Groupings

Groupings work by pulling like/matching data together to display results based on a specific field (e.g., Agent Name). Applying effective groupings can really help you better understand the data in a given report.

Applying a grouping to a report

Applying a grouping works like adding a new field to a report.

From the Grouping tab within the configuration side panel, click the (+) icon to add a grouping. From the resulting drop-down, select the field you want data grouped based on, and then click Build to apply the change.

In the images below, a report is being grouped by Agent Name.

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Unlike summary functions, a grouping doesn't exactly reduce or roll up the data to a single row. Rather, it creates a single row for each distinct value in the field being grouped. Grouping by Agent Name is common, as it allows for quick comparisons between different agents' metrics. 

Below is the output when a report's data is grouped by Agent Name. No other column or field has been summarized or grouped.

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Since Insights reduced the data to a single line per agent, there isn't a whole lot we can learn from what we see—the other columns are simply the top-most rows of interaction data for each agent.

In other words, the data in the Queue Call Manager ID, Wait Time, Agent Talk Time, and Agent Hold Time data is not holistic—it's simply showing the top row of data associated with that agent (representing only a single interaction for each agent, the one indicated by the QCMID).

Applying summary functions in tandem with a grouping

Building off of the report in the previous screenshot, it's worth going column-by-column to make sure the data displayed is accurate and unambiguous:

Agent Name

This is our grouping. If desired, this field could also have a filter or filter group applied to it, to highlight or exclude specific agents' data.

Queue Call Manager ID

Applying a simple COUNT to this field would make its data accurate, as it would then show the number of interactions each agent handled over the report's timeframe.

Wait Time, Agent Talk Time, Agent Hold Time

Here, we can add summary functions to output each agent's average (AVG) values for each metric:

Applying multiple groupings

Multiple groupings can be applied to a report.

If we wanted to parse this report's data by Communication Type in addition to by Agent Name, here's what results:

This report now shows how many interactions of each type each agent handled, and what each agent's average wait, talk, and hold times were.

With multiple groupings applied to a report, reordering the groupings impacts the displayed result.

Below, see the same report as in the previous screenshot, but with the groupings reordered:

Date/time grouping

In addition to being able to group data by virtually any desired field or fields, another type of grouping exists—date/time grouping. A date/time grouping can be used in addition to other groupings.

Switch the date/time grouping toggle to on. A drop-down menu will appear just to the right of the toggle, from which the desired interval for the grouping can be set. Options include by year, by month, by week, by day, by hour, and by minute.

The report below is grouped by Agent Name, Communication Type, and Date/Time (by day). This results in one line of data per agent, per communication type, per day. Specifically, the highlighted portion (below) shows Eric's metrics for chats handled, broken down to show his metrics for June 17, 18, and 19 (3 rows).