The analytical features in Enneo provide a comprehensive view of the current state of a service organisation.
Central Data Tables
Enneo has three central data tables:
1. Ticket data
A ticket compiles all messages related to one of a customer’s topics, similar to a thread in GoogleMail. This dataset only includes tickets with data such as status (open/closed), SLA performance (timely resolved/not timely resolved), or skill category. With this dataset, using a filter on open tickets, one obtains an overview of the workload of the service center.
2. Incoming and outgoing messages
Exports the incoming and outgoing messages. A message is the original message of a ticket as well as replies from customers and/or agents including internal notes. The direction (incoming/outgoing) is defined by the direction column. This dataset provides insights into the incoming volume of a service center.
3. Export of edits
Exports all edits. A manual edit is always produced when a human user or an Enneo AI agent edits a ticket. This dataset provides insights into the performed workload of a service center, from teams or (depending on privacy settings) individual employees.
This dataset is described in detail here.
Relationship Between Data Tables
To illustrate the relationship between tickets, messages, and edits, here is an example:
| Activity | Tickets | Messages | Edits | Direction | Type | Edit Type |
|---|
| Customer sends an email | 1 | 1 | 0 | in | Initial | |
| Employee replies + closes | 1 | 2 | 1 | out | Subsequent | With reply |
| Employee writes note | 1 | 3 | 1 | internal | Subsequent | |
| Customer has a follow-up question | 1 | 4 | 1 | in | Subsequent | |
| Customer asks another question | 1 | 5 | 1 | in | Subsequent | |
| Employee: Status pending | 1 | 5 | 2 | | | Set as pending |
| Employee writes note | 1 | 6 | 2 | internal | Subsequent | |
| Employee assigns colleague | 1 | 6 | 2 | | Subsequent | |
| Colleague closes ticket | 1 | 6 | 3 | | | Without reply |
| Sum | 1 | 6 | 3 | | | |
