resolve tickets, but you can change the aggregator to show the average time, the minimum time, the maximum time and more.

Use this article to learn about the different aggregators you can use, and how to use them.

## Changing the metric aggregator

**To change the metric aggregator**

- In query builder, add a metric to the
**Metrics**panel. - Click the metric you added.
- From the list, select a new aggregator.
The available aggregators will differ depending on the metric you choose. Use the Metric aggregators reference to find out more about each aggregator.

- To save the new metric aggregator, click
**Apply**.

**Metrics**panel, click the down arrow next to the metric, and select the aggregators you want to use.

## Metric aggregators reference

Use this table to learn about the different aggregators and when to use them.

Aggregator | Description | When to use |
---|---|---|

COUNT |
Counts all values of an attribute. If the same value is recorded more than once, each occurrence is counted. |
Used for counting objects like tickets, calls, chats, users, organizations, etc. |

D_COUNT
(distinct count) |
Counts the number of different (unique) values. Values recorded more than once are counted only once. |
Used for distinct counting objects like tickets, calls, chats, users, organizations, etc. |

SUM |
Adds up all numeric values. |
Used for database counted, arithmetical operation and time duration metrics like Chat Messages, % Satisfaction Score, Resolution Time. |

AVG
(average) |
Calculates the arithmetic mean of numeric values. |
Used for time duration and database counted metrics like Resolution Time and Chat Messages. |

MED
(median) |
Identifies the numeric value that separates the higher half of the values from the lower half. |
Used for time duration and database counted metrics like Resolution Time and Chat Messages. |

MIN
(minimum) |
Identifies the lowest numeric value. |
Used for time duration and database counted metrics like Resolution Time and Chat Messages. |

MAX
(maximum) |
Identifies the highest numeric value. |
Used for time duration and database counted metrics like Resolution Time and Chat Messages. |

(standard deviation) |
Measures how far numeric values are spread out from their average value. If it is low the numeric values are close to the average. If it is high the numeric values are spread out. |
Used for time duration and database counted metrics like Resolution Time and Chat Messages. |

## Choosing the right metric aggregator

By default, metrics use the most relevant aggregator. In some situations, a different aggregator might better suit your reporting needs or you might need to decide which aggregator to use on a new calculated metric. Use the following sections to help you to decide which metric aggregator to use.

### COUNT and D_COUNT

**COUNT:**Counting all recorded values.**DCOUNT:**Counts only unique values.

In many cases, both aggregators will return the same results because the values they are counting are not repetitive. For example, if you count Ticket IDs in the Tickets dataset, the results for both aggregators are equal, because the ID of each ticket appears only once in this dataset. If you do the same in the Ticket Updates dataset, the COUNT aggregator returns a much higher result, because Ticket ID is recorded for each update.

### SUM

This aggregator is often used for database counters and arithmetical operation metrics, but it also can be used for duration metrics, for example, to calculate the total time spent by agents on calls or chats.

The database counted metrics are computed outside of Explore and appear in Explore as ready to use metrics. They normally measure the number of specific events or objects like Agent Replies, Assignee Stations, Reopens, or Chat Messages.

The arithmetical operation metrics are calculations created in Explore that perform numerical operations with existing metrics. For example, SUM should be used for % Satisfaction Score metric, which is a division of Good Satisfaction Tickets by Rated Satisfaction Tickets.

### AVG, MED, MIN, MAX, VARIANCE and STD_DEV

Team efficiency and performance is analyzed in Zendesk using time duration and database counted metrics aggregated using AVG, MED, MIN, MAX, VARIANCE and STD_DEV.

AVG and MED play a similar role in understanding the tendency of a metric. If the data you are comparing is mostly uniform then the AVG aggregator can be used. However, in many cases, Zendesk data has a high number of outliers, meaning that MED is the best option. See Average vs Median for a closer look at these aggregators.

The MIN and MAX aggregators can be used to identify the highest and lowest metric outliers.

VARIANCE and STD_DEV are more advanced analytical aggregators and are rarely used, but they are helpful in measuring how uniform or spread out the metric values are. If you never used these aggregators start with STD_DEV. Standard deviation is expressed in the same units as average and median aggregators and can be easily compared with them.

## 3 Comments

I am new to this Software but have been using Power BI for years. I am not sure why the program will not allow me to make averages of simple metrics such as the number of tickets solved per person.

Hi Chris, I'm sorry for the late response.

One way you could do this is (using the

Ticketsdataset) to add the metricSUM(Tickets solved - Daily average), and then addAssignee nameto theRowspanel.I hope this helps,

How can I rather than looking at the MED look at the 90% percentile for example? In our case, that's a lot more telling than the MED and it's much more the metric we would want to check.

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