Create and manage a Case Classification (CC) model
Create and manage a Case Classification (CC) model
Coveo Machine Learning (Coveo ML) Case Classification (CC) models complement the Case Classification functionality of the Coveo Administration Console Case Assist (platform-ca | platform-eu | platform-au) page.
When you choose to generate case classification suggestions based on context recognition, you must configure a Coveo ML CC model to render classification suggestions in cases. Coveo ML CC models learn from support cases that have been correctly classified to provide classification suggestions on cases that haven’t yet been classified.
On your support website, users can contact your support team by filling a support case. Under the hood, your Contact Support form contains a Case Classification model that’s been configured to provide suggestions based on context recognition, which means that the feature is powered by a Coveo ML CC model.
A user accesses your support website to fill a support case and enters the following information:
-
Case Subject: Speedbit watch connection problem
-
Case Description: My Speedbit watch doesn’t connect with my smartphone.
Since the model has previously learned from the terms and classifications used by other users when filling their support cases, the model suggests the following classifications to the current user:
-
For the
@producttype
field: Speedbit, Watch -
For the
@issuetype
field: Connection, Bluetooth
Prerequisites
Before creating a Coveo ML CC model, ensure that the support cases you want to use to train the model meet the following data requirements:
Closed support cases
To help the model train from quality data, we recommend that you use closed
support cases when selecting the cases that must be used by the model. This allows the model to learn only from support cases that have already been resolved.
The Apply additional filters section of the model configuration allows you to segment the support cases on which the model bases its training.
You want the Coveo ML CC model to base its training only on closed support cases.
Therefore, in the Apply additional filters section, you enter sfstatus is equal to Closed
.
Sufficient data in the training fields
The text fields of the support cases from which you want the model to base its training must contain at least 10 characters to be considered by the model.
When configuring your Coveo ML CC model, you chose to train your model based on the subject
and description
fields.
Therefore, the model only takes into account the support cases that contain a minimum of 10 characters in both the subject
and description
fields for its learning process.
Sufficient classified support cases
Each field value that is to be predicted by the model must be part of at least 500 indexed support cases.
When configuring your Coveo ML CC model, in the Fields to predict section, you chose to provide predictions for the caseType
field.
In the support cases from which you chose to train the model, the caseType
field has three possible values: issue
, request
, and incident
.
Among the available support cases:
-
1007 have been classified as
issue
-
1885 have been classified as
request
-
283 have been classified as
incident
Since there are only 283 cases that have been classified as incident
, the model only provides issue
and request
as classification values for the caseType
field.
English support cases
The value of the index field that identifies the language of the support cases must be English
for the support cases to be considered by the model.
Create a CC model
|
Note
A Case Classification model can’t be edited once it’s created. Instead, you can create a new model with the required changes. |
-
Depending on whether models have already been created in your Coveo organization:
-
If your Coveo organization doesn’t contain any models, on the Models (platform-ca | platform-eu | platform-au) page, click the Case Classification card, and then click Create model.
-
If your Coveo organization already contains models, on the Models (platform-ca | platform-eu | platform-au) page, click Add model, and then click the Case Classification card.
-
-
Under Name, enter a meaningful display name for the model, and then click Next.
-
In the Learn from section, select the sources that contain the support cases from which the model should base its training.
NoteIf your Coveo organization includes multiple indexes, the model can learn only from sources that are linked to the default index.
-
(Optional) In the Apply additional filters section, you can specify a condition to segment the cases that the model should learn from.
-
(Optional) In the Edit default filters section, you can edit the default index fields that the model must use to identify the language and creation date of the support cases.
-
Click Next.
-
Select the index field corresponding to the unique identifier of your cases (e.g.,
sfcasenumber
). -
Select the case fields (input fields) that the model must use for its learning process (typically
subject
anddescription
).Notes-
For the model to learn from the fields chosen in this step, the scoped fields must contain between 10 and 3000 characters.
-
While we recommend using the
subject
anddescription
fields, you can use any other field that contains information that tends to solve cases, such asresolution
,summary
, andproblemDescription
.
-
-
Click Next.
-
In the Specify the output fields for which the model should provide predictions section, in the dropdown menu, select the fields that the model should provide predictions for (e.g.,
producttype
andissuetype
). Note that the selected fields must be of the Facet type, and can’t be of the Multi-Value Facet type.Leading practiceWe don’t recommend selecting fields for which generic values are available (e.g.,
other
ordefault
). -
Click Next.
-
In the Summary section, review your Coveo ML CC model configuration.
Once the model has been created, you cannot modify its configuration. If necessary, however, you can modify its name.
-
Click Add model.
Some of the support cases that have been targeted while configuring the model may later get filtered out because they can’t be used for training purposes. See CC model case filtering for details.
-
Associate the model with a Case Assist configuration.
|
If you have the Enterprise edition, group this CC model and your other implementation resources together in a project. See Manage projects. |
CC model case filtering
Some of the support cases that you scoped while configuring the model may get filtered out because they can’t be used for training purposes.
The model performs the following filtering process to ignore support cases for which:
-
Duplicated unique identifiers have been found. When the model finds cases with a duplicated unique identifier, it uses only one of them.
-
The selected input fields for prediction aren’t of the
string
data type. -
The selected input fields for prediction have only one or no possible values.
-
The selected input fields for prediction contain empty values.
-
The selected input fields for training contain empty values.
-
The selected input fields for training aren’t of the
string
orlist of strings
data types. -
The selected input fields for training contain less than 10, or more than 3,000 characters.
You can replicate how the model would filter some of the targeted support cases by using the Content Browser (platform-ca | platform-eu | platform-au) feature of the Coveo Administration Console.
You plan on creating a CC model with the following configuration:
-
Support cases from the
My Support Cases Source
. -
Uses support cases that have the
closed
status. -
Uses support cases that have been created in
October
,November
, andDecember
of2021
. -
Learns from support cases in
English
. -
Learns from support cases the have the
casenumber
field as the unique identifier. -
Uses the
description
andsubject
as input fields for training. -
Uses the
producttype
andissuetype
as output fields for prediction.
To see the indexed support cases that will be used by the model, you can enter the following query in the Content Browser:
(@status=="closed" @language=="English" @casenumber @sfcasenumber @subject @description @producttype @issuetype) ((@source=="My Support Cases Source") (@year==2021) (@month==(12,11,10)))
Delete a CC model
-
On the Models (platform-ca | platform-eu | platform-au) page, click the ML model that you want to delete, and then click More > Delete in the Action bar.
-
In the Delete a Model panel that appears, click Delete model.
Review active model information
On the Models (platform-ca | platform-eu | platform-au) page, click the desired model (must be Active), and then click Open in the Action bar (see Reviewing Coveo Machine Learning model information).
Reference
"Status" column
On the Models (platform-ca | platform-eu | platform-au) page of the Administration Console, the Status column indicates the current state of your Coveo ML models.
When inspecting the Status column, a given model is either in the Active or Inactive state. Additional information can be displayed depending on the model’s current state.

The following table lists the possible model statuses, their definitions, and their status colors as shown in the Administration Console:
Status | Definition | Status color |
---|---|---|
Active |
The model is active and available. |
|
Inactive |
The model isn’t available. |
|
Update in queue |
Waiting to process a scheduled update or configuration change. |
|
Updating |
The model is being rebuilt based on a new configuration. |
|
Waiting |
The model is in the building queue. |
|
Building |
The model is currently being processed. |
|
Degraded |
The model is active, but has some limitations. Additional information is available in the Error section of a model (see Review model information). |
|
Failed |
The model couldn’t be built with the requested configuration. Additional information is available in the Error section of a model (see Review model information). |
|
Update failed |
The model couldn’t be updated with the requested configuration. |
|
Error |
An error prevented the model from being built successfully. |
|
Archived |
The model was archived because it hasn’t been queried for at least 60 days. |
Filtering options
When configuring a Coveo ML CC model, you can specify additional filters to adapt how the model should learn from the data it receives.
The Apply additional filters section allows you to specify a condition to segment the cases that the model should learn from.
The Edit default filters section lets you modify the default filters used by the model to identify the language and creation date of the support cases.
"Apply Additional Filters" section
In this section, you can optionally specify a condition to segment the cases on which the model should base its training.
To avoid the model building on inaccurate information, we recommend that you only scope closed support cases.
You want the Coveo ML CC model to base its training only on closed support cases.
Therefore, in the Apply additional filters section, you enter sfstatus is equal to Closed
.
To specify an additional filter
-
In the Apply additional filters section, click
.
-
In the Add a Condition panel that opens, in the Field name input, enter the name of the field that you want to use to segment cases.
-
In the Select an operator dropdown menu, select the desired operator.
-
In the Value input, enter the value of the field on which you want to segment the cases.
-
Click Add filter.
"Edit Default Filters" section
In this section, you can optionally edit the default index fields that the model must use to identify the language and creation date of the support cases.
By default, the model uses the following field values:
-
Language: The value of the
language
field. -
Date: The value of the
date
field.
However, your support cases may use the value of different fields to identify their language and creation date.
The support cases you want to use to train your Coveo ML CC model use the following field values to identify their language and creation date:
-
Language: The value of the
sflanguage
field. -
Date: The value of the
sfcreationdate
field.
Therefore, you specify these fields in the Edit default filters section to instruct the model to use the sflanguage
and sfcreationdate
values rather than the default ones.
To edit the default language and date filters
-
In the Language dropdown menu, select the field that must identify the language of the support cases.
The value of the field that identifies the language of the support cases must be
English
for the support cases to be considered by the model. -
In the Date range section:
-
In the first dropdown menu, select the field that must identify the creation date of the support cases.
-
In the second dropdown menu, select the period of time for which the model should learn from support cases. By default, the model learns from the support cases created in the last 6 months. However, you can select one of the available preset ranges, or enter a custom date range.
Leading practiceWe recommend that you use a dynamic date range (i.e., Last 3 months, Last 6 months, or Last year) to train your model to ensure that it learns from the latest available data.
Using a fixed date range (e.g., from 2022/01/01 to 2022/06/01) results in the model always retraining on the same data.
-
Required privileges
By default, members with the required privileges can view and edit elements of the Models (platform-ca | platform-eu | platform-au) page.
The following table indicates the privileges required for members to manage Coveo CC models (see Manage privileges and Privilege reference).
Action | Service - Domain | Required access level |
---|---|---|
View models |
Machine Learning - Models |
View |
Manage models |
Organization - Organization |
View |
Machine Learning - Models |
Edit |
|
At least one of the following privileges:
|
Enable / Allowed |