Problem Statement

Support and service teams would typically want to manage their team workloads; which teams need more manpower, which teams are always having a long case duration, which types of cases can be reduced with self-service/knowledge base articles.

Typically these insights would be required to be monitored at a daily or weekly basis, with some insights raised at a monthly management meeting for decision making.

An example of Support and Service data structure

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Call Centre:

Service Ticket Desk:

Please refer to this article for more information about preparing data.


A segment is a qualitative value, like names or categories. Here are some of the typical segments we find in support and service data:

  • Case attributes: Case Resolution, Case Type, Outstanding Days Bracket, Time of Day, Priority, etc.

  • Team attributes: Team, Department, Agent, etc.

  • Other attributes: Channel, etc.


A measure is a quantitative, numeric value. Here are some of the typical measures we find in support & service data:

Case Metrics: Case Duration, Closed/Open/Reopen Count, Escalation Count, Outstanding Days, Interaction Duration

Team Metrics: Average Case per Team, Average Case Duration per Team, Number of Case

What sort of insights can Auto Insights help me uncover?

Identify patterns

  • Number of Cases against products this month compared to last month

  • Outstanding Days by Case Type this week

  • Number of Case filtered for Open Status by Case Type yesterday

Explore Team performances

  • Total Outstanding Days by Teams this week

  • Number of Cases comparing Outstanding Days bracket

  • Number of Cases specific for Complaints by Teams this week

  • Reopen Count by Teams this month

  • Escalation Count by Teams this month

  • Average Case per Team this week

Related material
How to prepare data

How to upload data
Quick guide to Auto Insights

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